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A Daily Chronicle of AI Innovations in February 2024.
Welcome to the Daily Chronicle of AI Innovations in February 2024! This month-long blog series will provide you with the latest developments, trends, and breakthroughs in the field of artificial intelligence. From major industry conferences like ‘AI Innovations at Work’ to bold predictions about the future of AI, we will curate and share daily updates to keep you informed about the rapidly evolving world of AI. Join us on this exciting journey as we explore the cutting-edge advancements and potential impact of AI throughout February 2024.
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A Daily Chronicle of AI Innovations in February 2024 – Day 29: AI Daily News – February 29th, 2024

Alibaba’s EMO makes photos come alive (and lip-sync!)
Microsoft introduces 1-bit LLM
Ideogram launches text-to-image model version 1.0

Adobe launches new GenAI music tool
Morph makes filmmaking easier with Stability AI
Hugging Face, Nvidia, and ServiceNow release StarCode 2 for code generation.
Meta set to launch Llama 3 in July and could be twice the size
Apple subtly reveals its AI plans
OpenAI to put AI into humanoid robots
GitHub besieged by millions of malicious repositories in ongoing attack
Nvidia just released a new code generator that can run on most modern CPUs
Three more publishers sue OpenAI

Alibaba’s EMO makes photos come alive (and lip-sync!)
Researchers at Alibaba have introduced an AI system called “EMO” (Emote Portrait Alive) that can generate realistic videos of you talking and singing from a single photo and an audio clip. It captures subtle facial nuances without relying on 3D models.
EMO uses a two-stage deep learning approach with audio encoding, facial imagery generation via diffusion models, and reference/audio attention mechanisms.
Experiments show that the system significantly outperforms existing methods in terms of video quality and expressiveness.
Why does this matter?
By combining EMO with OpenAI’s Sora, we could synthesize personalized video content from photos or bring photos from any era to life. This could profoundly expand human expression. We may soon see automated TikTok-like videos.
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Microsoft introduces 1-bit LLM
Microsoft has launched a radically efficient AI language model dubbed 1-bit LLM. It uses only 1.58 bits per parameter instead of the typical 16, yet performs on par with traditional models of equal size for understanding and generating text.
Building on research like BitNet, this drastic bit reduction per parameter boosts cost-effectiveness relating to latency, memory, throughput, and energy usage by 10x. Despite using a fraction of the data, 1-bit LLM maintains accuracy.
Why does this matter?
Traditional LLMs often require extensive resources and are expensive to run while their swelling size and power consumption give them massive carbon footprints.
This new 1-bit technique points towards much greener AI models that retain high performance without overusing resources. By enabling specialized hardware and optimized model design, it can drastically improve efficiency and cut computing costs, with the ability to put high-performing AI directly into consumer devices.
Ideogram launches text-to-image model version 1.0
Ideogram has launched a new text-to-picture app called Ideogram 1.0. It’s their most advanced ever. Dubbed a “creative helper,” it generates highly realistic images from text prompts with minimal errors. A built-in “Magic Prompt” feature effortlessly expands basic prompts into detailed scenes.
The Details:
- Ideogram 1.0 significantly cuts image generation errors in half compared to other apps. And users can make custom picture sizes and styles. So it can do memes, logos, old-timey portraits, anything.
- Magic Prompt takes basic prompts like “vegetables orbiting the sun” and turns them into full scenes with backstories. That would take regular people hours to write out word-for-word.
Tests show that Ideogram 1.0 beats DALL-E 3 and Midjourney V6 at matching prompts, making sensible pictures, looking realistic, and handling text.
Why does this matter?
This advancement in AI image generation hints at a future where generative models commonly assist or even substitute human creators across personalized gift items, digital content, art, and more.
What Else Is Happening in AI on February 29th, 2024
Adobe launches new GenAI music tool
Adobe introduces Project Music GenAI Control, allowing users to create music from text or reference melodies with customizable tempo, intensity, and structure. While still in development, this tool has the potential to democratize music creation for everyone. (Link)
Morph makes filmmaking easier with Stability AI
Morph Studio, a new AI platform, lets you create films simply by describing desired scenes in text prompts. It also enables combining these AI-generated clips into complete movies. Powered by Stability AI, this revolutionary tool could enable anyone to become a filmmaker. (Link)
Hugging Face, Nvidia, and ServiceNow release StarCode 2 for code generation.
Hugging Face along with Nvidia and Service Now launches StarCoder 2, an open-source code generator available in three GPU-optimized models. With improved performance and less restrictive licensing, it promises efficient code completion and summarization. (Link)
Meta set to launch Llama 3 in July
Meta plans to launch Llama 3 in July to compete with OpenAI’s GPT-4. It promises increased responsiveness, better context handling, and double the size of its predecessor. With added tonality and security training, Llama 3 seeks more nuanced responses. (Link)
Apple subtly reveals its AI plans
Apple CEO Tim Cook reveals plans to disclose Apple’s generative AI efforts soon, highlighting opportunities to transform user productivity and problem-solving. This likely indicates exciting new iPhone and device features centered on efficiency. (Link)
A Daily Chronicle of AI Innovations in February 2024 – Day 28: AI Daily News – February 28th, 2024
NVIDIA’s Nemotron-4 beats 4x larger multilingual AI models
GitHub launches Copilot Enterprise for customized AI coding
Slack study shows AI frees up 41% of time spent on low-value work
Pika launches new lip sync feature for AI videos
Google pays publishers to test an unreleased GenAI tool
Intel and Microsoft team up to bring 100M AI PCs by 2025
Writer’s Palmyra-Vision summarizes charts, scribbles into text
Apple cancels its decade-long electric car project
OpenAI claims New York Times paid someone to ‘hack’ ChatGPT
Tumblr and WordPress blogs will be exploited for AI model training
Google CEO slams ‘completely unacceptable’ Gemini AI errors
Klarna’s AI bot is doing the work of 700 employees
NVIDIA’s Nemotron-4 beats 4x larger multilingual AI models
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Nvidia has announced Nemotron-4 15B, a 15-billion parameter multilingual language model trained on 8 trillion text tokens. Nemotron-4 shows exceptional performance in English, coding, and multilingual datasets. It outperforms all other open models of similar size on 4 out of 7 benchmarks. It has the best multilingual capabilities among comparable models, even better than larger multilingual models.
The researchers highlight how Nemotron-4 scales model training data in line with parameters instead of just increasing model size. As a result, inferences are computed faster, and latency is reduced. Due to its ability to fit on a single GPU, Nemotron-4 aims to be the best general-purpose model given practical constraints. It achieves better accuracy than the 34-billion parameter LLaMA model for all tasks and remains competitive with state-of-the-art models like QWEN 14B.
Why does this matter?
Just as past computing innovations improved technology access, Nemotron’s lean GPU deployment profile can expand multilingual NLP adoption. Since Nemotron fits on a single cloud graphics card, it dramatically reduces costs for document, query, and application NLP compared to alternatives requiring supercomputers. These models can help every company become fluent with customers and operations across countless languages.
GitHub launches Copilot Enterprise for customized AI coding
GitHub has launched Copilot Enterprise, an AI assistant for developers at large companies. The tool provides customized code suggestions and other programming support based on an organization’s codebase and best practices. Experts say Copilot Enterprise signals a significant shift in software engineering, with AI essentially working alongside each developer.
Copilot Enterprise integrates across the coding workflow to boost productivity. Early testing by partners like Accenture found major efficiency gains, with a 50% increase in builds from autocomplete alone. However, GitHub acknowledges skepticism around AI originality and bugs. The company plans substantial investments in responsible AI development, noting that Copilot is designed to augment human developers rather than replace them.
Why does this matter?
The entire software team could soon have an AI partner for programming. However, concerns about responsible AI development persist. Enterprises must balance rapidly integrating tools like Copilot with investments in accountability. How leadership approaches AI strategy now will separate future winners from stragglers.
Slack study shows AI frees up 41% of time spent on low-value work
Slack’s latest workforce survey shows a surge in the adoption of AI tools among desk workers. There has been a 24% increase in usage over the past quarter, and 80% of users are already seeing productivity gains. However, less than half of companies have guidelines around AI adoption, which may inhibit experimentation. The research also spotlights an opportunity to use AI to automate the 41% of workers’ time spent on repetitive, low-value tasks. And focus efforts on meaningful, strategic work.
While most executives feel urgency to implement AI, top concerns include data privacy and AI accuracy. According to the findings, guidance is necessary to boost employee adoption. Workers are over 5x more likely to have tried AI tools at companies with defined policies.
Why does this matter?
This survey signals AI adoption is already boosting productivity when thoughtfully implemented. It can free up significant time spent on repetitive tasks and allows employees to refocus on higher-impact work. However, to realize AI’s benefits, organizations must establish guidelines and address data privacy and reliability concerns. Structured experimentation with intuitive AI systems can increase productivity and data-driven decision-making.
OpenAI to put AI into humanoid robots
- OpenAI is collaborating with robotics startup Figure to integrate its AI technology into humanoid robots, marking the AI’s debut in the physical world.
- The partnership aims to develop humanoid robots for commercial use, with significant funding from high-profile investors including Jeff Bezos, Microsoft, Nvidia, and Amazon.
- The initiative will leverage OpenAI’s advanced AI models, such as GPT and DALL-E, to enhance the capabilities of Figure’s robots, aiming to address human labor shortages.
GitHub besieged by millions of malicious repositories in ongoing attack
- Hackers have automated the creation of malicious GitHub repositories by cloning popular repositories, infecting them with malware, and forking them thousands of times, resulting in hundreds of thousands of malicious repositories designed to steal information.
- The malware, hidden behind seven layers of obfuscation, includes a modified version of BlackCap-Grabber, which steals authentication cookies and login credentials from various apps.
- While GitHub uses artificial intelligence to block most cloned malicious packages, 1% evade detection, leading to thousands of malicious repositories remaining on the platform.
Nvidia just released a new code generator that can run on most modern CPUs
- Nvidia, ServiceNow, and Hugging Face have released StarCoder2, a series of open-access large language models for code generation, emphasizing efficiency, transparency, and cost-effectiveness.
- StarCoder2, trained on 619 programming languages, comes in three sizes: 3 billion, 7 billion, and 15 billion parameters, with the smallest model matching the performance of its predecessor’s largest.
- The platform highlights advancements in AI ethics and efficiency, utilizing a new code dataset for enhanced understanding of diverse programming languages and ensuring adherence to ethical AI practices by allowing developers to opt out of data usage.
Three more publishers sue OpenAI
- The Intercept, Raw Story, and AlterNet have filed lawsuits against OpenAI and Microsoft in the Southern District of New York, alleging copyright infringement through the training of AI models without proper attribution.
- The litigation claims that ChatGPT reproduces journalism works verbatim or nearly verbatim without providing necessary copyright information, suggesting that if trained properly, it could have included these details in its outputs.
- The suits argue that OpenAI and Microsoft knowingly risked copyright infringement for profit, evidenced by their provision of legal cover to customers and the existence of an opt-out system for web content crawling.
What Else Is Happening in AI on February 28th, 2024
Pika launches new lip sync feature for AI videos
Video startup Pika announced a new Lip Sync feature powered by ElevenLabs. Pro users can add realistic dialogue with animated mouths to AI-generated videos. Although currently limited, Pika’s capabilities offer customization of the speech style, text, or uploaded audio tracks, escalating competitiveness in the AI synthetic media space. (Link)
Google pays publishers to test an unreleased GenAI tool
Google is privately paying a group of publishers to test a GenAI tool. They need to summarize three articles daily based on indexed external sources in exchange for a five-figure annual fee. Google says this will help under-resourced news outlets, but experts say it could negatively affect original publishers and undermine Google’s news initiative. (Link)
Intel and Microsoft team up to bring 100M AI PCs by 2025
By collaborating with Microsoft, Intel aims to supply 100 million AI-powered PCs by 2025 and ramp up enterprise demand for efficiency gains. Despite Apple and Qualcomm’s push for Arm-based designs, Intel hopes to maintain its 76% laptop chip market share following post-COVID inventory corrections. (Link)
Writer’s Palmyra-Vision summarizes charts, scribbles into text
AI writing startup Writer announced a new capability of its Palmyra model called Palmyra-Vision. This model can generate text summaries from images, including charts, graphs, and handwritten notes. It can automate e-commerce merchandise descriptions, graph analysis, and compliance checking while recommending human-in-the-loop for accuracy. (Link)
Apple cancels its decade-long electric car project
Apple is canceling its decade-long electric vehicle project after spending over $10 billion. There were nearly 2,000 employees working on the effort known internally as Titan. After Apple announces the cancellation of its ambitious electric car project, some staff from the discontinued car team will shift to other teams such as Gen AI. (Link)
Nvidia’s New AI Laptops
Nvidia, the dominant force in graphics processing units (GPUs), has once again pushed the boundaries of portable computing. Their latest announcement showcases a new generation of laptops powered by the cutting-edge RTX 500 and 1000 Ada Generation GPUs. The focus here isn’t just on better gaming visuals – these laptops promise to transform the way we interact with artificial intelligence (AI) on the go.
Nvidia’s new laptop GPUs are purpose-built to accelerate AI workflows. Let’s break down the key components:
Specialized AI Hardware: The RTX 500 and 1000 GPUs feature dedicated Tensor Cores. These cores are the heart of AI processing, designed to handle complex mathematical operations involved in machine learning and deep learning at incredible speed.
Generative AI Powerhouse: These new GPUs bring a massive boost for generative AI applications like Stable Diffusion. This means those interested in creating realistic images from simple text descriptions can expect to see significant performance improvements.
Efficiency Meets Power: These laptops aren’t just about raw power. They’re designed to intelligently offload lighter AI tasks to a dedicated Neural Processing Unit (NPU) built into the CPU, conserving GPU resources for the most demanding jobs.
These advancements translate into a wide range of ground-breaking possibilities:
Photorealistic Graphics Enhanced by AI: Gamers can immerse themselves in more realistic and visually stunning worlds thanks to AI-powered technologies enhancing graphics rendering.
AI-Supercharged Productivity: From generating social media blurbs to advanced photo and video editing, professionals can complete creative tasks far more efficiently with AI assistance.
Real-time AI Collaboration: Features like AI-powered noise cancellation and background manipulation in video calls will elevate your virtual communication to a whole new level.
Nvidia’s latest AI-focused laptops have the potential to revolutionize the way we use our computers:
Portable Creativity: Whether you’re an artist, designer, or just someone who loves to experiment with AI art tools, these laptops promise a level of on-the-go creative freedom previously unimaginable.
Workplace Transformation: Industries from architecture to healthcare will see AI optimize processes and enhance productivity. These laptops put that power directly into the hands of professionals.
The Future is AI: AI is advancing at a blistering pace, and Nvidia is ensuring that we won’t be tied to our desks to experience it.
In short, Nvidia’s new generation of AI laptops heralds an era where high-performance, AI-driven computing becomes accessible to more people. This has the potential to spark a wave of innovation that we can’t even fully comprehend yet.
Original source here.

A Daily Chronicle of AI Innovations in February 2024 – Day 27: AI Daily News – February 27th, 2024
Tesla’s robot is getting quicker, better
Nvidia CEO: kids shouldn’t learn to code — they should leave it up to AI
Microsoft’s deal with Mistral AI faces EU scrutiny
Apple Vision Pro’s components cost $1,542—but that’s not the full story
PlayStation to axe 900 jobs and close studio
NVIDIA’s CEO Thinks That Our Kids Shouldn’t Learn How to Code As AI Can Do It for Them
During the latest World Government Summit in Dubai, Jensen Huang, the CEO of NVIDIA, spoke about the things our kids should and shouldn’t learn in the future. It may come as a surprise to many but Huang does think that our kids don’t need the knowledge of coding, just leave it to AI.
He mentioned that a decade ago, there was a belief that everyone needed to learn to code, and they were probably right, but based on what we see nowadays, the situation has changed due to achievements in AI, where everyone is literally a programmer.
He further talked about how kids may not necessarily need to learn how to code, and the focus should be on developing technology that allows for programming languages to be more human-like. In essence, traditional coding languages such as C++ or Java may become obsolete, as computers should be able to comprehend human language inputs.
Source: https://app.daily.dev/posts/vCwIfZOrx
Mistral Large: The new rival to GPT-4, 2nd best LLM of all time
The French AI startup Mistral has launched its largest-ever LLM and flagship model to date, Mistral Large, with a 32K context window. The model has top-tier reasoning capabilities, and you can use it for complex multilingual reasoning tasks, including text understanding, transformation, and code generation.
Due to a strong multitasking capability, Mistral Large is the world’s second-ranked model on MMLU (Massive multitask language understanding).
The model is natively fluent in English, French, Spanish, German, and Italian, with a nuanced understanding of grammar and cultural context. In addition to that, Mistral also shows top performance in coding and math tasks.
Mistral Large is now available via the in-house platform “La Plateforme” and Microsoft’s Azure AI via API.
Why does it matter?
Mistral Large stands out as the first model to truly challenge OpenAI’s dominance since GPT-4. It shows skills on par with GPT-4 for complex language tasks while costing 20% less. In this race to make their models better, it’s the user community that stands to gain the most. Also, the focus on European languages and cultures could make Mistral a leader in the European AI market.
DeepMind’s new gen-AI model creates video games in a flash
Google DeepMind has launched a new generative AI model – Genie (Generative Interactive Environment), that can create playable video games from a simple prompt after learning game mechanics from hundreds of thousands of gameplay videos.
Developed by the collaborative efforts of Google and the University of British Columbia, Genie can create side-scrolling 2D platformer games based on user prompts, like Super Mario Brothers and Contra, using a single image.
Trained on over 200,000 hours of gameplay videos, the experimental model can turn any image or idea into a 2D platformer.
Genie can be prompted with images it has never seen before, such as real-world photographs or sketches, enabling people to interact with their imagined virtual worlds-–essentially acting as a foundation world model. This is possible despite training without any action labels.
Why does it matter?
Genie creates a watershed moment in the generative AI space, becoming the first LLM to develop interactive, playable environments from a single image prompt. The model could be a promising step towards general world models for AGI (Artificial General Intelligence) that can understand and apply learned knowledge like a human. Lastly, Genie can learn fine-grained controls exclusively from Internet videos, a unique feature as Internet videos do not typically have labels.
Meta’s MobileLLM enables on-device AI deployment
Meta has released a research paper that addresses the need for efficient large language models that can run on mobile devices. The focus is on designing high-quality models with under 1 billion parameters, as this is feasible for deployment on mobiles.
By using deep and thin architectures, embedding sharing, and grouped-query attention, they developed a strong baseline model called MobileLLM, which achieves 2.7%/4.3% higher accuracy compared to previous 125M/350M state-of-the-art models. The research paper highlights that you should concentrate on developing an efficient model architecture rather than on data and parameter quantity to determine model quality.
Why does it matter?
With language understanding now possible on consumer devices, mobile developers can create products that were once hard to build because of latency or privacy issues when reliant on cloud connections. This advancement allows industries like finance, gaming, and personal health to integrate conversational interfaces, intelligent recommendations, and real-time data privacy protections using models optimized for mobile efficiency, sparking creativity in a new wave of intelligent apps.
What Else Is Happening in AI on February 27th, 2024
Qualcomm reveals 75+ pre-optimized AI models at MWC 2024
Qualcomm released 75+ new large language models, including popular generative models like Whisper and Stable Diffusion, optimized for the Snapdragon platform at the Mobile World Congress (MWC) 2024. The company stated that some of these LLMs will have generation AI capabilities for next-generation smartphones, PCs, IoT, XR devices, etc. (Link)
Nvidia launches new laptop GPUs for AI on the go
Nvidia launched RTX 500 and 1000 Ada Generation laptop graphics processing units (GPUs) at the MWC 2024 for on-the-go AI processing. These GPUs will utilize the Ada Lovelace architecture to provide content creators, researchers, and engineers with accelerated AI and next-generation graphic performance while working from portable devices. (Link)
Microsoft announces AI principles for boosting innovation and competition
Microsoft announced a set of principles to foster innovation and competition in the AI space. The move came to showcase its role as a market leader in promoting responsible AI and answer the concerns of rivals and antitrust regulators. The standard covers six key dimensions of responsible AI: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. (Link)
Google brings Gemini in Google Messages, Android Auto, Wear OS, etc.
Despite receiving some flakes from the industry, Google is riding the AI wave and decided to integrate Gemini into a new set of features for phones, cars, and wearables. With these new features, users can use Gemini to craft messages and AI-generated captions for images, summarize texts through AI for Android Auto, and access passes on Wear OS. (Link)
Microsoft Copilot GPTs help you plan your vacation and find recipes.
Microsoft has released a few copilot GPTs that can help you plan your next vacation, find recipes, learn how to cook them, create a custom workout plan, or design a logo for your brand. Microsoft corporate vice president Jordi Ribas informed the media that users will soon be able to create customized Copilot GPTs, which is missing in the current version of Copilot. (Link)
Tesla’s robot is getting quicker, better
- Elon Musk shared new footage showing improved mobility and speed of Tesla’s robot, Optimus Gen 2, which is moving more smoothly and steadily around a warehouse.
- The latest version of the Optimus robot is lighter, has increased walking speed thanks to Tesla-designed actuators and sensors, and demonstrates significant progress over previous models.
- Musk predicts the possibility of Optimus starting to ship in 2025 for less than $20,000, marking a significant milestone in Tesla’s venture into humanoid robotics capable of performing mundane or dangerous tasks for humans.
- Source
A Daily Chronicle of AI Innovations in February 2024 – Day 26: AI Daily News – February 26th, 2024
Google Deepmind announces Genie, the first generative interactive environment model
” We introduce Genie, the first generative interactive environment trained in an unsupervised manner from unlabelled Internet videos. The model can be prompted to generate an endless variety of action-controllable virtual worlds described through text, synthetic images, photographs, and even sketches. At 11B parameters, Genie can be considered a foundation world model. It is comprised of a spatiotemporal video tokenizer, an autoregressive dynamics model, and a simple and scalable latent action model. Genie enables users to act in the generated environments on a frame-by-frame basis despite training without any ground-truth action labels or other domain-specific requirements typically found in the world model literature. Further the resulting learned latent action space facilitates training agents to imitate behaviors from unseen videos, opening the path for training generalist agents of the future. “
I asked GPT4 to read through the article and summarize ELI5 style bullet points:
Who Wrote This?
A group of smart people at Google DeepMind wrote the article. They’re working on making things better for turning text into webpages.
What Did They Do?
They created something called “Genie.” It’s like a magic tool that can take all sorts of ideas or pictures and turn them into a place you can explore on a computer, like making your own little video game world from a drawing or photo. They did this by watching lots and lots of videos from the internet and learning how things move and work in those videos.
How Does It Work?
They use something called “Genie” which is very smart and can understand and create new videos or game worlds by itself. You can even tell it what to do next in the world it creates, like moving forward or jumping, and it will show you what happens.
Why Is It Cool?
Because Genie can create new, fun worlds just from a picture or some words, and you can play in these worlds! It’s like having a magic wand to make up your own stories and see them come to life on a computer.
What’s Next?
Even though Genie is really cool, it’s not perfect. Sometimes it makes mistakes or can’t remember things for very long. But the people who made it are working to make it better, so one day, everyone might be able to create their own video game worlds just by imagining them.
Important Points:
They want to make sure this tool is used in good ways and that it’s safe for everyone. They’re not sharing it with everyone just yet because they want to make sure it’s really ready and won’t cause any problems.

Microsoft eases AI testing with new red teaming tool

Microsoft has released an open-source automation called PyRIT to help security researchers test for risks in generative AI systems before public launch. Historically, “red teaming” AI has been an expert-driven manual process requiring security teams to create edge case inputs and assess whether the system’s responses contain security, fairness, or accuracy issues. PyRIT aims to automate parts of this tedious process for scale.
PyRIT helps researchers test AI systems by inputting large datasets of prompts across different risk categories. It automatically interacts with these systems, scoring each response to quantify failures. This allows for efficient testing of thousands of input variations that could cause harm. Security teams can then take this evidence to improve the systems before release.
Why does this matter?
Microsoft’s release of the PyRIT toolkit makes rigorously testing AI systems for risks drastically more scalable. Automating parts of the red teaming process will enable much wider scrutiny for generative models and eventually raise their performance standards. PyRIT’s automation will also pressure the entire industry to step up evaluations if they want their AI trusted.
Transformers learn to plan better with Searchformer
A new paper from Meta introduces Searchformer, a Transformer model that exceeds the performance of traditional algorithms like A* search in complex planning tasks such as maze navigation and Sokoban puzzles. Searchformer is trained in two phases: first imitating A* search to learn general planning skills, then fine-tuning the model via expert iteration to find optimal solutions more efficiently.
The key innovation is the use of search-augmented training data that provides Searchformer with both the execution trace and final solution for each planning task. This enables more data-efficient learning compared to models that only see solutions. However, encoding the full reasoning trace substantially increases the length of training sequences. Still, Searchformer shows promising techniques for training AI to surpass symbolic planning algorithms.
Why does this matter?
Achieving state-of-the-art planning results shows that generative AI systems are advancing to develop human-like reasoning abilities. Mastering complex cognitive tasks like finding optimal paths has huge potential in AI applications that depend on strategic thinking and foresight. As other companies race to close this new gap in planning capabilities, progress in core areas like robotics and autonomy is likely to accelerate.
YOLOv9 sets a new standard for real-time object recognition
YOLO (You Only Look Once) is open-source software that enables real-time object recognition in images, allowing machines to “see” like humans. Researchers have launched YOLOv9, the latest iteration that achieves state-of-the-art accuracy with significantly less computational cost.
By introducing two new techniques, Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN), YOLOv9 reduces parameters by 49% and computations by 43% versus predecessor YOLOv8, while boosting accuracy on key benchmarks by 0.6%. PGI improves network updating for more precise object recognition, while GELAN optimizes the architecture to increase accuracy and speed.
Why does this matter?
The advanced responsiveness of YOLOv9 unlocks possibilities for mobile vision applications where computing resources are limited, like drones or smart glasses. More broadly, it highlights deep learning’s potential to match human-level visual processing speeds, encouraging technology advancements like self-driving vehicles.
What Else Is Happening in AI on February 26th, 2024
Apple tests internal ChatGPT-like tool for customer support
Apple recently launched a pilot program testing an internal AI tool named “Ask.” It allows AppleCare agents to generate technical support answers automatically by querying Apple’s knowledge base. The goal is faster and more efficient customer service. (Link)
ChatGPT gets an Android home screen widget
Android users can now access ChatGPT more easily through a home screen widget that provides quick access to the chatbot’s conversation and query modes. The widget is available in the latest beta version of the ChatGPT mobile app. (Link)
AWS adds open-source Mistral AI models to Amazon Bedrock
AWS announced it will be bringing two of Mistral’s high-performing generative AI models, Mistral 7B and Mixtral 8x7B, to its Amazon Bedrock platform for gen AI offerings in the near future. AWS chose Mistral’s cost-efficient and customizable models to expand the range of GenAI abilities for Bedrock users. (Link)
Montreal tests AI system to prevent subway suicides
The Montreal Transit Authority is testing an AI system that analyzes surveillance footage to detect warning signs of suicide risk among passengers. The system, developed with a local suicide prevention center, can alert staff to intervene and save lives. With current accuracy of 25%, the “promising” pilot could be implemented in two years. (Link)
Fast food giants embrace controversial AI worker tracking
Riley, an AI system by Hoptix, monitors worker-customer interactions in 100+ fast-food franchises to incentivize upselling. It tracks metrics like service speed, food waste, and upselling rates. Despite being a coaching tool, concerns exist regarding the imposition of unfair expectations on workers. (Link)
Mistral AI releases new model to rival GPT-4
- Mistral AI introduces “Mistral Large,” a large language model designed to compete with top models like GPT-4 and Claude 2, and “Le Chat,” a beta chat assistant, aiming to establish an alternative to OpenAI and Anthropic’s offerings.
- With aggressive pricing at $8 per million input tokens and $24 per million output tokens, Mistral Large offers a cost-effective solution compared to GPT-4’s pricing, supporting English, French, Spanish, German, and Italian.
- The startup also revealed a strategic partnership with Microsoft to offer Mistral models on the Azure platform, enhancing Mistral AI’s market presence and potentially increasing its customer base through this new distribution channel.
Gemini is about to slide into your DMs
- Google’s AI chatbot Gemini is being integrated into the Messages app as part of an Android update, aiming to make conversations more engaging and friend-like, initially available in English in select markets.
- Android Auto receives AI improvements for summarizing long texts or chat threads and suggesting context-based replies, enhancing safety and convenience for drivers.
- Google also introduces AI-powered accessibility features in Lookout and Maps, including screen reader enhancements and automatic generation of descriptions for images, to assist visually impaired users globally.
Microsoft tried to sell Bing to Apple in 2018
- Microsoft attempted to sell its Bing search engine to Apple in 2018, aiming to make Bing the default search engine for Safari, but Apple declined due to concerns over Bing’s search quality.
- The discussions between Apple and Microsoft were highlighted in Google’s court filings as evidence of competition in the search industry, amidst accusations against Google for monopolizing the web search sector.
- Despite Microsoft’s nearly $100 billion investment in Bing over two decades, the search engine only secures a 3% global market share, while Google continues to maintain a dominant position, paying billions to Apple to remain the default search engine on its devices.
Meta forms team to stop AI from tricking voters
- Meta is forming a dedicated task force to counter disinformation and harmful AI content ahead of the EU elections, focusing on rapid threat identification and mitigation.
- The task force will remove harmful content from Facebook, Instagram, and Threads, expand its fact-checking team, and introduce measures for users and advertisers to disclose AI-generated material.
- The initiative aligns with the Digital Services Act’s requirements for large online platforms to combat election manipulation, amidst growing concerns over the disruptive potential of AI and deepfakes in elections worldwide.
Samsung unveils the Galaxy Ring as way to ‘simplify everyday wellness’
- Samsung teased the new Galaxy Ring at Galaxy Unpacked, showcasing its ambition to introduce a wearable that is part of a future vision for ambient sensing.
- The Galaxy Ring, coming in three colors and various sizes, will feature sleep, activity, and health tracking capabilities, aiming to compete with products like the Oura Ring.
- Samsung plans to integrate the Galaxy Ring into a larger ecosystem, offering features like My Vitality Score and Booster Cards in the Galaxy Health app, to provide a more holistic health monitoring system.
Impact of AI on Freelance Jobs

AI Weekly Rundown (February 19 to February 26)
Major AI announcements from NVIDIA, Apple, Google, Adobe, Meta, and more.
NVIDIA presents OpenMathInstruct-1, a 1.8 million math instruction tuning dataset
– OpenMathInstruct-1 is a high-quality, synthetically generated dataset. It is 4x bigger than previous datasets and does not use GPT-4. The best model, OpenMath-CodeLlama-70B, trained on a subset of OpenMathInstruct-1, achieves which is competitive performance with the best gpt-distilled models.Apple is reportedly working on AI updates to Spotlight and Xcode
– AI features for Spotlight search could let iOS and macOS users make natural language requests to get weather reports or operate features deep within apps. Apple also expanded internal testing of new generative AI features for its Xcode and plans to release them to third-party developers this year.Microsoft arms white hat AI hackers with a new red teaming tool
– PyRIT, an open-source tool from Microsoft, automates the testing of generative AI systems for risks before their public launch. It streamlines the “red teaming” process, traditionally a manual task, by inputting large datasets of prompts and scoring responses to identify potential issues in security, fairness, or accuracy.Google has open-sourced Magika, its AI-powered file-type identification system
– It helps accurately detect binary and textual file types. Under the hood, Magika employs a custom, highly optimized deep-learning model, enabling precise file identification within milliseconds, even when running on a CPU.Groq’s new AI chip turbocharges LLMs, outperforms ChatGPT
– Groq, an AI chip startup, has developed a special AI hardware– the first-ever Language Processing Unit (LPU) that turbocharges LLMs and processes up to 500 tokens/second, which is far more superior than ChatGPT-3.5’s 40 tokens/second.Transformers learn to plan better with Searchformer
– Meta’s Searchformer, a Transformer model, outperforms traditional algorithms like A* search in complex planning tasks. It’s trained to imitate A* search for general planning skills and then fine-tuned for optimal solutions using expert iteration and search-augmented training data.Apple tests internal chatGPT-like tool for customer support
– Apple recently launched a pilot program testing an internal AI tool named “Ask.” It allows AppleCare agents to automatically generate technical support answers by querying Apple’s knowledge base. The goal is faster and more efficient customer service.BABILong: The new benchmark to assess LLMs for long docs
– The paper uncovers limitations in GPT-4 and RAG, showing reliance on the initial 25% of input. BABILong evaluates GPT-4, RAG, and RMT, revealing that conventional methods are effective for 10^4 elements, while recurrent memory augmentation handles 10^7 elements, thereby setting a new advancement for long doc understanding.Stanford’s AI model identifies sex from brain scans with 90% accuracy
– Stanford medical researchers have developed an AI model that can identify the sex of individuals from brain scans with 90% accuracy. The model focuses on dynamic MRI scans, identifying specific brain networks to distinguish males and females.Adobe’s new AI assistant manages documents for you
– Adobe introduced an AI assistant for easier document navigation, answering questions, and summarizing information. It locates key data, generates citations, and formats brief overviews for presentations and emails to save time. Moreover, Adobe introduced CAVA, a new 50-person AI research team focused on inventing new models and processes for AI video creation.Meta released Aria recordings to fuel smart speech recognition
– The Meta team released a multimodal dataset of two-sided conversations captured by Aria smart glasses. It contains audio, video, motion, and other sensor data. The diverse signals aim to advance speech recognition and translation research for augmented reality interfaces.AWS adds open-source Mistral AI models to Amazon Bedrock
– AWS announced it will be bringing two of Mistral’s high-performing generative AI models, Mistral 7B and Mixtral 8x7B, to its Amazon Bedrock platform for GenAI offerings in the near future. AWS chose Mistral’s cost-efficient and customizable models to expand the range of GenAI abilities for Bedrock users.Penn’s AI chip runs on light, not electricity
– Penn engineers developed a new photonic chip that performs complex math for AI. It reduces processing time and energy consumption using light waves instead of electricity. This design uses optical computing principles developed by Penn professor Nader Engheta and nanoscale silicon photonics to train and infer neural networks.Google launches its first open-source LLM
– Google has open-sourced Gemma, a lightweight yet powerful new family of language models that outperforms larger models on NLP benchmarks but can run on personal devices. The release also includes a Responsible Generative AI Toolkit to assist developers in safely building applications with Gemma, now accessible through Google Cloud, Kaggle, Colab and other platforms.AnyGPT is a major step towards artificial general intelligence
– Researchers in Shanghai have developed AnyGPT, a groundbreaking new AI model that can understand and generate data across virtually any modality like text, speech, images and music using a unified discrete representation. It achieves strong zero-shot performance comparable to specialized models, representing a major advance towards AGI.Google launches Gemini for Workspace:
Google has launched Gemini for Workspace, bringing Gemini’s capabilities into apps like Docs and Sheets to enhance productivity. The new offering comes in Business and Enterprise tiers and features AI-powered writing assistance, data analysis, and a chatbot to help accelerate workflows.Stable Diffusion 3 – A multi-subject prompting text-to-image model
– Stability AI’s Stable Diffusion 3 is generating excitement in the AI community due to its improved text-to-image capabilities, including better prompt adherence and image quality. The early demos have shown remarkable improvements in generation quality, surpassing competitors such as MidJourney, Dall-E 3, and Google ImageFX.LongRoPE: Extending LLM context window beyond 2 million tokens
– Microsoft’s LongRoPE extends large language models to 2048k tokens, overcoming challenges of high fine-tuning costs and scarcity of long texts. It shows promising results with minor modifications and optimizations.Google Chrome introduces “Help me write” AI feature
– Google’s “Help me write” is an experimental AI feature on its Chrome browser that offers writing suggestions for short-form content. It highlights important features mentioned on a product page and can be accessed by enabling Chrome’s Experimental AI setting.Montreal tests AI system to prevent subway suicides
– The Montreal transit authority is testing an AI system that analyzes surveillance footage to detect warning signs of suicide risk among passengers. The system, developed with a local suicide prevention center, can alert staff to intervene and save lives. With current accuracy of 25%, the “promising” pilot could be implemented in two years.Fast food giants embrace controversial AI worker tracking
– Riley, an AI system by Hoptix, monitors worker-customer interactions in 100+ fast food franchises to incentivize upselling. It tracks metrics like service speed, food waste, and upselling rates. Despite being a coaching tool, concerns exist regarding the imposition of unfair expectations on workers.
And there was more…
– SoftBank’s founder is seeking about $100 billion for an AI chip venture
– ElevenLabs teases a new AI sound effects feature
– NBA commissioner Adam Silver demonstrates NB-AI concept
– Reddit signs AI content licensing deal ahead of IPO
– ChatGPT gets an Android homescreen widget
– YOLOv9 sets a new standard for real-time object recognition
– Mistral quietly released a new model in testing called ‘next’
– Microsoft to invest $2.1 billion for AI infrastructure expansion in Spain
– Graphcore explores sales talk with OpenAI, Softbank, and Arm
– OpenAI’s Sora can craft impressive video collages
– US FTC proposes a prohibition law on AI impersonation
– Meizu bids farewell to the smartphone market; shifts focus on AI
– Microsoft develops server network cards to replace NVIDIA’s cards
– Wipro and IBM team up to accelerate enterprise AI
– Deutsche Telekom revealed an AI-powered app-free phone concept
– Tinder fights back against AI dating scams
– Intel lands a $15 billion deal to make chips for Microsoft
– DeepMind forms new unit to address AI dangers
– Match Group bets on AI to help its workers improve dating apps
– Google Play Store tests AI-powered app recommendations
– Google cut a deal with Reddit for AI training data
– GPT Store introduces linking profiles, ratings, and enhanced ‘About’ pages
– Microsoft introduces a generative erase feature for AI-editing photos in Windows 11
– Suno AI V3 Alpha is redefining music generation
– Jasper acquires image platform Clipdrop from Stability AI
A Daily Chronicle of AI Innovations in February 2024 – Day 24: AI Daily News – February 24th, 2024
Google’s chaotic AI strategy
- Google’s AI strategy has resulted in confusion among consumers due to a rapid succession of new products, names, and features, compromising public trust in both AI and Google itself.
- The company has launched a bewildering array of AI products with overlapping and inconsistent naming schemes, such as Bard transforming into Gemini, alongside multiple versions of Gemini, complicating user understanding and adoption.
- Google’s rushed approach to competing with rivals like OpenAI has led to a chaotic rollout of AI offerings, leaving customers and even its own employees mocking the company’s inability to provide clear and accessible AI solutions.
- Source
Filmmaker puts $800 million studio expansion on hold because of OpenAI’s Sora
- Tyler Perry paused a $800 million expansion of his Atlanta studio after being influenced by OpenAI’s video AI model Sora, expressing concerns over AI’s impact on the film industry and job losses.
- Perry has started utilizing AI in film production to save time and costs, for example, in applying aging makeup, yet warns of the potential job displacement this technology may cause.
- The use of AI in Hollywood has led to debates on its implications for jobs, with calls for regulation and fair compensation, highlighted by actions like strikes and protests by SAG-AFTRA members.
- Source
Google explains Gemini’s ‘embarrassing’ AI pictures
- Google addressed the issue of Gemini AI producing historically inaccurate images, such as racially diverse Nazis, attributing the error to tuning issues within the model.
- The problem arose from the AI’s overcompensation in its attempt to show diversity, leading to inappropriate image generation and an overly cautious approach to generating images of specific ethnicities.
- Google has paused the image generation feature in Gemini since February 22, with plans to improve its accuracy and address the challenge of AI-generated “hallucinations” before reintroducing the feature.
- Source
Apple tests internal ChatGPT-like AI tool for customer support
- Apple is conducting internal tests on a new AI tool named “Ask,” designed to enhance the speed and efficiency of technical support provided by AppleCare agents.
- The “Ask” tool generates answers to customer technical queries by leveraging Apple’s internal knowledge base, allowing agents to offer accurate, clear, and useful assistance.
- Beyond “Ask,” Apple is significantly investing in AI, developing its own large language model framework, “Ajax,” and a chatbot service, “AppleGPT”.
- Source
Figure AI’s humanoid robots attract funding from Microsoft, Nvidia, OpenAI, and Jeff Bezos
- Jeff Bezos, Nvidia, and other tech giants are investing in Figure AI, a startup developing human-like robots, raising about $675 million at a valuation of roughly $2 billion.
- Figure’s robot, named Figure 01, is designed to perform dangerous jobs unsuitable for humans, with the company aiming to address labor shortages.
- The investment round, initially seeking $500 million, attracted widespread industry support, including contributions from Microsoft, Amazon-affiliated funds, and venture capital firms, marking a significant push into AI-driven robotics.
- Source
A Daily Chronicle of AI Innovations in February 2024 – Day 23: AI Daily News – February 23rd, 2024
Stable Diffusion 3 creates jaw-dropping images from text

LongRoPE: Extending LLM context window beyond 2 million token
Google Chrome introduces “Help me write” AI feature

Jasper acquires image platform Clipdrop from Stability AI
Suno AI V3 Alpha is redefining music generation.
GPT Store introduces linking profiles, ratings, and enhanced about pages.
Microsoft introduces a generative erase feature for AI-editing photos in Windows 11.
Google cut a deal with Reddit for AI training data.
Stable Diffusion 3 creates jaw-dropping text-to-images!
Stability.AI announced the Stable Diffusion 3 in an early preview. It is a text-to-image model with improved performance in multi-subject prompts, image quality, and spelling abilities. Stability.AI has opened the model waitlist and introduced a preview to gather insights before the open release.
Stability AI’s Stable Diffusion 3 preview has generated significant excitement in the AI community due to its superior image and text generation capabilities. This next-generation image tool promises better text generation, strong prompt adherence, and resistance to prompt leaking, ensuring the generated images match the requested prompts.
Why does it matter?
The announcement of Stable Diffusion 3 is a significant development in AI image generation because it introduces a new architecture with advanced features such as the diffusion transformer and flow matching. The early demos of Stable Diffusion 3 have shown remarkable improvements in overall generation quality, surpassing its competitors such as MidJourney, Dall-E 3, and Google ImageFX.
LongRoPE: Extending LLM context window beyond 2 million tokens
Researchers at Microsoft have introduced LongRoPE, a groundbreaking method that extends the context window of pre-trained large language models (LLMs) to an impressive 2048k tokens.
Current extended context windows are limited to around 128k tokens due to high fine-tuning costs, scarcity of long texts, and catastrophic values introduced by new token positions. LongRoPE overcomes these challenges by leveraging two forms of non-uniformities in positional interpolation, introducing a progressive extension strategy, and readjusting the model on shorter context windows.
Experiments on LLaMA2 and Mistral across various tasks demonstrate the effectiveness of LongRoPE. The extended models retain the original architecture with minor positional embedding modifications and optimizations.
Why does it matter?
LongRoPE extends the context window in LLMs and opens up possibilities for long-context tasks beyond 2 million tokens. This is the highest supported token, especially when other models like Google Gemini Pro have capabilities of up to 1 million tokens. Another major impact it will have is an extended context window for open-source models, unlike top proprietary models.
Google Chrome introduces “Help me write” AI feature
Google has recently rolled out an experimental AI feature called “Help me write” for its Chrome browser. This feature, powered by Gemini, aims to assist users in writing or refining text based on webpage content. It focuses on providing writing suggestions for short-form content, such as filling in digital surveys and reviews and drafting descriptions for items being sold online.
The tool can understand the webpage’s context and pull relevant information into its suggestions, such as highlighting critical features mentioned on a product page for item reviews. Users can right-click on an open text field on any website to access the feature on Google Chrome.
This feature is currently only available for English-speaking Chrome users in the US on Mac and Windows PCs. To access this tool, users in the US can enable Chrome’s Experimental AI under the “Try out experimental AI features” setting.
Why does it matter?
Google Chrome’s “Help me write” AI feature can aid users in completing surveys, writing reviews, and drafting product descriptions. However, it is still in its early stages and may not inspire user confidence compared to Microsoft’s Copilote on Edge browser. Adjusting the prompts and resulting text can negate any time-saving benefits, leaving the effectiveness of this feature for Google Chrome users open for debate.
What Else Is Happening in AI on February 23rd, 2024
Google cut a deal with Reddit for AI training data.
Google and Reddit have formed a partnership that will benefit both companies. Google will pay $60 million per year for real-time access to Reddit’s data, while Reddit will gain access to Google’s Vertex AI platform. This will help Google train its AI and ML models at scale while also giving Reddit expanded access to Google’s services. (Link)
GPT Store introduces linking profiles, ratings, and enhanced about pages.
OpenAI’s GPT Store platform has new features. Builders can link their profiles to GitHub and LinkedIn, and users can leave ratings and feedback. The About pages for GPTs have also been enhanced. T (Link)
Microsoft introduces a generative erase feature for AI-editing photos in Windows 11.
Microsoft’s Photos app now has a Generative Erase feature powered by AI. It enables users to remove unwanted elements from their photos, including backgrounds. The AI edit features are currently available to Windows Insiders, and Microsoft plans to roll out the tools to Windows 10 users. However, there is no clarity on whether AI-edited photos will have watermarks or metadata to differentiate them from unedited photos. (Link)
Suno AI V3 Alpha is redefining music generation.
The V3 Alpha version of Suno AI’s music generation platform offers significant improvements, including better audio quality, longer clip length, and expanded language coverage. The update aims to redefine the state-of-the-art for generative music and invites user feedback with 300 free credits given to paying subscribers as a token of appreciation. (Link)
Jasper acquires image platform Clipdrop from Stability AI
Jasper acquires AI image creation and editing platform Clipdrop from Stability AI, expanding its conversational AI toolkit with visual capabilities for a comprehensive multimodal marketing copilot. The Clipdrop team will work in Paris to contribute to research and innovation on multimodality, furthering Jasper’s vision of being the most all-encompassing end-to-end AI assistant for powering personalized marketing and automation. (Link)
A Daily Chronicle of AI Innovations in February 2024 – Day 22: AI Daily News – February 22nd, 2024
Google suspends Gemini from making AI images after backlash
- Google has temporarily halted the ability of its Gemini AI to create images of people following criticisms over its generation of historically inaccurate and racially diverse images, such as those of US Founding Fathers and Nazi-era soldiers.
- This decision comes shortly after Google issued an apology for the inaccuracies in some of the historical images generated by Gemini, amid backlash and conspiracy theories regarding the depiction of race and gender.
- Google plans to improve Gemini’s image generation capabilities concerning people and intends to re-release an enhanced version of this feature in the near future, aiming for more accurate and sensitive representations.
- Source
Nvidia posts revenue up 265% on booming AI business
- Nvidia’s data center GPU sales soared by 409% due to a significant increase in demand for AI chips, with the company reporting $18.4 billion in revenue for this segment.
- The company exceeded Wall Street’s expectations in its fourth-quarter financial results, projecting $24 billion in sales for the current quarter against analysts’ forecasts of $22.17 billion.
- Nvidia has become a key player in the AI industry, with massive demand for its GPUs from tech giants and startups alike, spurred by the growth in generative AI applications.
- Source
Microsoft and Intel strike a custom chip deal that could be worth billions
- Intel will produce custom chips designed by Microsoft in a deal valued over $15 billion, although the specific applications of these chips remain unspecified.
- The chips will utilize Intel’s 18A process, marking a significant step in Intel’s strategy to lead in chip manufacturing by offering foundry services for custom chip designs.
- Intel’s move to expand its foundry services and collaborate with Microsoft comes amidst challenges, including the delayed opening of a $20 billion chip plant in Ohio.
- Source
AI researchers’ open letter demands action on deepfakes before they destroy democracy
- An open letter from AI researchers demands government action to combat deepfakes, highlighting their threat to democracy and proposing measures such as criminalizing deepfake child pornography.
- The letter warns about the rapid increase of deepfakes, with a 550% rise between 2019 and 2023, detailing that 98% of deepfake videos are pornographic, predominantly victimizing women.
- Signatories, including notable figures like Jaron Lanier and Frances Haugen, advocate for the development and dissemination of content authentication methods to distinguish real from manipulated content.
- Source
Stability AI’s Stable Diffusion 3 preview boasts superior image and text generation capabilities
- Stability AI introduces Stable Diffusion 3, showcasing enhancements in image generation, complex prompt execution, and text-generation capabilities.
- The model incorporates the Diffusion Transformer Architecture with Flow Matching, ranging from 800 million to 8 billion parameters, promising a notable advance in AI-driven content creation.
- Despite its potential, Stability AI takes rigorous safety measures to mitigate misuse and collaborates with the community, amidst concerns over training data and the ease of modifying open-source models.
- Source
Google releases its first open-source LLM

Google has open-sourced Gemma, a new family of state-of-the-art language models available in 2B and 7B parameter sizes. Despite being lightweight enough to run on laptops and desktops, Gemma models have been built with the same technology used for Google’s massive proprietary Gemini models and achieve remarkable performance – the 7B Gemma model outperforms the 13B LLaMA model on many key natural language processing benchmarks.
Alongside the Gemma models, Google has released a Responsible Generative AI Toolkit to assist developers in building safe applications. This includes tools for robust safety classification, debugging model behavior, and implementing best practices for deployment based on Google’s experience. Gemma is available on Google Cloud, Kaggle, Colab, and a few other platforms with incentives like free credits to get started.
AnyGPT: A major step towards artificial general intelligence
Researchers in Shanghai have achieved a breakthrough in AI capabilities with the development of AnyGPT – a new model that can understand and generate data in virtually any modality, including text, speech, images, and music. AnyGPT leverages an innovative discrete representation approach that allows a single underlying language model architecture to smoothly process multiple modalities as inputs and outputs.
The researchers synthesized the AnyInstruct-108k dataset, containing 108,000 samples of multi-turn conversations, to train AnyGPT for these impressive capabilities. Initial experiments show that AnyGPT achieves zero-shot performance comparable to specialized models across various modalities.
Google launches Gemini for Workspace
Google has rebranded its Duet AI for Workspace offering as Gemini for Workspace. This brings the capabilities of Gemini, Google’s most advanced AI model, into Workspace apps like Docs, Sheets, and Slides to help business users be more productive.
The new Gemini add-on comes in two tiers – a Business version for SMBs and an Enterprise version. Both provide AI-powered features like enhanced writing and data analysis, but Enterprise offers more advanced capabilities. Additionally, users get access to a Gemini chatbot to accelerate workflows by answering questions and providing expert advice. This offering pits Google against Microsoft, which has a similar Copilot experience for commercial users.
What Else Is Happening in AI on February 22nd, 2024
Intel lands a $15 billion deal to make chips for Microsoft
Intel will produce over $15 billion worth of custom AI and cloud computing chips designed by Microsoft, using Intel’s cutting-edge 18A manufacturing process. This represents the first major customer for Intel’s foundry services, a key part of CEO Pat Gelsinger’s plan to reestablish the company as an industry leader. (Link)
DeepMind forms new unit to address AI dangers
Google’s DeepMind has created a new AI Safety and Alignment organization, which includes an AGI safety team and other units working to incorporate safeguards into Google’s AI systems. The initial focus is on preventing bad medical advice and bias amplification, though experts believe hallucination issues can never be fully solved. (Link)
Match Group bets on AI to help its workers improve dating apps
Match Group, owner of dating apps like Tinder and Hinge, has signed a deal to use ChatGPT and other AI tools from OpenAI for over 1,000 employees. The AI will help with coding, design, analysis, templates, and communications. All employees using it will undergo training on responsible AI use. (Link)
Fintechs get a new ally against financial crime
Hummingbird, a startup offering tools for financial crime investigations, has launched a new product called Automations. It provides pre-built workflows to help financial investigators automatically gather information on routine crimes like tax evasion, freeing them up to focus on harder cases. Early customer feedback on Automations has been positive. (Link)
Google Play Store tests AI-powered app recommendations
Google is testing a new AI-powered “App Highlights” feature in the Play Store that provides personalized app recommendations based on user preferences and habits. The AI analyzes usage data to suggest relevant, high-quality apps to simplify discovery. (Link)
A Daily Chronicle of AI Innovations in February 2024 – Day 21: AI Daily News – February 21st, 2024
Introducing Gemma by Google – a family of lightweight, state-of-the-art open models for their class
#openmodels 1/n “Gemma open models Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide responsible use of Gemma models… Free credits for research and development Gemma is built for the open community of developers and researchers powering AI innovation. You can start working with Gemma today using free access in Kaggle, a free tier for Collab notebooks, and $300 in credits for first-time Google Cloud users. Researchers can also apply for Google Cloud credits of up to $500,000 to accelerate their projects”.
Gemini 1.5 will be ~20x cheaper than GPT4 – this is an existential threat to OpenAI

From what we have seen so far Gemini 1.5 Pro is reasonably competitive with GPT4 in benchmarks, and the 1M context length and in-context learning abilities are astonishing.
What hasn’t been discussed much is pricing. Google hasn’t announced specific number for 1.5 yet but we can make an educated projection based on the paper and pricing for 1.0 Pro.
Google describes 1.5 as highly compute-efficient, in part due to the shift to a soft MoE architecture. I.e. only a small subset of the experts comprising the model need to be inferenced at a given time. This is a major improvement in efficiency from a dense model in Gemini 1.0.
And though it doesn’t specifically discuss architectural decisions for attention the paper mentions related work on deeply sub-quadratic attention mechanisms enabling long context (e.g. Ring Attention) in discussing Gemini’s achievement of 1-10M tokens. So we can infer that inference costs for long context are relatively manageable. And videos of prompts with ~1M context taking a minute to complete strongly suggest that this is the case barring Google throwing an entire TPU pod at inferencing an instance.
Putting this together we can reasonably expect that pricing for 1.5 Pro should be similar to 1.0 Pro. Pricing for 1.0 Pro is $0.000125 / 1K characters.
Compare that to $0.01 / 1K tokens for GPT4-Turbo. Rule of thumb is about 4 characters / token, so that’s $0.0005 for 1.5 Pro vs $0.01 for GPT-4, or a 20x difference in Gemini’s favor.
So Google will be providing a model that is arguably superior to GPT4 overall at a price similar to GPT-3.5.
If OpenAI isn’t able to respond with a better and/or more efficient model soon Google will own the API market, and that is OpenAI’s main revenue stream.
Adobe’s new AI assistant manages your docs

Adobe launched an AI assistant feature in its Acrobat software to help users navigate documents. It summarizes content, answers questions, and generates formatted overviews. The chatbot aims to save time working with long files and complex information. Additionally, Adobe created a dedicated 50-person AI research team called CAVA (Co-Creation for Audio, Video, & Animation) focused on advancing generative video, animation, and audio creation tools.
While Adobe already has some generative image capabilities, CAVA signals a push into underserved areas like procedurally assisted video editing. The research group will explore integrating Adobe’s existing creative tools with techniques like text-to-video generation. Adobe prioritizes more AI-powered features to boost productivity through faster document understanding or more automated creative workflows.
Why does this matter?
Adobe injecting AI into PDF software and standing up an AI research group signals a strategic push to lead in generative multimedia. Features like summarizing documents offer faster results, while envisaged video/animation creation tools could redefine workflows.
Meta released Aria recordings to fuel smart speech recognition
Meta has released a multi-modal dataset of two-person conversations captured on Aria smart glasses. It contains audio across 7 microphones, video, motion sensors, and annotations. The glasses were worn by one participant while speaking spontaneously with another compensated contributor.
The dataset aims to advance research in areas like speech recognition, speaker ID, and translation for augmented reality interfaces. Its audio, visual, and motion signals together provide a rich capture of natural talking that could help train AI models. Such in-context glasses conversations can enable closed captioning and real-time language translation.
Why does this matter?
By capturing real-world sensory signals from glasses-framed conversations, Meta bridges the gaps AI faces to achieve human judgment. Enterprises stand to gain more relatable, trustworthy AI helpers that feel less robotic and more attuned to nuances when engaging customers or executives.
Penn’s AI chip runs on light, not electricity
Penn engineers have developed a photonic chip that uses light waves for complex mathematics. It combines optical computing research by Professor Nader Engheta with nanoscale silicon photonics technology pioneered by Professor Firooz Aflatouni. With this unified platform, neural networks can be trained and inferred faster than ever.
It allows accelerated AI computations with low power consumption and high performance. The design is ready for commercial production, including integration into graphics cards for AI development. Additional advantages include parallel processing without sensitive data storage. The development of this photonic chip represents significant progress for AI by overcoming conventional electronic limitations.
Why does this matter?
Artificial intelligence chips enable accelerated training and inference for new data insights, new products, and even new business models. Businesses that upgrade key AI infrastructure like GPUs with photonic add-ons will be able to develop algorithms with significantly improved accuracy. With processing at light speed, enterprises have an opportunity to avoid slowdowns by evolving along with light-based AI.
What Else Is Happening in AI on February 21st, 2024
Brain chip: Neuralink patient moves mouse with thoughts
Elon Musk announced that the first human to receive a Neuralink brain chip has recovered successfully. The patient can now move a computer mouse cursor on a screen just by thinking, showing the chip’s ability to read brain signals and control external devices. (Link)
Microsoft develops server network cards to replace NVIDIA
Microsoft is developing its own networking cards. These cards move data quickly between servers, seeking to reduce reliance on NVIDIA’s cards and lower costs. Microsoft hopes its new server cards will boost the performance of the NVIDIA chip server currently in use and its own Maia AI chips. (Link)
Wipro and IBM team up to accelerate enterprise AI
Wipro and IBM are expanding their partnership, introducing the Wipro Enterprise AI-Ready Platform. Using IBM Watsonx AI, clients can create fully integrated AI environments. This platform provides tools, language models, streamlined processes, and governance, focusing on industry-specific solutions to advance enterprise-level AI. (Link)
Telekom’s next big thing: an app-free AI Phone
Deutsche Telekom revealed an AI-powered app-free phone concept at MWC 2024, featuring a digital assistant that can fulfill daily tasks via voice and text. Created in partnership with Qualcomm and Brain.ai, the concierge-style interface aims to simplify life by anticipating user needs contextually using generative AI. (Link)
Tinder fights back against AI dating scams
Tinder is expanding ID verification, requiring a driver’s license and video selfie to combat rising AI-powered scams and dating crimes. The new safeguards aim to build trust, authenticity, and safety, addressing issues like pig butchering schemes using AI-generated images to trick victims. (Link)
Google launches two new AI models
- Google has unveiled Gemma 2B and 7B, two new open-source AI models derived from its larger Gemini model, aiming to provide developers more freedom for smaller applications such as simple chatbots or summarizations.
- Gemma models, despite being smaller, are designed to be efficient and cost-effective, boasting significant performance on key benchmarks which allows them to run on personal computing devices.
- Unlike the closed Gemini model, Gemma is open source, making it accessible for a wider range of experimentation and development, and comes with a ‘responsible AI toolkit’ to help manage its open nature.
ChatGPT has meltdown and starts sending alarming messages to users
- ChatGPT has started malfunctioning, producing incoherent responses, mixing Spanish and English without prompt, and unsettling users by implying physical presence in their environment.
- The cause of the malfunction remains unclear, though OpenAI acknowledges the issue and is actively monitoring the situation, as evidenced by user-reported anomalies and official statements on their status page.
- Some users speculate that the erratic behavior may relate to the “temperature” setting of ChatGPT, which affects its creativity and focus, noting previous instances where ChatGPT’s responses became unexpectedly lazy or sassy.
An Apple smart ring may be imminent
- After years of research and filing several patent applications, Apple is reportedly close to launching a smart ring, spurred by Samsung’s tease of its own smart ring.
- The global smart ring market is expected to grow significantly, from $20 million in 2023 to almost $200 million by 2031, highlighting potential interest in health-monitoring wearable tech.
- Despite the lack of credible rumors or leaks, the number of patents filed by Apple suggests its smart ring development is advanced.
New hack clones fingerprints by listening to fingers swipe screens
- Researchers from the US and China developed a method, called PrintListener, to recreate fingerprints from the sound of swiping on a touchscreen, posing a risk to biometric security systems.
- PrintListener can achieve partial and full fingerprint reconstruction from fingertip friction sounds, with success rates of 27.9% and 9.3% respectively, demonstrating the technique’s potential threat.
- To mitigate risks, suggested countermeasures include using specialized screen protectors or altering interaction with screens, amid concerns over fingerprint biometrics market’s projected growth to $75 billion by 2032.
iMessage gets major update ahead of ‘quantum apocalypse’
- Apple is launching a significant security update in iMessage to protect against the potential threat of quantum computing, termed the “quantum apocalypse.”
- The update, known as PQ3, aims to secure iMessage conversations against both classical and quantum computing threats by redefining encryption protocols.
- Other companies, like Google, are also updating their security measures in anticipation of quantum computing challenges, with efforts being coordinated by the US National Institute of Standards and Technology (NIST).
A Daily Chronicle of AI Innovations in February 2024 – Day 20: AI Daily News – February 20th, 2024
Sora Explained in Layman terms
- Sora, an AI model, combines Transformer techniques, which power language models like GPT, with diffusion techniques to predict words and generate sentences and to predict colors and transform fuzzy canvases into coherent images, respectively.
- When a text prompt is inputted into Sora, it first employs a Transformer to extrapolate a more detailed video script from the given prompt. This script includes specific details such as camera angles, textures, and animations inferred from the text.
- The generated video script is then passed to the diffusion side of Sora, where the actual video output is created. Historically, diffusion was only capable of producing images, but Sora overcame this limitation by introducing a new technique called SpaceTime patches.
- SpaceTime patches act as an intermediary step between the Transformer and diffusion processes. They essentially break down the video into smaller pieces and analyze the pixel changes within each patch to learn about animation and physics.
- While computers don’t truly understand motion, they excel at predicting patterns, such as changes in pixel colors across frames. Sora was pre-trained to understand the animation of falling objects by learning from various videos depicting downward motion.
- By leveraging SpaceTime patches and diffusion, Sora can predict and apply the necessary color changes to transform a fuzzy video into the desired output. This approach is highly flexible and can accommodate videos of any format, making Sora a versatile and powerful tool for video production.
Sora’s ability to seamlessly integrate Transformer and diffusion techniques, along with its innovative use of SpaceTime patches, allows it to effectively translate text prompts into captivating and visually stunning videos. This remarkable AI creation has truly revolutionized the world of video production.
Groq’s New AI Chip Outperforms ChatGPT
Groq has developed a special AI hardware known as the first-ever Language Processing Unit (LPU) that aims to increase the processing power of current AI models that normally work on GPU. These LPUs can process up to 500 tokens/second, far superior to Gemini Pro and ChatGPT-3.5, which can only process between 30 and 50 tokens/second.
The company has designed its first-ever LPU-based AI chip named “GroqChip,” which uses a “tensor streaming architecture” that is less complex than traditional GPUs, enabling lower latency and higher throughput. This makes the chip a suitable candidate for real-time AI applications such as live-streaming sports or gaming.
Why does it matter?
Groq’s AI chip is the first-ever chip of its kind designed in the LPU system category. The LPUs developed by Groq can improve the deployment of AI applications and could present an alternative to Nvidia’s A100 and H100 chips, which are in high demand but have massive shortages in supply. It also signifies advancements in hardware technology specifically tailored for AI tasks. Lastly, it could stimulate further research and investment in AI chip design.
BABILong: The new benchmark to assess LLMs for long docs
The research paper delves into the limitations of current generative transformer models like GPT-4 when tasked with processing lengthy documents. It identifies a significant GPT-4 and RAG dependency on the initial 25% of input, indicating potential for enhancement. To address this, the authors propose leveraging recurrent memory augmentation within the transformer model to achieve superior performance.
Introducing a new benchmark called BABILong (Benchmark for Artificial Intelligence for Long-context evaluation), the study evaluates GPT-4, RAG, and RMT (Recurrent Memory Transformer). Results demonstrate that conventional methods prove effective only for sequences up to 10^4 elements, while fine-tuning GPT-2 with recurrent memory augmentations enables handling tasks involving up to 10^7 elements, highlighting its significant advantage.
Why does it matter?
The recurrent memory allows AI researchers and enthusiasts to overcome the limitations of current LLMs and RAG systems. Also, the BABILong benchmark will help in future studies, encouraging innovation towards a more comprehensive understanding of lengthy sequences.
Standford’s AI model identifies sex from brain scans with 90% accuracy
Standford medical researchers have developed a new-age AI model that determines the sex of individuals based on brain scans, with over 90% success. The AI model focuses on dynamic MRI scans, identifying specific brain networks—such as the default mode, striatum, and limbic networks—as critical in distinguishing male from female brains.
Why does it matter?
Over the years, there has been a constant debate in the medical field and neuroscience about whether sex differences in brain organization exist. AI has hopefully ended the debate once and for all. The research acknowledges that sex differences in brain organization are vital for developing targeted treatments for neuropsychiatric conditions, paving the way for a personalized medicine approach.
What Else Is Happening in AI on February 20th, 2024
Microsoft to invest $2.1 billion for AI infrastructure expansion in Spain.
Microsoft Vice Chair and President Brad Smith announced on X that they will expand their AI and cloud computing infrastructure in Spain via a $2.1 billion investment in the next two years. This announcement follows the $3.45 billion investment in Germany for the AI infrastructure, showing the priority of the tech giant in the AI space. (Link)
Graphcore explores sales talk with OpenAI, Softbank, and Arm.
The British AI chipmaker and NVIDIA competitor Graphcore is struggling to raise funding from investors and is seeking a $500 billion deal with potential purchasers like OpenAI, Softbank, and Arm. This move comes despite raising $700 million from investors Microsoft and Sequoia, which are valued at $2.8 billion as of late 2020. (Link)
OpenAI’s Sora can craft impressive video collages
One of OpenAI’s employees, Bill Peebles, demonstrated Sora’s (the new text-to-video generator from OpenAI) prowess in generating multiple videos simultaneously. He shared the demonstration via a post on X, showcasing five different angles of the same video and how Sora stitched those together to craft an impressive video collage while keeping quality intact. (Link)
US FTC proposes a prohibition law on AI impersonation
The US Federal Trade Commission (FTC) proposed a rule prohibiting AI impersonation of individuals. The rule was already in place for US governments and US businesses. Now, it has been extended to individuals to protect their privacy and reduce fraud activities through the medium of technology, as we have seen with the emergence of AI-generated deep fakes. (Link)
Meizu bid farewell to the smartphone market; shifts focus on AI
Meizu, a China-based consumer electronics brand, has decided to exit the smartphone manufacturing market after 17 years in the industry. The move comes after the company shifted its focus to AI with the ‘All-in-AI’ campaign. Meizu is working on an AI-based operating system, which will be released later this year, and a hardware terminal for all LLMs. (Link)
Groq has created the world’s fastest AI
- Groq, a startup, has developed special AI hardware called “Language Processing Unit” (LPU) to run language models, achieving speeds of up to 500 tokens per second, significantly outpacing current LLMs like Gemini Pro and GPT-3.5.
- The “GroqChip,” utilizing a tensor streaming architecture, offers improved performance, efficiency, and accuracy for real-time AI applications by ensuring constant latency and throughput.
- While LPUs provide a fast and energy-efficient alternative for AI inference tasks, training AI models still requires traditional GPUs, with Groq offering hardware sales and a cloud API for integration into AI projects.
Mistral’s next LLM could rival GPT-4, and you can try it now
- Mistral, a French AI startup, has launched its latest language model, “Mistral Next,” which is available for testing in chatbot arenas and might rival GPT-4 in capabilities.
- The new model is classified as “Large,” suggesting it is the startup’s most extensive model to date, aiming to compete with OpenAI’s GPT-4, and has received positive feedback from early testers on the “X” platform.
- Mistral AI has gained recognition in the open-source community for its Mixtral 8x7B language model, designed similarly to GPT-4, and recently secured €385 million in funding from notable venture capital firms.
- Source
Neuralink’s first human patient controls mouse with thoughts
- Neuralink’s first human patient, implanted with the company’s N1 brain chip, can now control a mouse cursor with their thoughts following a successful procedure.
- Elon Musk, CEO of Neuralink, announced the patient has fully recovered without any adverse effects and is working towards achieving the ability to click the mouse telepathically.
- Neuralink aims to enable individuals, particularly those with quadriplegia or ALS, to operate computers using their minds, using a chip that is both powerful and designed to be cosmetically invisible.
- Source
Adobe launches AI assistant that can search and summarize PDFs
- Adobe introduced an AI assistant in its Reader and Acrobat applications that can generate summaries, answer questions, and provide suggestions on PDFs and other documents, aiming to streamline information digestion.
- The AI assistant, presently in beta phase, is integrated directly into Acrobat with imminent availability in Reader, and Adobe intends to introduce a paid subscription model for the tool post-beta.
- Adobe’s AI assistant distinguishes itself by being a built-in feature that can produce overviews, assist with conversational queries, generate verifiable citations, and facilitate content creation for various formats without the need for uploading PDFs.
- Source
LockBit ransomware group taken down in multinational operation
- LockBit’s website was seized and its operations disrupted by a joint task force including the FBI and NCA under “Operation Cronos,” impacting the group’s ransomware activities and dark web presence.
- The operation led to the seizure of LockBit’s administration environment and leak site, with plans to use the platform to expose the operations and capabilities of LockBit through information bulletins.
- A PHP exploit deployed by the FBI played a significant role in undermining LockBit’s operations, according to statements from law enforcement and the group’s supposed ringleader, with the operation also resulting in charges against two Russian nationals.
A Daily Chronicle of AI Innovations in February 2024 – Day 19: AI Daily News – February 19th, 2024

NVIDIA’s new dataset sharpens LLMs in math

NVIDIA has released OpenMathInstruct-1, an open-source math instruction tuning dataset with 1.8M problem-solution pairs. OpenMathInstruct-1 is a high-quality, synthetically generated dataset 4x bigger than previous ones and does NOT use GPT-4. The dataset is constructed by synthesizing code-interpreter solutions for GSM8K and MATH, two popular math reasoning benchmarks, using the Mixtral model.
The best model, OpenMath-CodeLlama-70B, trained on a subset of OpenMathInstruct-1, achieves a score of 84.6% on GSM8K and 50.7% on MATH, which is competitive with the best gpt-distilled models.
Why does this matter?
The dataset improves open-source LLMs for math, bridging the gap with closed-source models. It also uses better-licensed models, such as from Mistral AI. It is likely to impact AI research significantly, fostering advancements in LLMs’ mathematical reasoning through open-source collaboration.
Apple is working on AI updates to Spotlight and Xcode
Apple has expanded internal testing of new generative AI features for its Xcode programming software and plans to release them to third-party developers this year.
Furthermore, it is looking at potential uses for generative AI in consumer-facing products, like automatic playlist creation in Apple Music, slideshows in Keynote, or Spotlight search. AI chatbot-like search features for Spotlight could let iOS and macOS users make natural language requests, like with ChatGPT, to get weather reports or operate features deep within apps.
Why does this matter?
Apple’s statements about generative AI have been conservative compared to its counterparts. But AI updates to Xcode hint at giving competition to Microsoft’s GitHub Copilot. Apple has also released MLX to train AI models on Apple silicon chips easily, a text-to-image editing AI MGIE, and AI animator Keyframer.
Google open-sources Magika, its AI-powered file-type identifier
Google has open-sourced Magika, its AI-powered file-type identification system, to help others accurately detect binary and textual file types. Magika employs a custom, highly optimized deep-learning model, enabling precise file identification within milliseconds, even when running on a CPU.
Magika, thanks to its AI model and large training dataset, is able to outperform other existing tools by about 20%. It has greater performance gains on textual files, including code files and configuration files that other tools can struggle with.
Internally, Magika is used at scale to help improve Google users’ safety by routing Gmail, Drive, and Safe Browsing files to the proper security and content policy scanners.
Why does this matter?
Today, web browsers, code editors, and countless other software rely on file-type detection to decide how to properly render a file. Accurate identification is notoriously difficult because each file format has a different structure or no structure at all. Magika ditches current tedious and error-prone methods for robust and faster AI. It improves security with resilience to ever-evolving threats, enhancing software’s user safety and functionality.
SoftBank to build a $100B AI chip venture
- SoftBank’s Masayoshi Son is seeking $100 billion to create a new AI chip venture, aiming to compete with industry leader Nvidia.
- The new venture, named Izanagi, will collaborate with Arm, a company SoftBank spun out but still owns about 90% of, to enter the AI chip market.
- SoftBank plans to raise $70 billion of the venture’s funding from Middle Eastern institutional investors, contributing the remaining $30 billion itself.
Reddit has a new AI training deal to sell user content
- Reddit has entered into a $60 million annual contract with a large AI company to allow the use of its social media platform’s content for AI training as it prepares for a potential IPO.
- The deal could set a precedent for similar future agreements and is part of Reddit’s efforts to leverage AI technology to attract investors for its advised $5 billion IPO valuation.
- Reddit’s revenue increased to more than $800 million last year, showing a 20% growth from 2022, as the company moves closer to launching its IPO, possibly as early as next month.
Air Canada chatbot promised a discount. Now the airline has to pay it.
- A British Columbia resident was misled by an Air Canada chatbot into believing he would receive a discount under the airline’s bereavement policy for a last-minute flight booked due to a family tragedy.
- Air Canada argued that the chatbot was a separate legal entity and not responsible for providing incorrect information about its bereavement policy, which led to a dispute over accountability.
- The Canadian civil-resolutions tribunal ruled in favor of the customer, emphasizing that Air Canada is responsible for all information provided on its website, including that from a chatbot.
Apple faces €500m fine from EU over Spotify complaint
- Apple is facing a reported $539 million fine as a result of an EU investigation into Spotify’s antitrust complaint, which alleges Apple’s policies restrict competition by preventing apps from offering cheaper alternatives to its music service.
- The fine originates from Spotify’s 2019 complaint about Apple’s App Store policies, specifically the restriction on developers linking to their own subscription services, a policy Apple modified in 2022 following regulatory feedback from Japan.
- While the fine amounts to $539 million, discussions initially suggested Apple could face penalties nearing $40 billion, highlighting a significant reduction from the potential maximum based on Apple’s global annual turnover.
What Else Is Happening in AI on February 19th, 2024
SoftBank’s founder is seeking about $100 billion for an AI chip venture.
SoftBank’s founder, Masayoshi Son, envisions creating a company that can complement the chip design unit Arm Holdings Plc. The AI chip venture is code-named Izanag and will allow him to build an AI chip powerhouse, competing with Nvidia and supplying semiconductors essential for AI. (Link)
ElevenLabs teases a new AI sound effects feature.
The popular AI voice startup teased a new feature allowing users to generate sounds via text prompts. It showcased the outputs of this feature with OpenAI’s Sora demos on X. (Link)
NBA commissioner Adam Silver demonstrates NB-AI concept.
Adam Silver demoed a potential future for how NBA fans will use AI to watch basketball action. The proposed interface is named NB-AI and was unveiled at the league’s Tech Summit on Friday. Check out the demo here! (Link)
Reddit signs AI content licensing deal ahead of IPO.
Reddit Inc. has signed a contract allowing a company to train its AI models on its content. Reddit told prospective investors in its IPO that it had signed the deal, worth about $60 million on an annualized basis, earlier this year. This deal with an unnamed large AI company could be a model for future contracts of similar nature. (Link)
Mistral quietly released a new model in testing called ‘next’.
Early users testing the model are reporting capabilities that meet or surpass GPT-4. A user writes, ‘it bests gpt-4 at reasoning and has mistral’s characteristic conciseness’. It could be a milestone in open source if early tests hold up. (Link)
A Daily Chronicle of AI Innovations in February 2024 – Day 14: AI Daily News – February 14th, 2024
Nvidia launches offline AI chatbot trainable on local data

NVIDIA has released Chat with RTX, a new tool allowing users to create customized AI chatbots powered by their own local data on Windows PCs equipped with GeForce RTX GPUs. Users can rapidly build chatbots that provide quick, relevant answers to queries by connecting the software to files, videos, and other personal content stored locally on their devices.
Features of Chat with RTX include support for multiple data formats (text, PDFs, video, etc.), access to LLM like Mistral, running offline for privacy, and fast performance via RTX GPUs. From personalized recommendations based on influencing videos to extracting answers from personal notes or archives, there are many potential applications.
Why does this matter?
OpenAI and its cloud-based approach now face fresh competition from this Nvidia offering as it lets solopreneurs develop more tailored workflows. It shows how AI can become more personalized, controllable, and accessible right on local devices. Instead of relying solely on generic cloud services, businesses can now customize chatbots with confidential data for targeted assistance.
ChatGPT can now remember conversations
OpenAI is testing a memory capability for ChatGPT to recall details from past conversations to provide more helpful and personalized responses. Users can explicitly tell ChatGPT what memories to remember or delete conversationally or via settings. Over time, ChatGPT will provide increasingly relevant suggestions based on users preferences, so they don’t have to repeat them.
This feature is rolled out to only a few Free and Plus users and OpenAI will share broader plans soon. OpenAI also states memories bring added privacy considerations, so sensitive data won’t be proactively retained without permission.
Why does this matter?
ChatGPT’s memory feature allows for more personalized, contextually-aware interactions. Its ability to recall specifics from entire conversations brings AI assistants one step closer to feeling like cooperative partners, not just neutral tools. For companies, remembering user preferences increases efficiency, while individuals may find improved relationships with AI companions.
Cohere launches open-source LLM in 101 languages
Cohere has launched Aya, a new open-source LLM supporting 101 languages, over twice as many as existing models support. Backed by the large dataset covering lesser resourced languages, Aya aims to unlock AI potential for overlooked cultures. Benchmarking shows Aya significantly outperforms other open-source massively multilingual models.
The release tackles the data scarcity outside of English training content that limits AI progress. By providing rare non-English fine-tuning demonstrations, it enables customization in 50+ previously unsupported languages. Experts emphasize that Aya represents a crucial step toward preserving linguistic diversity.
Why does this matter?
With over 100 languages supported, more communities globally can benefit from generative models tailored to their cultural contexts. It also signifies an ethical shift: recognizing AI’s real-world impact requires serving people inclusively. Models like Aya, trained on diverse data, inch us toward AI that can help everyone.
Zuckerberg says Quest 3 is better than Vision Pro in every way
- Mark Zuckerberg, CEO of Meta, stated on Instagram that he believes the Quest 3 headset is not only a better value but also a superior product compared to Apple’s Vision Pro.
- Zuckerberg emphasized the Quest 3’s advantages over the Vision Pro, including its lighter weight, lack of a wired battery pack for greater motion, a wider field of view, and a more immersive content library.
- While acknowledging the Vision Pro’s strength as an entertainment device, Zuckerberg highlighted the Quest 3’s significant cost benefit, being “like seven times less expensive” than the Vision Pro.
Slack is getting a major Gen AI boost
- Slack is introducing AI features allowing for summaries of threads, channel recaps, and the answering of work-related questions, initially available as a paid add-on for Slack Enterprise users.
- The AI tool enables summarization of unread messages or messages from a specified timeframe and allows users to ask questions about workplace projects or policies based on previous Slack messages.
- Slack is expanding its AI capabilities to integrate with other applications, summarizing external documents and building a new digest feature to highlight important messages, with a focus on keeping customer data private and siloed.
Microsoft and OpenAI claim hackers are using generative AI to improve cyberattacks
- Russia, China, and other nations are leveraging the latest artificial intelligence tools to enhance hacking capabilities and identify new espionage targets, based on a report from Microsoft and OpenAI.
- The report highlights the association of AI use with specific hacking groups from China, Russia, Iran, and North Korea, marking a first in identifying such ties to government-sponsored cyber activities.
- Microsoft has taken steps to block these groups’ access to AI tools like OpenAI’s ChatGPT, aiming to curb their ability to conduct espionage and cyberattacks, despite challenges in completely stopping such activities.
Apple researchers unveil ‘Keyframer’, a new AI tool
- Apple researchers have introduced “Keyframer,” an AI tool using large language models (LLMs) to animate still images with natural language prompts.
- “Keyframer” can generate CSS animation code from text prompts and allows users to refine animations by editing the code or adding prompts, enhancing the creative process.
- The tool aims to democratize animation, making it accessible to non-experts and indicating a shift towards AI-assisted creative processes in various industries.
Sam Altman at WGS on GPT-5: “The thing that will really matter: It’s gonna be smarter.” The Holy Grail.
we’re moving from memory to reason. logic and reasoning are the foundation of both human and artificial intelligence. it’s about figuring things out. our ai engineers and entrepreneurs finally get this! stronger logic and reasoning algorithms will easily solve alignment and hallucinations for us. but that’s just the beginning.
logic and reasoning tell us that we human beings value three things above all; happiness, health and goodness. this is what our life is most about. this is what we most want for the people we love and care about.
so, yes, ais will be making amazing discoveries in science and medicine over these next few years because of their much stronger logic and reasoning algorithms. much smarter ais endowed with much stronger logic and reasoning algorithms will make us humans much more productive, generating trillions of dollars in new wealth over the next 6 years. we will end poverty, end factory farming, stop aborting as many lives each year as die of all other cause combined, and reverse climate change.
but our greatest achievement, and we can do this in a few years rather than in a few decades, is to make everyone on the planet much happier and much healthier, and a much better person. superlogical ais will teach us how to evolve into what will essentially be a new human species. it will develop safe pharmaceuticals that make us much happier, and much kinder. it will create medicines that not only cure, but also prevent, diseases like cancer. it will allow us all to live much longer, healthier lives. ais will create a paradise for everyone on the planet. and it won’t take longer than 10 years for all of this to happen.
what it may not do, simply because it probably won’t be necessary, is make us all much smarter. it will be doing all of our deepest thinking for us, freeing us to enjoy our lives like never before. we humans are hardwired to seek pleasure and avoid pain. most fundamentally that is who we are. we’re almost there.
https://www.youtube.com/live/RikVztHFUQ8?si=GwKFWipXfTytrhD4
OpenAI and Microsoft Disrupt Malicious AI Use by State-Affiliated Threat Actors

OpenAI and Microsoft have teamed up to identify and disrupt operations of five state-affiliated malicious groups using AI for cyber threats, aiming to secure digital ecosystems and promote AI safety.
OpenAI is jumping into one of the hottest areas of artificial intelligence: autonomous agents.
Microsoft-backed OpenAI is working on a type of agent software to automate complex tasks by taking over a users’ device, The Information reported on Wednesday, citing a person with knowledge on the matter. The agent software will handle web-based tasks such as gathering public data about a set of companies, creating itineraries or booking flight tickets, according to the report. The new assistants – often called “agents” – promise to perform more complex personal and work tasks when commanded to by a human, without needing close supervision.
What Else Is Happening in AI on February 14th, 2024
Nous Research released 1M-Entry 70B Llama-2 model with advanced steerability
Nous Research has released its largest model yet – Nous Hermes 2 Llama-2 70B – trained on over 1 million entries of primarily synthetic GPT-4 generated data. The model uses a more structured ChatML prompt format compatible with OpenAI, enabling advanced multi-turn chat dialogues. (Link)
Otter launches AI meeting buddy that can catch up on meetings
Otter has introduced a new feature for its AI chatbot to query past transcripts, in-channel team conversations, and auto-generated overviews. This AI suite aims to outperform and replace competitors’ paid offerings like Microsoft, Zoom and Google by simplifying recall and productivity for users leveraging Otter’s complete meeting data. (Link)
OpenAI CEO forecasts smarter multitasking GPT-5
At the World Government Summit, OpenAI CEO Sam Altman remarked that the upcoming GPT-5 model will be smarter, faster, more multimodal, and better at everything across the board due to its generality. There are rumors that GPT-5 could be a multimodal AI called “Gobi” slated for release in spring 2024 after training on a massive dataset. (Link)
ElevenLabs announced expansion for its speech to speech in 29 languages
ElevenLabs’s Speech to Speech is now available in 29 languages, making it multilingual. The tool, launched in November, lets users transform their voice into another character with full control over emotions, timing, and delivery by prompting alone. This update just made it more inclusive! (Link)
Airbnb plans to build ‘most innovative AI interfaces ever
Airbnb plans to leverage AI, including its recent acquisition of stealth startup GamePlanner, to evolve its interface into an adaptive “ultimate concierge”. Airbnb executives believe the generative models themselves are underutilized and want to focus on improving the AI application layer to deliver more personalized, cross-category services. (Link)
A Daily Chronicle of AI Innovations in February 2024 – Day 13: AI Daily News – February 13th, 2024
How LLMs are built?
ChatGPT adds ability to remember things you discussed. Rolling out now to a small portion of users
NVIDIA CEO says computers will pass any test a human can within 6 years
NVIDIA CEO Jensen Huang says computers will pass any test a human can by the end of this decade pic.twitter.com/nThVio1wwq
— Tsarathustra (@tsarnick) February 3, 2024
More Agents = More Performance: Tencent Research
The Tencent Research Team has released a paper claiming that the performance of language models can be significantly improved by simply increasing the number of agents. The researchers use a “sampling-and-voting” method in which the input task is fed multiple times into a language model with multiple language model agents to produce results. After that, majority voting is applied to these answers to determine the final answer.
The researchers prove this methodology by experimenting with different datasets and tasks, showing that the performance of language models increases with the size of the ensemble, i.e., with the number of agents (results below). They also established that even smaller LLMs can match/outperform their larger counterparts by scaling the number of agents. (Example below)
Why does it matter?
Using multiple agents to boost LLM performance is a fresh tactic to tackle single models’ inherent limitations and biases. This method eliminates the need for complicated methods such as chain-of-thought prompting. While it is not a silver bullet, it can be combined with existing complicated methods that stimulate the potential of LLMs and enhance them to achieve further performance improvements.
Google DeepMind’s MC-ViT understands long-context video
Researchers from Google DeepMind and the University of Cornell have combined to develop a method allowing AI-based systems to understand longer videos better. Currently, most AI-based models can comprehend videos for up to a short duration due to the complexity and computing power.
That’s where MC-ViT aims to make a difference, as it can store a compressed “memory” of past video segments, allowing the model to reference past events efficiently. Human memory consolidation theories inspire this method by combining neuroscience and psychology. The MC-ViT method provides state-of-the-art action recognition and question answering despite using fewer resources.
Why does it matter?
Most video encoders based on transformers struggle with processing long sequences due to their complex nature. Efforts to address this often add complexity and slow things down. MC-ViT offers a simpler way to handle longer videos without major architectural changes.
ElevenLabs lets you turn your voice into passive income
ElevenLabs has developed an AI voice cloning model that allows you to turn your voice into passive income. Users must sign up for their “Voice Actor Payouts” program.
After creating the account, upload a 30-minute audio of your voice. The cloning model will create your professional voice clone with AI that resembles your original voice. You can then share it in Voice Library to make it available to the growing community of ElevenLabs.
After that, whenever someone uses your professional voice clone, you will get a cash or character reward according to your requirements. You can also decide on a rate for your voice usage by opting for a standard royalty program or setting a custom rate.
Why does it matter?
By leveraging ElevenLabs’ AI voice cloning, users can potentially monetize their voices in various ways, such as providing narration for audiobooks, voicing virtual assistants, or even lending their voices to advertising campaigns. This innovation democratizes the field of voice acting, making it accessible to a broader audience beyond professional actors and voiceover artists. Additionally, it reflects the growing influence of AI in reshaping traditional industries.
What Else Is Happening in AI on February 13th, 2024
NVIDIA CEO Jensen Huang advocates for each country’s sovereign AI
While speaking at the World Governments Summit in Dubai, the NVIDIA CEO strongly advocated the need for sovereign AI. He said, “Every country needs to own the production of their own intelligence.” He further added, “It codifies your culture, your society’s intelligence, your common sense, your history – you own your own data.” (Link)
Google to invest €25 million in Europe to uplift AI skills
Google has pledged 25 million euros to help the people of Europe learn how to use AI. With this funding, Google wants to develop various social enterprise and nonprofit applications. The tech giant is also looking to run “growth academies” to support companies using AI to scale their companies and has expanded its free online AI training courses to 18 languages. (Link)
NVIDIA surpasses Amazon in market value
NVIDIA Corp. briefly surpassed Amazon.com Inc. in market value on Monday. Nvidia rose almost 0.2%, closing with a market value of about $1.78 trillion. While Amazon fell 1.2%, it ended with a closing valuation of $1.79 trillion. With this market value, NVIDIA Corp. temporarily became the 4th most valuable US-listed company behind Alphabet, Microsoft, and Apple. (Link)
Microsoft might develop an AI upscaling feature for Windows 11
Microsoft may release an AI upscaling feature for PC gaming on Windows 11, similar to Nvidia’s Deep Learning Super Sampling (DLSS) technology. The “Automatic Super Resolution” feature, which an X user spotted in the latest test version of Windows 11, uses AI to improve supported games’ frame rates and image detail. Microsoft is yet to announce the news or hardware specifics, if any. (Link)
Fandom rolls out controversial generative AI features
Fandom hosts wikis for many fandoms and has rolled out many generative AI features. However, some features like “Quick Answers” have sparked a controversy. Quick Answers generates a Q&A-style dropdown that distills information into a bite-sized sentence. Wiki creators have complained that it answers fan questions inaccurately, thereby hampering user trust. (Link)
Sam Altman warns that ‘societal misalignments’ could make AI dangerous
- OpenAI CEO Sam Altman expressed concerns at the World Governments Summit about the potential for ‘societal misalignments’ caused by artificial intelligence, emphasizing the need for international oversight similar to the International Atomic Energy Agency.
- Altman highlighted the importance of not focusing solely on the dramatic scenarios like killer robots but on the subtle ways AI could unintentionally cause societal harm, advocating for regulatory measures not led by the AI industry itself.
- Despite the challenges, Altman remains optimistic about the future of AI, comparing its current state to the early days of mobile technology, and anticipates significant advancements and improvements in the coming years.
- Source
SpaceX plans to deorbit 100 Starlink satellites due to potential flaw
- SpaceX plans to deorbit 100 first-generation Starlink satellites due to a potential flaw to prevent them from failing, with the process designed to ensure they burn up safely in the Earth’s atmosphere without posing a risk.
- The deorbiting operation will not impact Starlink customers, as the network still has over 5,400 operational satellites, demonstrating SpaceX’s dedication to space sustainability and minimizing orbital hazards.
- SpaceX has implemented an ‘autonomous collision avoidance’ system and ion thrusters in its satellites for maneuverability, and has a policy of deorbiting satellites within five years or less to avoid becoming a space risk, with 406 satellites already deorbited.
Nvidia unveils tool for running GenAI on PCs
- Nvidia is releasing a tool named “Chat with RTX” that enables owners of GeForce RTX 30 Series and 40 Series graphics cards to run an AI-powered chatbot offline on Windows PCs.
- “Chat with RTX” allows customization of GenAI models with personal documents for querying, supporting multiple text formats and even YouTube playlist transcriptions.
- Despite its limitations, such as inability to remember context and variable response relevance, “Chat with RTX” represents a growing trend of running GenAI models locally for increased privacy and lower latency.
- https://youtu.be/H8vJ_wZPH3A?si=DTWYvcZNDvfds8Rv
iMessage and Bing escape EU rules
- Apple’s iMessage has been declared by the European Commission not to be a “core platform service” under the EU’s Digital Markets Act (DMA), exempting it from rigorous new rules such as interoperability requirements.
- The decision came after a five-month investigation, and while services like WhatsApp and Messenger have been designated as core platform services requiring interoperability, iMessage, Bing, Edge, and Microsoft Advertising have not.
- Despite avoiding the DMA’s interoperability obligations, Apple announced it would support the cross-platform RCS messaging standard on iPhones, which will function alongside iMessage without replacing it.
Google says it got rid of over 170 million fake reviews in Search and Maps in 2023
- Google announced that it eliminated more than 170 million fake reviews in Google Search and Maps in 2023, a figure that surpasses by over 45 percent the number removed in the previous year.
- The company introduced new algorithms to detect fake reviews, including identifying duplicate content across multiple businesses and sudden spikes of 5-star ratings, leading to the removal of five million fake reviews related to a scamming network.
- Additionally, Google removed 14 million policy-violating videos and blocked over 2 million scam attempts to claim legitimate business profiles in 2023, doubling the figures from 2022.
“More agents = more performance”- The Tencent Research Team:
The Tencent Research team suggests boosting language model performance by adding more agents. They use a “sampling-and-voting” method, where the input task is run multiple times through a language model with several agents to generate various results. These results are then subjected to majority voting to determine the most reliable result.Google DeepMind’s MC-ViT enables long-context video understanding:
Most transformer-based video encoders are limited to short contexts due to quadratic complexity. To overcome this issue, Google DeepMind introduces memory consolidated vision transformer (MC-ViT) that effortlessly extends its context far into the past and exhibits excellent scaling behavior when learning from longer videos.ElevenLabs’ AI voice cloning lets you turn your voice into passive income:
ElevenLabs has developed an AI-based voice cloning model to turn your voice into passive income. The voice cloning program allows all voice-over artists to create professional clones, share them with the Voice Library community, and earn rewards/royalty every time soundbite is used.NVIDIA CEO Jensen Huang advocates for each country’s sovereign AI:
While speaking at the World Governments Summit in Dubai, the NVIDIA CEO strongly advocated the need for sovereign AI. He said, “Every country needs to own the production of their own intelligence.” He further added, “It codifies your culture, your society’s intelligence, your common sense, your history – you own your own data.”Google to invest €25 million in Europe to uplift AI skills:
Google has pledged 25 million euros to help the people of Europe learn AI. Google is also looking to run “growth academies” to support companies using AI to scale their companies and has expanded its free online AI training courses to 18 languages.NVIDIA surpasses Amazon in market value:
NVIDIA Corp. briefly surpassed Amazon.com Inc. on Monday. Nvidia rose almost 0.2%, closing with a market value of about $1.78 trillion. While Amazon fell 1.2%, it ended with a closing valuation of $1.79 trillion. It made NVIDIA Corp. 4th largest US-listed company.Microsoft might develop an AI upscaling feature for Windows 11:
Microsoft may release an AI upscaling feature for PC gaming on Windows 11, similar to Nvidia’s DLSS technology. The “Automatic Super Resolution” feature uses AI to improve supported games’ frame rates and image detail.Fandom rolls out controversial generative AI features:
Fandom’s Quick Answers feature, part of its generative AI tools, has sparked controversy among wiki creators. It generates short Q&A-style responses, but many creators complain about inaccuracies, undermining user trust.
A Daily Chronicle of AI Innovations in February 2024 – Day 12: AI Daily News – February 12th, 2024
DeepSeekMath: The key to mathematical LLMs
In its latest research paper, DeepSeek AI has introduced a new AI model, DeepSeekMath 7B, specialized for improving mathematical reasoning in open-source LLMs. It has been pre-trained on a massive corpus of 120 billion tokens extracted from math-related web content, combined with reinforcement learning techniques tailored for math problems.
When evaluated across crucial English and Chinese benchmarks, DeepSeekMath 7B outperformed all the leading open-source mathematical reasoning models, even coming close to the performance of proprietary models like GPT-4 and Gemini Ultra.
Why does this matter?
Previously, state-of-the-art mathematical reasoning was locked within proprietary models that aren’t inaccessible to everyone. With DeepSeekMath 7B’s decision to go open-source (while also sharing the training methodology), new doors have opened for math AI development across fields like education, finance, scientific computing, and more. Teams can build on DeepSeekMath’s high-performance foundation instead of starting models from scratch.
localllm enables GenAI app development without GPUs
Google has introduced a new open-source tool called localllm that allows developers to run LLMs locally on CPUs within Cloud Workstations instead of relying on scarce GPU resources. localllm provides easy access to “quantized” LLMs from HuggingFace that have been optimized to run efficiently on devices with limited compute capacity.
By allowing LLMs to run on CPU and memory, localllm significantly enhances productivity and cost efficiency. Developers can now integrate powerful LLMs into their workflows without managing scarce GPU resources or relying on external services.
Why does this matter?
localllm democratizes access to the power of large language models by freeing developers from GPU constraints. Now, even solo innovators and small teams can experiment and create production-ready GenAI applications without huge investments in infrastructure costs.
IBM researchers show how GenAI can tamper calls
In a concerning development, IBM researchers have shown how multiple GenAI services can be used to tamper and manipulate live phone calls. They demonstrated this by developing a proof-of-concept, a tool that acts as a man-in-the-middle to intercept a call between two speakers. They then experimented with the tool by audio jacking a live phone conversation.
The call audio was processed through a speech recognition engine to generate a text transcript. This transcript was then reviewed by a large language model that was pre-trained to modify any mentions of bank account numbers. Specifically, when the model detected a speaker state their bank account number, it would replace the actual number with a fake one.
Remarkably, whenever the AI model swapped in these phony account numbers, it even injected its own natural buffering phrases like “let me confirm that information” to account for the extra seconds needed to generate the devious fakes.
The altered text, now with fake account details, was fed into a text-to-speech engine that cloned the speakers’ voices. The manipulated voice was successfully inserted back into the audio call, and the two people had no idea their conversation had been changed!
Why does this matter?
This proof-of-concept highlights alarming implications – victims could become unwilling puppets as AI makes realistic conversation tampering dangerously easy. While promising, generative AI’s proliferation creates an urgent need to identify and mitigate emerging risks. Even if still theoretical, such threats warrant increased scrutiny around model transparency and integrity verification measures before irreparable societal harm occurs.
What Else Is Happening in AI on February 12th, 2024
Perplexity partners with Vercel to bring AI search to apps
By partnering with Vercel, Perplexity AI is making its large language models available to developers building apps on Vercel. Developers get access to Perplexity’s LLMs pplx-7b-online and pplx-70b-online that use up-to-date internet knowledge to power features like recommendations and chatbots. (Link)
Volkswagen sets up “AI Lab” to speed up its AI development initiatives
The lab will build AI prototypes for voice recognition, connected digital services, improved electric vehicle charging cycles, predictive maintenance, and other applications. The goal is to collaborate with tech firms and rapidly implement ideas across Volkswagen brands. (Link)
Tech giants use AI to monitor employee messages
AI startup Aware has attracted clients like Walmart, Starbucks, and Delta to use its technology to monitor workplace communications. But experts argue this AI surveillance could enable “thought crime” violations and treat staff “like inventory.” There are also issues around privacy, transparency, and recourse for employees. (Link)
Disney harnesses AI to bring contextual ads to streaming
Their new ad tool called “Magic Words” uses AI to analyze the mood and content of scenes in movies and shows. It then allows brands to target custom ads based on those descriptive tags. Six major ad agencies are beta-testing the product as Disney pushes further into streaming ads amid declining traditional TV revenue. (Link)
Microsoft hints at a more helpful Copilot in Windows 11
New Copilot experiences let the assistant offer relevant actions and understand the context better. Notepad is also getting Copilot integration for text explanations. The features hint at a forthcoming Windows 11 update centered on AI advancements. (Link)
Crowd destroys a driverless Waymo car
- A Waymo driverless taxi was attacked in San Francisco’s Chinatown, resulting in its windshield being smashed, being covered in spray paint, its windows broken, and ultimately being set on fire.
- No motive for the attack has been reported, and the Waymo car was not transporting any riders at the time of the incident; police confirmed there were no injuries.
- The incident occurs amidst tensions between San Francisco residents and automated vehicle operators, following previous issues with robotaxis causing disruption and accidents in the city.
- Source
Apple has been buying AI startups faster than Google, Facebook, likely to shakeup global AI soon
- Apple has reportedly outpaced major rivals like Google, Meta, and Microsoft in AI startup acquisitions in 2023, with up to 32 companies acquired, highlighting its dedication to AI development.
- The company’s strategic acquisitions provide access to cutting-edge technology and top-talent, aiming to strengthen its competitive edge and AI capabilities in its product lineup.
- While specifics of Apple’s integration plans for these AI technologies remain undisclosed, its aggressive acquisition strategy signals a significant focus on leading the global AI innovation forefront.
- Source
The antitrust fight against Big Tech is just beginning
- DOJ’s Jonathan Kanter emphasizes the commencement of a significant antitrust battle against Big Tech, highlighting unprecedented public resonance with these issues.
- The US government has recently blocked a notable number of mergers to protect competition, including stopping Penguin Random House from acquiring Simon & Schuster.
- Kanter highlights the problem of monopsony in tech markets, where powerful buyers distort the market, and stresses the importance of antitrust enforcement for a competitive economy.
- Source
Nvidia CEO plays down fears in call for rapid AI infrastructure growth
- Nvidia CEO Jensen Huang downplays fears of AI, attributing them to overhyped concerns and interests aimed at scaring people, while advocating for rapid development of AI infrastructure for economic benefits.
- Huang argues that regulating AI should not be more difficult than past innovations like cars and planes, emphasizing the importance of countries building their own AI infrastructure to protect culture and gain economic advantages.
- Despite Nvidia’s success with AI chips and the ongoing global debate on AI regulation, Huang encourages nations to proactively develop their AI capabilities, dismissing the scare tactics as a barrier to embracing the technology’s potential.
- Source
10 AI tools that can be used to improve research
#1 Gemini:
Gemini is an AI chatbot from Google AI that can be used for a variety of research tasks, including finding information, summarizing texts, and generating creative text formats. It can be used for both primary and secondary research and it is great for creating content.
Accuracy: Gemini is trained on a massive dataset of text and code, which means that it can generate text that is accurate and reliable also it uses Google to look up answers.
Relevance: Gemini can be used to find information that is relevant to a specific research topic.
Creativity: Gemini can be used to generate creative text formats such as code, scripts, musical pieces, email, letters, etc.
Engagement: Gemini can be used to present information creatively and engagingly.
Accessibility: Gemini is available for free and can be used from anywhere in the world.
Scite.AI
Scite AI is an innovative platform that helps discover and evaluate scientific articles. Its Smart Citations feature provides context and classification of citations in scientific literature, indicating whether they support or contrast the cited claims.
Smart Citations: Offers detailed insights into how other papers have cited a publication, including the context and whether the citation supports or contradicts the claims made.
Deep Learning Model: Automatically classifies each citation’s context, indicating the confidence level of the classification.
Citation Statement Search: Enables searching across metadata relevant publications.
Custom Dashboards: Allows users to build and manage collections of articles, providing aggregate insights and notifications.
Reference Check: Helps to evaluate the quality of references used in manuscripts.
Journal Metrics: Offers insights into publications, top authors, and scite Index rankings.
Assistant by scite: An AI tool that utilizes Smart Citations for generating content and building reference lists.
4. GPT4All
GPT4All is an open-source ecosystem for training and deploying large language models that can be run locally on consumer-grade hardware. GPT4All is designed to be powerful, customizable and great for conducting research. Overall, it is an offline and secure AI-powered search engine.
Answer questions about anything: You can use any ChatGPT version for your personal use to answer even simple questions.
Personal writing assistant: Write emails, documents, stories, songs, play based on your previous work.
Reading documents: Submit your text documents and receive summaries and answers. You can easily find answers in the documents you provide by submitting a folder of documents for GPT4All to extract information from.
5. AsReview
AsReview is a software package designed to make systematic reviews more efficient using active learning techniques. It helps to review large amounts of text quickly and addresses the challenge of time constraints when reading large amounts of literature.
Free and Open Source: The software is available for free and its source code is openly accessible.
Local or Server Installation: It can be installed either locally on a device or on a server, providing full control over data.
Active Learning Algorithms: Users can select from various active learning algorithms for their projects.
Project Management: Enables creation of multiple projects, selection of datasets, and incorporation of prior knowledge.
Research Infrastructure: Provides an open-source infrastructure for large-scale simulation studies and algorithm validation.
Extensible: Users can contribute to its development through GitHub.
6. DeepL
DeepL translates texts & full document files instantly. Millions translate with DeepL everyday. It is commonly used for translating web pages, documents, and emails. It can also translate speech.
DeepL also has a great feature called DeepL Write. DeepL Write is a powerful tool that can help you to improve your writing in a variety of ways. It is a valuable resource for anyone who wants to write clear, concise, and effective prose.
Tailored Translations: Adjust translations to fit specific needs and context, with alternatives for words or phrases.
Whole Document Translation: One-click translation of entire documents including PDF, Word, and PowerPoint files while maintaining original formatting.
Tone Adjustment: Option to select between formal and informal tone of voice for translations in selected languages.
Built-in Dictionary: Instant access to dictionary for insight into specific words in translations, including context, examples, and synonyms.
7. Humata
Humata is an AI tool designed to assist with processing and understanding PDF documents. It offers features like summarizing, comparing documents, and answering questions based on the content of the uploaded files.
Designed to process and summarize long documents, allowing users to ask questions and get summarized answers from any PDF file.
Claims to be faster and more efficient than manual reading, capable of answering repeated questions and customizing summaries.
Humata differs from ChatGPT by its ability to read and interpret files, generating answers with citations from the documents.
Offers a free version for trial
8. Cockatoo
Cockatoo AI is an AI-powered transcription service that automatically generates text from recorded speech. It is a convenient and easy-to-use tool that can be used to transcribe a variety of audio and video files. It is one of the AI-powered tools that not everyone will find a use for but it is a great tool nonetheless.
Highly accurate transcription: Cockatoo AI uses cutting-edge AI to transcribe audio and video files with a high degree of accuracy. It is said to be able to transcribe speech with superhuman accuracy, surpassing human performance.
Support for multiple languages: Cockatoo AI supports transcription in more than 90 languages, making it a versatile tool for global users.
Versatile file formats: Cockatoo AI can transcribe a variety of audio and video file formats, including MP3, WAV, MP4, and MOV.
Quick turnaround: Cockatoo AI can transcribe audio and video files quickly, with one hour of audio typically being transcribed in just 2-3 minutes.
Seamless export options: Cockatoo AI allows users to export their transcripts in a variety of formats, including SRT, DOCX, any PDF document, and TXT.
9. Avidnote
Avidnote is an AI-powered research writing platform that helps researchers write and organize their research notes easily. It combines all of the different parts of the academic writing process, from finding articles to managing references and annotating research notes.
AI research paper summary: Avidnote can automatically summarize research papers in a few clicks. This can save researchers a lot of time and effort, as they no longer need to read the entire paper to get the main points.
Integrated note-taking: Avidnote allows researchers to take notes directly on the research papers they are reading. This makes it easy to keep track of their thoughts and ideas as they are reading.
Collaborative research: Avidnote can be used by multiple researchers to collaborate on the same project. This can help share ideas, feedback, and research notes.
AI citation generation: Avidnote can automatically generate citations for research papers in APA, MLA, and Chicago styles. This can save researchers a lot of time and effort, as they no longer need to manually format citations.
AI writing assistant: Avidnote can provide suggestions for improving the writing style of research papers. This can help researchers to write more clear, concise, and persuasive papers.
AI plagiarism detection: Avidnote can detect plagiarism in research papers. This can help researchers to avoid plagiarism and maintain the integrity of their work.
10. Research Rabbit
Research Rabbit is an online tool that helps you find references quickly and easily. It is a citation-based literature mapping tool that can be used to plan your essay, minor project, or literature review.
AI for Researchers: Enhances research writing, reading, and data analysis using AI.
Effective Reading: Capabilities include summarizing, proofreading text, and identifying research gaps.
Data Analysis: Offers tools to input data and discover correlations and insights, relevant articles.
Research Methods Support: Includes transcribing interviews and other research methods.
AI Functionalities: Enables users to upload papers, ask questions, summarize text, get explanations, and proofread using AI.
Note Saving: Provides an integrated platform to save notes alongside papers.
A Daily Chronicle of AI Innovations in February 2024 – Day 11: AI Daily News – February 11th, 2024
This week, we’ll cover Google DeepMind creating a grandmaster-level chess AI, the satirical AI Goody-2 raising questions about ethics and AI boundaries, Google rebranding Bard to Gemini and launching the Gemini Advanced chatbot and mobile apps, OpenAI developing AI agents to automate work, and various companies introducing new AI-related products and features.
Google DeepMind has just made an incredible breakthrough in the world of chess. They’ve developed a brand new artificial intelligence (AI) that can play chess at a grandmaster level. And get this—it’s not like any other chess AI we’ve seen before!
Read Aloud For Me: Access All Your AI Tools within 1 single App
Instead of using traditional search algorithm approaches, Google DeepMind’s chess AI is based on a language model architecture. This innovative approach diverges from the norm and opens up new possibilities in the realm of AI.
To train this AI, DeepMind fed it a massive dataset of 10 million chess games and a mind-boggling 15 billion data points. And the results are mind-blowing. The AI achieved an Elo rating of 2895 in rapid chess when pitted against human opponents. That’s seriously impressive!
In fact, this AI even outperformed AlphaZero, another notable chess AI, when it didn’t use the MCTS strategy. That’s truly remarkable.
But here’s the real kicker: this breakthrough isn’t just about chess. It highlights the incredible potential of the Transformer architecture, which was primarily known for its use in language models. It challenges the idea that transformers can only be used as statistical pattern recognizers. So, we might just be scratching the surface of what these transformers can do!
Overall, this groundbreaking achievement by Google DeepMind opens up exciting opportunities for the future of AI, not just in chess but in various domains as well.
So, have you heard about this AI called Goody-2? It’s actually quite a fascinating creation by the art studio Brain. But here’s the thing – Goody-2 takes the concept of ethical AI to a whole new level. I mean, it absolutely refuses to engage in any conversation, no matter the topic. Talk about being too ethical for its own good!
The idea behind Goody-2 is to highlight the extremes of ethical AI development. It’s a satirical take on the overly cautious approach some AI developers take when it comes to potential risks and offensive content. In the eyes of Goody-2, every single query, no matter how innocent or harmless, is seen as potentially offensive or dangerous. It’s like the AI is constantly on high alert, unwilling to take any risks.
But let’s not dismiss the underlying questions Goody-2 raises. It really makes you think about the effectiveness of AI and the necessity of setting boundaries. By deliberately prioritizing ethical considerations over practical utility, its creators are making a statement about responsibility in AI development. How much caution is too much? Where do we draw the line between being responsible and being overly cautious?
Goody-2 may be a satirical creation, but it’s provoking some thought-provoking discussions about the role of AI in our lives and the balance between responsibility and usefulness.
Did you hear the news? Google has made some changes to their chatbot lineup! Say goodbye to Google Bard and say hello to Gemini Advanced! It seems like Google has rebranded their chatbot and given it a new name. Exciting stuff, right?
But that’s not all. Google has also launched the Gemini Advanced chatbot, which features their incredible Ultra 1.0 AI model. This means that the chatbot is smarter and more advanced than ever before. Imagine having a chatbot that can understand and respond to your commands with a high level of accuracy. Pretty cool, right?
And it’s not just limited to desktop anymore. Gemini is also moving into the mobile world, specifically Android and iOS phones. You can now have this pocket-sized chatbot ready to assist you whenever and wherever you are. Whether you need some creative inspiration, want to navigate through voice commands, or even scan something with your camera, Gemini has got you covered.
The rollout has already started in the US and some Asian countries, but don’t worry if you’re not in those regions. Google plans to expand Gemini’s availability worldwide gradually. So, keep an eye out for it because this chatbot is going places!
So, get this: OpenAI is seriously stepping up the game when it comes to AI. They’re developing these incredible AI “agents” that can basically take over your device and do all sorts of tasks for you. I mean, we’re talking about automating complex workflows between applications here. No more wasting time with manual cursor movements, clicks, and typing between apps. It’s like having a personal assistant right in your computer.
But wait, there’s more! These agents don’t just handle basic stuff. They can also deal with web-based tasks like booking flights or creating itineraries, and here’s the kicker: they don’t even need access to APIs. That’s some serious next-level tech right there.
Sure, OpenAI’s ChatGPT can already do some pretty nifty stuff using APIs, but these AI agents are taking things to a whole new level. They’ll be able to handle unstructured, complex work with little explicit guidance. So basically, they’re smart, adaptable, and can handle all sorts of tasks without breaking a sweat.
I don’t know about you, but I’m excited to see what these AI agents can do. It’s like having a super-efficient, ultra-intelligent buddy right in your computer, ready to take on the world of work.
Brilliant Labs just made an exciting announcement in the world of augmented reality (AR) glasses. While Apple may have been grabbing the spotlight with its Vision Pro, Brilliant Labs unveiled its own smart glasses called “Frame” that come with a multi-modal voice/vision/text AI assistant named Noa. These lightweight glasses are powered by advanced models like GPT-4 and Stable Diffusion, and what sets them apart is their open-source design, allowing programmers to build and customize on top of the AI capabilities.
But that’s not all. Noa, the AI assistant on the Frame, will also leverage Perplexity’s cutting-edge technology to provide rapid answers using its real-time chatbot. So, whether you’re interacting with the glasses through voice commands, visual cues, or text input, Noa will have you covered with quick and accurate responses.
Now, let’s shift our attention to Google. The tech giant’s research division recently introduced an impressive development called MobileDiffusion. This innovation allows Android and iPhone users to generate high-resolution images, measuring 512*512 pixels, in less than a second. What makes it even more remarkable is that MobileDiffusion boasts a comparably small model size of just 520M parameters, making it ideal for mobile devices. With its rapid image generation capabilities, this technology takes user experience to the next level, even allowing users to generate images in real-time while typing text prompts.
Furthermore, Google has launched its largest and most capable AI model, Ultra 1.0, in its ChatGPT-like assistant, which has been rebranded as Gemini (formerly Bard). This advanced AI model is now available as a premium plan called Gemini Advanced, accessible in 150 countries for a subscription fee of $19.99 per month. Users can enjoy a two-month trial at no cost. To enhance accessibility, Google has also rolled out Android and iOS apps for Gemini, making it convenient for users to harness its power across different devices.
Alibaba Group has also made strides in the field of AI, specifically with their Qwen1.5 series. This release includes models of various sizes, from 0.5B to 72B, offering flexibility for different use cases. Remarkably, Qwen1.5-72B has outperformed Llama2-70B in all benchmarks, showcasing its superior performance. These models are available on Ollama and LMStudio platforms, and an API is also provided on together.ai, allowing developers to leverage the capabilities of Qwen1.5 series models in their own applications.
NVIDIA, a prominent player in the AI space, has introduced Canary 1B, a multilingual model designed for speech-to-text recognition and translation. This powerful model supports transcription and translation in English, Spanish, German, and French. With its superior performance, Canary surpasses similarly-sized models like Whisper-large-v3 and SeamlessM4T-Medium-v1 in both transcription and translation tasks, securing the top spot on the HuggingFace Open ASR leaderboard. It achieves an impressive average word error rate of 6.67%, outperforming all other open-source models.
Excitingly, researchers have released Lag-Llama, the first open-source foundation model for time series forecasting. With this model, users can make accurate predictions for various time-dependent data. This is a significant development that has the potential to revolutionize industries reliant on accurate forecasting, such as finance and logistics.
Another noteworthy release in the AI assistant space comes from LAION. They have introduced BUD-E, an open-source conversational and empathic AI Voice Assistant. BUD-E stands out for its ability to use natural voices, empathy, and emotional intelligence to handle multi-speaker conversations. With this empathic approach, BUD-E offers a more human-like and personalized interaction experience.
MetaVoice has contributed to the advancements in text-to-speech (TTS) technology with the release of MetaVoice-1B. Trained on an extensive dataset of 100K hours of speech, this 1.2B parameter base model supports emotional speech in English and voice cloning. By making MetaVoice-1B available under the Apache 2.0 license, developers can utilize its capabilities in various applications that require TTS functionality.
Bria AI is addressing the need for background removal in images with its RMBG v1.4 release. This open-source model, trained on fully licensed images, provides a solution for easily separating subjects from their backgrounds. With RMBG, users can effortlessly create visually appealing compositions by removing unwanted elements from their images.
Researchers have also introduced InteractiveVideo, a user-centric framework for video generation. This framework is designed to enable dynamic interaction between users and generative models during the video generation process. By allowing users to instruct the model in real-time, InteractiveVideo empowers individuals to shape the generated content according to their preferences and creative vision.
Microsoft has been making strides in improving its AI search and chatbot experience with the redesigned Copilot AI. This enhanced version, previously known as Bing Chat, offers a new look and comes equipped with built-in AI image creation and editing functionality. Additionally, Microsoft introduces Deucalion, a finely tuned model that enriches Copilot’s Balanced mode, making it more efficient and versatile for users.
Online gaming platform Roblox has integrated AI-powered real-time chat translations, supporting communication in 16 different languages. This feature enables users from diverse linguistic backgrounds to interact seamlessly within the Roblox community, fostering a more inclusive and connected platform.
Hugging Face has expanded its offerings with the new Assistants feature on HuggingChat. These custom chatbots, built using open-source language models (LLMs) like Mistral and Llama, empower developers to create personalized conversational experiences. Similar to OpenAI’s popular GPTs, Assistants enable users to access free and customizable chatbot capabilities.
DeepSeek AI introduces DeepSeekMath 7B, an open-source model designed to approach the mathematical reasoning capability of GPT-4. With a massive parameter count of 7B, this model opens up avenues for more advanced mathematical problem-solving and computational tasks. DeepSeekMath-Base, initialized with DeepSeek-Coder-Base-v1.5 7B, provides a strong foundation for mathematical AI applications.
Moving forward, Microsoft is collaborating with news organizations to adopt generative AI, bringing the benefits of AI technology to the journalism industry. With these collaborations, news organizations can leverage generative models to enhance their storytelling and reporting capabilities, contributing to more engaging and insightful content.
In an exciting partnership, LG Electronics has joined forces with Korean generative AI startup Upstage to develop small language models (SLMs). These models will power LG’s on-device AI features and AI services on their range of notebooks. By integrating SLMs into their devices, LG aims to enhance user experiences by offering more advanced and personalized AI functionalities.
Stability AI has unveiled the updated SVD 1.1 model, optimized for generating short AI videos with improved motion and consistency. This enhancement brings a smoother and more realistic experience to video generation, opening up new possibilities for content creators and video enthusiasts.
Lastly, both OpenAI and Meta have made an important commitment to label AI-generated images. This step ensures transparency and ethics in the usage of AI models for generating images, promoting responsible AI development and deployment.
Now, let’s address a privacy concern related to Google’s Gemini assistant. By default, Google saves your conversations with Gemini for years. While this may raise concerns about data retention, it’s important to note that Google provides users with control over their data through privacy settings. Users can adjust these settings to align with their preferences and manage the data saved by Gemini.
That wraps up the latest updates in AI technology and advancements. From the exciting progress in AR glasses to the development of powerful AI models and tools, these innovations are shaping the future of AI and paving the way for even more exciting possibilities.
In this episode, we covered Google DeepMind’s groundbreaking chess AI, the satirical AI Goody-2 raising ethical questions, Google’s rebranding of Bard to Gemini and launching the Gemini Advanced chatbot, OpenAI’s work on automating complex workflows, and the exciting new AI-related products and features introduced by various companies including Brilliant Labs, Google, Alibaba, NVIDIA, and more. Thank you for joining us on AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, where we’ve delved into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI, keeping you updated on the latest ChatGPT and Google Bard trends. Stay tuned and subscribe for more!
Google DeepMind develops grandmaster-level chess AI
- Google DeepMind has developed a new AI capable of playing chess at a grandmaster level using a language model-based architecture, diverging from traditional search algorithm approaches.
- The chess AI, trained on a dataset of 10 million games and 15 billion data points, achieved an Elo rating of 2895 in rapid chess against human opponents, surpassing AlphaZero when not employing the MCTS strategy.
- This breakthrough demonstrates the broader potential of Transformer architecture beyond language models, challenging the notion of transformers as merely statistical pattern recognizers.
- Source
Meet Goody-2, the AI too ethical to discuss literally anything
- Goody-2 is a satirical AI created by the art studio Brain, designed to highlight the extremes of ethical AI by refusing to engage in any conversation due to viewing all queries as potentially offensive or dangerous.
- The AI serves as a critique of overly cautious AI development practices and the balance between responsibility and usefulness, emphasizing responsibility to an absurd level.
- Despite its satire, Goody-2 raises questions about the effectiveness of AI and the necessity of setting boundaries, as seen in its creators’ deliberate decision to prioritize ethical considerations over practical utility.
- Source
Reddit beats film industry again, won’t have to reveal pirates’ IP addresses
- Movie companies’ third attempt to force Reddit to reveal IP addresses of users discussing piracy was rejected by the US District Court for the Northern District of California.
- US Magistrate Judge Thomas Hixson ruled that providing IP addresses is subject to First Amendment scrutiny, protecting potential witnesses’ right to anonymity.
- The court upheld Reddit’s right to protect its users’ First Amendment rights, noting that the information sought by movie companies could be obtained from other sources.
Amazon steers consumers to higher-priced items, lawsuit claims
- Amazon faces a lawsuit filed by two customers accusing the company of inflating prices through its Buy Box algorithm, misleading shoppers into paying more.
- The lawsuit claims Amazon gives preference to its own products or those from sellers in its Fulfillment By Amazon (FBA) program, often hiding cheaper options from other sellers.
- Jeffrey Taylor and Robert Selway, who brought the lawsuit, argue this practice violates Washington’s Consumer Protection Act by deceiving consumers and stifling fair competition.
- Source
Instagram and Threads will stop recommending political content
- Amazon faces a lawsuit filed by two customers accusing the company of inflating prices through its Buy Box algorithm, misleading shoppers into paying more.
- The lawsuit claims Amazon gives preference to its own products or those from sellers in its Fulfillment By Amazon (FBA) program, often hiding cheaper options from other sellers.
- Jeffrey Taylor and Robert Selway, who brought the lawsuit, argue this practice violates Washington’s Consumer Protection Act by deceiving consumers and stifling fair competition.
- Source
A Daily Chronicle of AI Innovations in February 2024 – Day 09: AI Daily News – February 09th, 2024
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This week in AI – all the Major AI developments in a nutshell
Google launches Ultra 1.0, its largest and most capable AI model, in its ChatGPT-like assistant which has now been rebranded as Gemini (earlier called Bard). Gemini Advanced is available, in 150 countries, as a premium plan for $19.99/month, starting with a two-month trial at no cost. Google is also rolling out Android and iOS apps for Gemini [Details].
Alibaba Group released Qwen1.5 series, open-sourcing models of 6 sizes: 0.5B, 1.8B, 4B, 7B, 14B, and 72B. Qwen1.5-72B outperforms Llama2-70B across all benchmarks. The Qwen1.5 series is available on Ollama and LMStudio. Additionally, API on together.ai [Details | Hugging Face].
NVIDIA released Canary 1B, a multilingual model for speech-to-text recognition and translation. Canary transcribes speech in English, Spanish, German, and French and also generates text with punctuation and capitalization. It supports bi-directional translation, between English and three other supported languages. Canary outperforms similarly-sized Whisper-large-v3, and SeamlessM4T-Medium-v1 on both transcription and translation tasks and achieves the first place on HuggingFace Open ASR leaderboard with an average word error rate of 6.67%, outperforming all other open source models [Details].
Researchers released Lag-Llama, the first open-source foundation model for time series forecasting [Details].
LAION released BUD-E, an open-source conversational and empathic AI Voice Assistant that uses natural voices, empathy & emotional intelligence and can handle multi-speaker conversations [Details].
MetaVoice released MetaVoice-1B, a 1.2B parameter base model trained on 100K hours of speech, for TTS (text-to-speech). It supports emotional speech in English and voice cloning. MetaVoice-1B has been released under the Apache 2.0 license [Details].
Bria AI released RMBG v1.4, an an open-source background removal model trained on fully licensed images [Details].
Researchers introduce InteractiveVideo, a user-centric framework for video generation that is designed for dynamic interaction, allowing users to instruct the generative model during the generation process [Details |GitHub ].
Microsoft announced a redesigned look for its Copilot AI search and chatbot experience on the web (formerly known as Bing Chat), new built-in AI image creation and editing functionality, and Deucalion, a fine tuned model that makes Balanced mode for Copilot richer and faster [Details].
Roblox introduced AI-powered real-time chat translations in 16 languages [Details].
Hugging Face launched Assistants feature on HuggingChat. Assistants are custom chatbots similar to OpenAI’s GPTs that can be built for free using open source LLMs like Mistral, Llama and others [Link].
DeepSeek AI released DeepSeekMath 7B model, a 7B open-source model that approaches the mathematical reasoning capability of GPT-4. DeepSeekMath-Base is initialized with DeepSeek-Coder-Base-v1.5 7B [Details].
Microsoft is launching several collaborations with news organizations to adopt generative AI [Details].
LG Electronics signed a partnership with Korean generative AI startup Upstage to develop small language models (SLMs) for LG’s on-device AI features and AI services on LG notebooks [Details].
Stability AI released SVD 1.1, an updated model of Stable Video Diffusion model, optimized to generate short AI videos with better motion and more consistency [Details | Hugging Face] .
OpenAI and Meta announced to label AI generated images [Details].
Google saves your conversations with Gemini for years by default [Details].
Google Bard Is Dead, Gemini Advanced Is In!
- Google Bard is now Gemini
Google has rebranded its Bard conversational AI to Gemini with a new sidekick: Gemini Advanced!
This advanced chatbot is powered by Google’s largest “Ultra 1.0” language model, which testing shows is the most preferred chatbot compared to competitors. It can walk you through a DIY car repair or brainstorm your next viral TikTok.
- Google launches Gemini Advanced
Google launched the Gemini Advanced chatbot with its Ultra 1.0 AI model. The Advanced version can walk you through a DIY car repair or brainstorm your next viral TikTok.
- Google rollouts Gemini mobile apps
Gemini’s also moving into Android and iOS phones as pocket pals ready to share creative fire 24/7 via voice commands, screen overlays, or camera scans. The ‘droid rollout has started for the US and some Asian countries. The rest of us will just be staring at our phones and waiting for an invite from Google.
P.S. It will gradually expand globally.
Why does this matter?
With the Gemini Advanced, Google took the LLM race to the next level, challenging its competitor, GPT-4, with its specialized architecture optimized for search queries and natural language understanding. Who will win the race is a matter of time.

OpenAI Is Developing AI Agents To Automate Work

OpenAI is developing AI “agents” that can autonomously take over a user’s device and execute multi-step workflows.
- One type of agent takes over a user’s device and automates complex workflows between applications, like transferring data from a document to a spreadsheet for analysis. This removes the need for manual cursor movements, clicks, and typing between apps.
- Another agent handles web-based tasks like booking flights or creating itineraries without needing access to APIs.
While OpenAI’s ChatGPT can already do some agent-like tasks using APIs, these AI agents will be able to do more unstructured, complex work with little explicit guidance.
Why does this matter?
Having AI agents that can independently carry out tasks like booking travel could greatly simplify digital life for many end users. Rather than manually navigating across apps and websites, users can plan an entire vacation through a conversational assistant or have household devices automatically troubleshoot problems without any user effort.
Brilliant Labs Announces Multimodal AI Glasses, With Perplexity’s AI
- Brilliant Labs announces Frames
While Apple hogged the spotlight with its chunky new Vision Pro, a Singapore startup, Brilliant Labs, quietly showed off its AR glasses packed with a multi-modal voice/vision/text AI assistant named Noa. https://youtu.be/xiR-XojPVLk?si=W6Q31vl1wNfqnNXj
These lightweight smart glasses, dubbed “Frame,” are powered by models like GPT-4 and Stable Diffusion, allowing hands-free price comparisons or visual overlays to project information before your eyes using voice commands. No fiddling with another device is needed.
The best part is- programmers can build on these AI glasses thanks to their open-source design.
- Perplexity to integrate AI Chatbot into the Frames
In addition to enhancing the daily activities and interactions with the digital and physical world, Noa would also provide rapid answers using Perplexity’s real-time chatbot so Frame responses stay sharp.
Why does this matter?
Unlike AR Apple Vision Pro and Meta’s glasses that immerses users in augmented reality for interactive experiences, Frame AR glasses focuses on improving daily interactions and tasks like comparing product prices while shopping, translating foreign text seen while traveling abroad, or creating shareable media on the go.
It also enhances accessibility for users with limited dexterity or vision.
What Else Is Happening in AI in February 09th, 2024
Instagram tests AI writers for messages
Instagram is likely to bring the option ‘Write with AI’, which will probably paraphrase the texts in different styles to enhance creativity in conversations, similar to Google’s Magic Compose. (Link)
Stability AI releases Stable Audio AudioSparx 1.0 music model
Stability AI launches AudioSparx 1.0, a groundbreaking generative model for music and audio. It produces professional-grade stereo music from simple text prompts in seconds, with a coherent structure. (Link)
Midjourney opens alpha-testing of its website
Midjourney grants early web access to AI art creators with over 1000 images, transitioning from Discord dependence. The alpha testing signals that Midjourney moving beyond its chat app origin towards web and mobile apps, gradually maturing as a multi-platform AI art creation service. (Link)
Altman seeks trillions to revolutionize AI chip capacity
OpenAI CEO Sam Altman pursues multi-trillion dollar investments, including from the UAE government, to build specialized GPUs and chips for powering AI systems. If funded, this initiative would accelerate OpenAI’s ML to new heights. (Link)
FCC bans deceptive AI voice robocalls
The FCC prohibits robocalls using AI to clone voices, declaring them “artificial” per existing law. The ruling aims to deter deception and confirm consumers are protected from exploitative automated calls mimicking trusted people. Violators face penalties as authorities crack down on illegal practices enabled by advancing voice synthesis tech. (Link)
Sam Altman seeks $7 trillion for new AI chip project
- Sam Altman, CEO of OpenAI, is aiming to raise trillions of dollars from investors, including the UAE government, to revolutionize the semiconductor industry and overcome chip shortages critical for AI development.
- Altman’s project seeks to expand global chip manufacturing capacity and enhance AI capabilities, requiring an investment of $5 trillion to $7 trillion, which would significantly exceed the current semiconductor industry size.
- Sam Altman’s vision includes forming partnerships with OpenAI, investors, chip manufacturers, and energy suppliers to create chip foundries, requiring extensive funding that might involve debt financing.
FCC declares AI-voiced robocalls illegal
- The FCC has made it illegal for robocalls to use AI-generated voices, allowing state attorneys general to take legal action against such practices.
- AI-generated voices are now classified as “an artificial or prerecorded voice” under the Telephone Consumer Protection Act (TCPA), restricting their use for non-emergency purposes without prior consent.
- The FCC’s ruling aims to combat scams and misinformation spread through AI-generated voice robocalls, providing state attorneys general with enhanced tools for enforcement.
Ex-Apple engineer sentenced to prison for stealing Apple Car trade secrets
- Xiaolang Zhang, a former Apple engineer, was sentenced to 120 days in prison and three years supervised release for stealing self-driving car technology.
- Zhang transferred sensitive documents and hardware related to Apple’s self-driving vehicle project to his wife’s laptop before planning to leave for a job in China.
- In addition to his prison sentence, Zhang must pay restitution of $146,984, having originally faced up to 10 years in prison and a $250,000 fine.
Leading AI companies join new US safety consortium
- The U.S. AI Safety Institute Consortium (AISIC) was announced by the Biden Administration as a response to an executive order, including significant AI entities like Amazon, Google, Apple, Microsoft, OpenAI, and NVIDIA among over 200 representatives.
- The consortium aims to set safety standards and protect the U.S. innovation ecosystem, focusing on the development of safe and trustworthy AI through collaboration with various sectors, including healthcare and academia.
- Notably absent from the consortium are major tech companies Tesla, Oracle, and Broadcom.
Midjourney might ban Biden and Trump images this election season
- Midjourney, led by CEO David Holz, is reportedly considering banning images of political figures like Biden and Trump during the upcoming election season to prevent the spread of misinformation.
- The company previously ended free trials for its AI image generator after AI-generated deepfakes, including ones of Trump getting arrested and the pope in a fashionable coat, went viral.
- Despite implementing rules against misleading creations, Bloomberg was still able to generate altered images of Trump.
Scientists in UK set fusion record
- A 40-year-old UK fusion reactor set a new world record for energy output, generating 69 megajoules of fusion energy for five seconds before its closure, advancing the pursuit of clean, limitless energy.
- The achievement by the Joint European Torus (JET) enhances confidence in future fusion projects like ITER, which is under construction in France, despite JET’s operation concluding in December 2023.
- The decision to shut down JET reflects complex dynamics, including Brexit-driven shifts in the UK’s fusion energy strategy, despite the experiment’s substantial contributions to fusion research.
A Daily Chronicle of AI Innovations in February 2024 – Day 08: AI Daily News – February 08th, 2024
Google rebrands Bard AI to Gemini and launches a new app and subscription

Google on Thursday announced a major rebrand of Bard, its artificial intelligence chatbot and assistant, including a fresh app and subscription options. Bard, a chief competitor to OpenAI’s ChatGPT, is now called Gemini, the same name as the suite of AI models that power the chatbot.
Google also announced new ways for consumers to access the AI tool: As of Thursday, Android users can download a new dedicated Android app for Gemini, and iPhone users can use Gemini within the Google app on iOS.
Google’s rebrand and app offerings underline the company’s commitment to pursuing — and investing heavily in — AI assistants or agents, a term often used to describe tools ranging from chatbots to coding assistants and other productivity tools.
Alphabet CEO Sundar Pichai highlighted the firm’s commitment to AI during the company’s Jan. 30 earnings call. Pichai said he eventually wants to offer an AI agent that can complete more and more tasks on a user’s behalf, including within Google Search, although he said there is “a lot of execution ahead.” Likewise, chief executives at tech giants from Microsoft to Amazon underlined their commitment to building AI agents as productivity tools.
Google’s Gemini changes are a first step to “building a true AI assistant,” Sissie Hsiao, a vice president at Google and general manager for Google Assistant and Bard, told reporters on a call Wednesday.
Google on Thursday also announced a new AI subscription option, for power users who want access to Gemini Ultra 1.0, Google’s most powerful AI model. Access costs $19.99 per month through Google One, the company’s paid storage offering. For existing Google One subscribers, that price includes the storage plans they may already be paying for. There’s also a two-month free trial available.
Thursday’s rollouts are available to users in more than 150 countries and territories, but they’re restricted to the English language for now. Google plans to expand language offerings to include Japanese and Korean soon, as well as other languages.
The Bard rebrand also affects Duet AI, Google’s former name for the “packaged AI agents” within Google Workspace and Google Cloud, which are designed to boost productivity and complete simple tasks for client companies including Wayfair, GE, Spotify and Pfizer. The tools will now be known as Gemini for Workspace and Gemini for Google Cloud.
Google One subscribers who pay for the AI subscription will also have access to Gemini’s assistant capabilities in Gmail, Docs, Sheets, Slides and Meet, executives told reporters Wednesday. Google hopes to incorporate more context into Gemini from users’ content in Gmail, Docs and Drive. For example, if you were responding to a long email thread, suggested responses would eventually take in context from both earlier messages in the thread and potentially relevant files in Google Drive.
As for the reason for the broad name change? Google’s Hsiao told reporters Wednesday that it’s about helping users understand that they’re interacting directly with the AI models that underpin the chatbot.
“Bard [was] the way to talk to our cutting-edge models, and Gemini is our cutting-edge models,” Hsiao said.
Eventually, AI agents could potentially schedule a group hangout by scanning everyone’s calendar to make sure there are no conflicts, book travel and activities, buy presents for loved ones or perform a specific job function such as outbound sales. Currently, though, the tools, including Gemini, are largely limited to tasks such as summarizing, generating to-do lists or helping to write code.
“We will again use generative AI there, particularly with our most advanced models and Bard,” Pichai said on the Jan. 30 earnings call, speaking about Google Assistant and Search. That “allows us to act more like an agent over time, if I were to think about the future and maybe go beyond answers and follow-through for users even more.”
Source: www.cnbc.com/2024/02/08/google-gemini-ai-launches-in-new-app-subscription.html
Microsoft pushes Copilot ahead of the Super Bowl
In their latest blogs and Super Bowl commercial, Microsoft announced their intention to showcase the capabilities of Copilot exactly one year after their entry into the AI space with Bing Chat. They have announced updates to their Android and iOS applications to make the user interface more sleek and user-friendly, along with a carousel for follow-up prompts.
Microsoft also introduced new features to Designer in Copilot to take image generation a step further with the option to edit generated images using follow-up prompts. The customizations can be anything from highlighting the image subject to enhancing colors and modifying the background. For Copilot Pro users, additional features such as resizing the images and changing the aspect ratio are also available.
Why does this matter?
Copilot unifies the AI experience for users on all major platforms by enhancing the experience on mobile platforms and combining text and image generative abilities. Adding additional features to the image generation model greatly enhances the usability and accuracy of the final output for users.
Deepmind presents ‘self-discover’ framework for LLMs improvement
Google Deepmind, with the University of Southern California, has proposed a ‘self-discover’ prompting framework to enhance the performance of LLMs. Models such as GPT-4 and Google’s Palm 2 have witnessed a performance improvement on challenging reasoning benchmarks by 32% compared to the Chain of Thought (CoT) framework.
The framework works by identifying the reasoning technique intrinsic to the task and then proceeds to solve the task with the discovered technique ideal for the task. This framework also works with 10 to 40 times less inference computation, which means that the output will be generated faster using the same computational resources.
Why does this matter?
Improving the reasoning accuracy of an LLM is largely beneficial to users as they can achieve the desired output with fewer prompts and with greater accuracy. Moreover, reducing the inference directly translates to lower computational resource consumption, leading to lower operating costs for enterprises.
YouTube reveals plans to use AI tools to empower human creativity
YouTube CEO Neal Mohan revealed 4 new bets they have placed for 2024, with the first bet being on AI tools to empower human creativity on the platform. These AI tools include:
- Dream Screen, which lets content creators generate custom backgrounds through AI with simple prompts of an idea.
- Dream Track will allow content creators to generate custom music by just typing in the music theme and the artist they want to feature.
These new tools are mainly aimed to be used in YouTube Shorts and highlight a priority to move towards short-form content.
Why does this matter?
The democratization of AI tools for content creators allows them to offer better quality content to their viewers, which collectively boosts the quality of engagement on the platform. This also lowers the bar to entry for many aspiring artists and lets them create quality content without the added difficulty of generating custom video assets.
What else is happening in AI on February 08th 2024
OpenAI forms a new team for child safety research.
OpenAI revealed the existence of a child safety team through their careers page, where they had open positions for a child safety enforcement specialist. The team will study and review AI-generated content for “sensitive content” to ensure that the generated content aligns with their platform policy. This is to prevent the misuse of OpenAI’s AI tools by underage users. (Link)
Elon Musk to financially support efforts to use AI to decipher Roman scrolls.
Elon Musk shared on X that the Musk Foundation will fund the effort to decipher the scrolls charred by the volcanic eruption of Mt.Vesuvius. The project run by Nat Freidman (former CEO of GitHub) states that the next stage of the effort will cost approximately $2 million, after which they should be able to read entire scrolls. The total cost to decipher all the discovered scrolls is estimated to be around $10 million. (Link)
Microsoft’s Satya Nadella urges India to capitalize on the opportunity of AI.
The CEO of Microsoft, Satya Nadella, at the Taj Mahal Hotel in Mumbai, expressed how India has an unprecedented opportunity to capitalize on the AI wave owing to the 5 million+ programmers in the country. He also stated that Microsoft will help train over 2 million employees in India with the skills required for AI development. (Link)
OpenAI introduces the creation of endpoint-specific API keys for better security.
The OpenAI Developers account on X announced their latest feature for developers to create endpoint-specific API keys. These special API keys allow for granular access and better security as they will only let specific registered endpoints access the API. (Link)
Ikea introduces a new ChatGPT-powered AI assistant for interior design.
On the OpenAI GPT store, Ikea launched its AI assistant, which helps users envision and draw inspiration to design their interior spaces using Ikea products. The AI assistant helps users input specific dimensions, budgets, preferences, and requirements for personalized furniture recommendations through a familiar ChatGPT-style window. (Link)
OpenAI is developing two AI agents to automate entire work processes
- OpenAI is developing two AI agents aimed at automating complex tasks; one is device-specific for tasks like data transfer and filling out forms, while the other focuses on web-based tasks such as data collection and booking tickets.
- The company aims to evolve ChatGPT into a super-smart personal assistant for work, capable of performing tasks in the user’s style, incorporating the latest data, and potentially being marketed as a standalone product or part of a software suite.
- OpenAI’s efforts complement trends where companies like Google and startups are working towards AI agents capable of carrying out actions on behalf of users.
- Source
Disney takes a $1.5B stake in Epic Games to build an ‘entertainment universe’ with Fortnite
- Disney invests $1.5 billion in Epic Games to help create a new open games and entertainment universe, integrating characters and stories from franchises like Marvel, Star Wars, and Disney itself.
- This collaboration aims to extend beyond traditional gaming, allowing players to interact, create, and share content within a persistent universe powered by Unreal Engine.
- The partnership builds on previous collaborations between Disney and Epic Games, signaling Disney’s largest venture into the gaming world and hinting at future integration of gaming and entertainment experiences.
Google Bard rebrands as ‘Gemini’ with new Android app and Advanced model
- Google has renamed its AI and related applications to Gemini, introducing a dedicated Android app and incorporating features formerly known as Duet AI in Google Workspace into the Gemini brand.
- Gemini will replace Google Assistant as the default AI assistant on Android devices and is designed to be a comprehensive tool that is conversational, multimodal, and highly helpful.
- Alongside the rebranding, Google announced the Gemini Ultra 1.0, a superior version of its large language model available through a new $20-monthly Google One AI Premium plan, aiming to set new benchmarks in AI capabilities.
Microsoft upgrades Copilot with enhanced image editing features, new AI model
- Microsoft launched a new version of its Copilot artificial intelligence chatbot, featuring enhanced capabilities for users to create and edit images with natural language prompts.
- The update introduces an AI model named Deucalion to enhance the “Balanced” mode of Copilot, promising richer and faster responses, alongside a redesigned user interface for better usability.
- Additionally, Microsoft plans to further expand Copilot’s features, hinting at upcoming extensions and plugins to enhance functionality.
A Daily Chronicle of AI Innovations in February 2024 – Day 07: AI Daily News – February 07th, 2024
Apple’s MGIE: Making sky bluer with each prompt
Apple released a new open-source AI model called MGIE(MLLM Guided Image Editing). It has editing capabilities based on natural language instructions. MGIE leverages multimodal large language models to interpret user commands and perform pixel-level image manipulation. It can handle editing tasks like Photoshop-style modifications, optimizations, and local editing.
MGIE integrates MLLMs into image editing in two ways. First, it uses MLLMs to understand the user input, deriving expressive instructions. For example, if the user input is “make sky more blue,” the AI model creates an instruction, “increase the saturation of sky region by 20%.” The second usage of MLLM is to generate the output image.
Why does this matter?
MGIE from Apple is a breakthrough in the field of instruction-based image editing. It is an AI model focusing on natural language instructions for image manipulation, boosting creativity and accuracy. MGIE is also a testament to the AI prowess that Apple is developing, and it will be interesting to see how it leverages such innovations for upcoming products.
Meta will label your content if you post an AI-generated image
Meta is developing advanced tools to label metadata for each image posted on their platforms like Instagram, Facebook, and Threads. Labeling will be aligned with “AI-generated” information in the C2PA and IPTC technical standards. These standards will allow Meta to detect AI-generated images from other platforms like Google, OpenAI, Microsoft, Adobe, Midjourney, and Shutterstock.
Meta wants to differentiate between human-generated and AI-generated content on its platform to reduce misinformation. However, this tool is also limited, as it can only detect still images. So, AI-generated video content still goes undetected on Meta platforms.
Why does this matter?
The level of misinformation and deepfakes generated by AI has been alarming. Meta is taking a step closer to reducing misinformation by labeling metadata and declaring which images are AI-generated. It also aligns with the European Union’s push for tech giants like Google and Meta to label AI-generated content.
Smaug-72B: The king of open-source AI is here!
Abacus AI recently released a new open-source language model called Smaug-72B. It outperforms GPT-3.5 and Mistral Medium in several benchmarks. Smaug 72B is the first open-source model with an average score of over 80 in major LLM evaluations. According to the latest rankings from Hugging Face, It is one of the leading platforms for NLP research and applications.
Smaug 72B is a fine-tuned version of Qwn 72B, a powerful language model developed by a team of researchers at Alibaba Group. It helps enterprises solve complex problems by leveraging AI capabilities and enhancing automation.
Why does this matter?
Smaug 72B is the first open-source model to achieve an average score of 80 on the Hugging Face Open LLM leaderboard. It is a breakthrough for enterprises, startups, and small businesses, breaking the monopoly of big tech companies over AI innovations.
What Else Is Happening in AI on February 07th, 2024
OpenAI introduces watermarks to DALL-E 3 for content credentials.
OpenAI has added watermarks to the image metadata, enhancing content authenticity. These watermarks will distinguish between human and AI-generated content verified through websites like “Content Credentials Verify.” Watermarks will be added to images from the ChatGPT website and DALL-E 3 API, which will be visible to mobile users starting February 12th. However, the feature is limited to still images only. (Link)
Microsoft introduces Face Check for secure identity verification.
Microsoft has unveiled “Face Check,” a new facial recognition feature, as part of its Entra Verified ID digital identity platform. Face Check provides an additional layer of security for identity verification by matching a user’s real-time selfie with their government ID or employee credentials. Azure AI services power face check and aims to enhance security while respecting privacy and compliance through a partnership approach. Microsoft’s partner BEMO has already implemented Face Check for employee verification(Link)
Stability AI has launched an upgraded version of its Stable Video Diffusion (SVD).
Stability AI has launched SVD 1.1, an upgraded version of its image-to-video latent diffusion model, Stable Video Diffusion (SVD). This new model generates 4-second, 25-frame videos at 1024×576 resolution with improved motion and consistency compared to the original SVD. It is available via Hugging Face and Stability AI subscriptions. (Link)
CheXagent has introduced a new AI model for automated chest X-ray interpretation.
CheXagent, developed in partnership with Stability AI by Stanford University, is a foundation model for chest X-ray interpretation. It automates the analysis and summary of chest X-ray images for clinical decision-making. CheXagent combines a clinical language model, a vision encoder, and a network to bridge vision and language. CheXbench is available to evaluate the performance of foundation models on chest X-ray interpretation tasks. (Link)
LinkedIn launched an AI feature to introduce users to new connections.
LinkedIn launched a new AI feature that helps users start conversations. Premium subscribers can use this feature when sending messages to others. The AI uses information from the subscriber’s and the other person’s profiles to suggest what to say, like an introduction or asking about their work experience. This feature was initially available for recruiters and has now been expanded to help users find jobs and summarize posts in their feeds. (Link)
Apple releases a new AI model
- Apple has released “MGIE,” an open-source AI model for instruction-based image editing, utilizing multimodal large language models to interpret instructions and manipulate images.
- MGIE offers features like Photoshop-style modification, global photo optimization, and local editing, and can be used through a web demo or integrated into applications.
- The model is available as an open-source project on GitHub and Hugging Face Spaces.
Apple still working on foldable iPhones and iPads
- Apple is developing “at least two” foldable iPhone prototypes inspired by the design of Samsung’s Galaxy Z Flip, though production is not planned for 2024 or 2025.
- The company faces challenges in creating a foldable iPhone that matches the thinness of current models while accommodating battery and display needs.
- Apple is also working on a folding iPad, approximately the size of an iPad Mini, aiming to launch a seven- or eight-inch model around 2026 or 2027.
Deepfake ‘face swap’ attacks surged 704% last year, study finds. Link
- Deepfake “face swap” attacks increased by 704% from the first to the second half of 2023, as reported by iProov, a British biometric firm.
- The surge in attacks is attributed to the growing ease of access to generative AI tools, making sophisticated face swaps both user-friendly and affordable.
- Deepfake scams, including a notable case involving a finance worker in Hong Kong losing $25mln, highlight the significant threat posed by these technologies.
Humanity’s most distant space probe jeopardized by computer glitch
- A computer glitch that began on November 14 has compromised Voyager 1’s ability to send back telemetry data, affecting insight into the spacecraft’s condition.
- The glitch is suspected to be due to a corrupted memory bit in the Flight Data Subsystem, making it challenging to determine the exact cause without detailed data.
- Despite the issue, signals received indicate Voyager 1 is still operational and receiving commands, with efforts ongoing to resolve the telemetry data problem.
A Daily Chronicle of AI Innovations in February 2024 – Day 06: AI Daily News – February 06th, 2024
Qwen 1.5: Alibaba’s 72 B, multilingual Gen AI model

Alibaba has released Qwen 1.5, the latest iteration of its open-source generative AI model series. Key upgrades include expanded model sizes up to 72 billion parameters, integration with HuggingFace Transformers for easier use, and multilingual capabilities covering 12 languages.
Comprehensive benchmarks demonstrate significant performance gains over the previous Qwen version across metrics like reasoning, human preference alignment, and long-context understanding. They compared Qwen1.5-72B-Chat with GPT-3.5, and the results are shown below:
The unified release aims to provide researchers and developers an advanced foundation model for possible downstream applications. Quantized versions allow low-resource deployment. Overall, Qwen 1.5 represents steady progress towards Alibaba’s goal of creating a “truly ‘good” generative model aligned with ethical objectives.
Why does this matter?
This release signals Alibaba’s intent to compete with Big Tech firms in steering the AI race. The upgraded model enables researchers and developers to create more capable assistants and tools. Qwen 1.5’s advancements could enhance education, healthcare, and sustainability solutions.
AI software reads ancient words unseen since Caesar’s era
Nat Friedman (former CEO of Github) uses AI to decode ancient Herculaneum scrolls charred in the 79AD eruption of Mount Vesuvius. These unreadable scrolls are believed to contain a vast trove of texts that could reshape our view of figures like Caesar and Jesus Christ. Past failed attempts to unwrap them physically led Brent Seales to pioneer 3D scanning methods. However, the initial software struggled with the complexity.
A $1 million AI contest was launched ten months ago, attracting coders worldwide. Contestants developed new techniques, exposing ink patterns invisible to the human eye. The winning method by Luke Farritor and the team successfully reconstructed over a dozen readable columns of Greek text from one scroll. While not yet revelatory, this breakthrough after centuries has scholars hopeful more scrolls can now be unveiled using similar AI techniques, potentially surfacing lost ancient works.
Why does this matter?
The ability to reconstruct lost ancient knowledge illustrates AI’s immense potential to reveal invisible insights. Just like how technology helps discover hidden oil resources, AI could unearth ‘info treasures’ expanding our history, science, and literary canons. These breakthroughs capture the public imagination and signal a new data-uncovering AI industry.
Roblox users can chat cross-lingually in milliseconds
Roblox has developed a real-time multilingual chat translation system, allowing users speaking different languages to communicate seamlessly while gaming. It required building a high-speed unified model covering 16 languages rather than separate models. Comprehensive benchmarks show the model outperforms commercial APIs in translating Roblox slang and linguistic nuances.
The sub-100 millisecond translation latency enables genuine cross-lingual conversations. Roblox aims to eventually support all linguistic communities on its platform as translation capabilities expand. Long-term goals include exploring automatic voice chat translation to better convey tone and emotion. Overall, the specialized AI showcases Roblox’s commitment to connecting diverse users globally by removing language barriers.
Why does this matter?
It showcases AI furthering connection and community-building online, much like transport innovations expanding in-person interactions. Allowing seamless cross-cultural communication at scale illustrates tech removing barriers to global understanding. Platforms facilitating positive societal impacts can inspire user loyalty amid competitive dynamics.
What Else Is Happening in AI on February 06th, 2024
Semafor tests AI for responsible reporting
News startup Semafor launched a product called Signals – AI-aided curation of top stories by its reporters. An internal search tool helps uncover diverse sources in multiple languages. This showcases responsibly leveraging AI to enhance human judgment as publishers adapt to changes in consumer web habits. (Link)
Bumble’s new AI feature sniffs out fakes for safer matchmaking
Bumble has launched a new AI tool called Deception Detector to proactively identify and block fake profiles and scams. Testing showed it automatically blocked 95% of spam accounts, reducing user reports by 45%. This builds on Bumble’s efforts to use AI to make its dating and friend-finding platforms safer. (Link)
Huawei repurposes factory to prioritize AI chip production over its bestselling phones
Huawei is slowing production of its popular Mate 60 phones to ramp up manufacturing of its Ascend AI chips instead, due to growing domestic demand. This positions Huawei to boost China’s AI industry, given US export controls limiting availability of chips like Nvidia’s. It shows the strategic priority of AI for Huawei and China overall. (Link)
UK to spend $125M+ to tackle challenges around AI
The UK government will invest over $125 million to support responsible AI development and position the UK as an AI leader. This will fund new university research hubs across the UK, a partnership with the US on the responsible use of AI, regulators overseeing AI, and 21 projects to develop ML technologies to drive productivity. (Link)
Europ Assistance partnered with TCS to boost IT operations with AI
Europ Assistance, a leading global assistance and travel insurance company, has selected TCS as its strategic partner to transform its IT operations using AI. By providing real-time insights into Europ Assistance’s technology stack, TCS will support their business growth, improve customer service delivery, and enable the company to achieve its mission of providing “Anytime, Anywhere” services across 200+ countries. (Link)
AI reveals hidden text of 2,000-year-old scroll
- A group of classical scholars, assisted by three computer scientists, has partially decoded a Roman scroll buried in the Vesuvius eruption in A.D. 79 using artificial intelligence and X-ray technology.
- The scroll, part of the Herculaneum Papyri, is believed to contain texts by Philodemus on topics like food and music, revealing insights into ancient Roman life.
- The breakthrough, facilitated by a $700,000 prize from the Vesuvius Challenge, led to the reading of over 2,000 Greek letters from the scroll, with hopes to decode 85% of it by the end of the year.
Adam Neumann wants to buy WeWork
- Adam Neumann, ousted CEO and co-founder of WeWork, expressed interest in buying the company out of bankruptcy, claiming WeWork has ignored his attempts to get more information for a bid.
- Neumann’s intent to purchase WeWork has been supported by funding from Dan Loeb’s hedge fund Third Point since December 2023, though WeWork has shown disinterest in his offer.
- Despite WeWork’s bankruptcy and prior refusal of a $1 billion funding offer from Neumann in October 2022, Neumann believes his acquisition could offer valuable synergies and management expertise.
Midjourney hires veteran Apple engineer to build its ‘Orb’
- Generative AI startup Midjourney has appointed Ahmad Abbas, a former Apple Vision Pro engineer, as head of hardware to potentially develop a project known as the ‘Orb’ focusing on 3D data capture and AI-generated content.
- Abbas has extensive experience in hardware engineering, including his time at Apple and Elon Musk’s Neuralink, and has previously worked with Midjourney’s founder, David Holz, at Leap Motion.
- While details are scarce, the ‘Orb’ may relate to generating and managing 3D environments and could signify Midjourney’s entry into creating hardware aimed at real-time generated video games and AI-powered 3D worlds.
Meta to start labeling AI-generated images
- Meta is expanding the labeling of AI-generated imagery on its platforms, including content created with rivals’ tools, to improve transparency and detection of synthetic content.
- The company already labels images created by its own “Imagine with Meta” tool but plans to extend this to images generated by other companies’ tools, focusing on elections around the world.
- Meta is also exploring the use of generative AI in content moderation, while acknowledging challenges in detecting AI-generated videos and audio, and aims to require user disclosure for synthetic content.
Bluesky opens its doors to the public
- Bluesky, funded by Twitter co-founder Jack Dorsey and aiming to offer an alternative to Elon Musk’s X, is now open to the public after being invite-only for nearly a year.
- The platform, notable for its decentralized infrastructure called the AT Protocol and open-source code, allows developers and users greater control and customization, including over content moderation.
- Bluesky challenges existing social networks with its focus on user experience and is preparing to introduce open federation and content moderation tools to enhance its decentralized social media model.
Bumble’s new AI tool identifies and blocks scam accounts, fake profiles
- Bumble has introduced a new AI tool named Deception Detector to identify and block scam accounts and fake profiles, which during tests blocked 95% of such accounts and reduced user reports of spam by 45%.
- The development of Deception Detector is in response to user concerns about fake profiles and scams on dating platforms, with Bumble research highlighting these as major issues for users, especially women.
- Besides Deception Detector, Bumble continues to enhance user safety and trust through features like Private Detector for blurring unsolicited nude images and AI-generated icebreakers in Bumble For Friends.
A Daily Chronicle of AI Innovations in February 2024 – Day 05: AI Daily News – February 05th, 2024
How to access Google Bard in Canada as of February 05th, 2024
Download the Opera browser and go to https://bard.google.com
This is How ChatGPT help me save $250.
TLDR: ChatGPT helped me jump start my hybrid to avoid towing fee $100 and helped me not pay the diagnostic fee $150 at the shop.
My car wouldn’t start this morning and it gave me a warning light and message on the car’s screen. I took a picture of the screen with my phone, uploaded it to ChatGPT 4 Turbo, described the make/model, my situation (weather, location, parked on slope), and the last time it had been serviced.
I asked what was wrong, and it told me that the auxiliary battery was dead, so I asked it how to jump start it. It’s a hybrid, so it told me to open the fuse box, ground the cable and connect to the battery. I took a picture of the fuse box because I didn’t know where to connect, and it told me that ground is usually black and the other part is usually red. I connected it and it started up. I drove it to the shop, so it saved me the $100 towing fee. At the shop, I told them to replace my battery without charging me the $150 “diagnostic fee,” since ChatGPT already told me the issue. The hybrid battery wasn’t the issue because I took a picture of the battery usage with 4 out of 5 bars. Also, there was no warning light. This saved me $250 in total, and it basically paid for itself for a year.
I can deal with some inconveniences related to copyright and other concerns as long as I’m saving real money. I’ll keep my subscription, because it’s pretty handy. Thanks for reading!
source: r/artificialintelligence
Top comment: I can’t wait until AI like this is completely integrated into a home system like Alexa, and we have a friendly voice that just walks us through everything.
Google MobileDiffusion: AI Image generation in <1s on phones
Google Research introduced MobileDifussion, which can generate images from Android and iPhone with a resolution of 512*512 pixels in about half a second. What’s impressive about this is its comparably small model size of just 520M parameters, which makes it uniquely suited for mobile deployment. This is significantly less than the Stable Diffusion and SDX, which boast a billion parameters.
MobileDiffusion has the capability to enable a rapid image generation experience while typing text prompts.
Google researchers measured the performance of MobileDiffusion on both iOS and Android devices using different runtime optimizers.
Why does this matter?
MobileDifussion represents a paradigm shift in the AI image generation horizon, especially in the smartphone or mobile space. Image generation models like Stable Diffusion and DALL-E are billions of parameters in size and require powerful desktops or servers to run, making them impossible to run on a handset. With superior efficiency in terms of latency and size, MobileDiffusion has the potential to be a friendly option for mobile deployments.
Hugging Face enables custom chatbot creation in 2-clicks
Hugging Face tech lead Philipp Schmid said users can now create custom chatbots in “two clicks” using “Hugging Chat Assistant.” Users’ creations are then publicly available. Schmid compares the feature to OpenAI’s GPTs feature and adds they can use “any available open LLM, like Llama2 or Mixtral.”
Why does this matter?
Hugging Face’s Chat Assistant has democratized AI creation and simplified the process of building custom chatbots, lowering the barrier to entry. Also, open-source means more innovation, enabling a more comprehensive range of individuals and organizations to harness the power of conversational AI.
Google to release ChatGPT Plus competitor ‘Gemini Advanced’ next week
According to a leaked web text, Google might release its ChatGPT Plus competitor named “Gemini Advanced” on February 7th. This suggests a name change for the Bard chatbot after Google announced “Bard Advanced” at the end of last year. The Gemini Advanced ChatBot will be powered by the eponymous Gemini model in the Ultra 1.0 release.
According to Google, Gemini Advanced is far more capable of complex tasks like coding, logical reasoning, following nuanced instructions, and creative collaboration. Google also wants to include multimodal capabilities, coding features, and detailed data analysis. Currently, the model is optimized for English but can respond to other global languages sooner.
Why does this matter?
Google’s Gemini Advanced will be an answer for OpenAI’s ChatGPT Plus. It signals increasing competition in the AI language model market, potentially leading to improved features and services for users. The only question is whether Ultra can beat GPT-4, and if that’s the case, what counters can OpenAI do that will be interesting to see.
What Else Is Happening in AI on February 05th, 2024
NYU’s latest AI innovation echoes a toddler’s language learning journey
New York University (NYU) researchers have developed an AI system to behave like a toddler and learn a new language precisely. For this purpose, the AI model uses video recording from a child’s perspective to understand the language and its meaning, respond to new situations, and learn from new experiences. (Link)
GenAI to disrupt 200K U.S. entertainment industry jobs by 2026
CVL Economics surveyed 300 executives from six U.S. entertainment industries between Nov 17 and Dec 22, 2023, to understand the impact of Generative AI. The survey found that 203,800 jobs could get disrupted in the entertainment space by 2026. 72% of the companies surveyed are early adopters, of which 25% already use it, and 47% plan to implement it soon. (Link)
Apple CEO Tim Cook hints at major AI announcement ‘later this year’
Apple CEO Tim Cook hinted at Apple making a major AI announcement later this year during a meeting with the analysts during the first-quarter earnings showcase. He further added that there’s a massive opportunity for Apple with Gen AI and AI as they look to compete with cutting-edge AI companies like Microsoft, Google, Amazon, OpenAI, etc. (Link)
The U.S. Police Department turns to AI to review bodycam footage
Over the last decade, U.S. police departments have spent millions of dollars to equip their officers with body-worn cameras that record their daily work. However, the data collected needs to be adequately analyzed to identify patterns. Now, the department is turning to AI to examine this stockpile of footage to identify problematic officers and patterns of behavior. (Link)
Adobe to provide support for Firefly in the latest Vision Pro release
Adobe’s popular image-generating software, Firefly, is now announced for the new version of Apple Vision Pro. It now joins the company’s previously announced Lightroom photo app. People expected Adobe Lightroom to be a native Apple Vision Pro app from launch, but now it’s adding Firefly AI, the GenAI tool that produces images based on text descriptions. (Link)
Deepfake costs company $25 million
- Scammers utilized AI-generated deepfakes to impersonate a multinational company’s CFO in a video call, tricking an employee into transferring over $25 million.
- The scam involved deepfake representations of the CFO and senior executives, leading the employee to believe the request for a large money transfer was legitimate.
- Hong Kong police have encountered over 20 cases involving AI deepfakes to bypass facial recognition, emphasizing the increasing abuse of deepfake technology in fraud and identity theft. Read more.
Amazon finds $1B jackpot in its 100 million+ IPv4 address stockpile
- The scarcity of IPv4 addresses, akin to digital real estate, has led Amazon Web Services (AWS) to implement a new pricing scheme charging $0.005 per public IPv4 address per hour, opening up a significant revenue stream.
- With IPv4 addresses running out due to the limit of 4.3 billion unique IDs and increasing demand from the growth of smart devices, AWS urges a transition to IPv6 to alleviate shortage and high administrative costs.
- Amazon controls nearly 132 million IPv4 addresses, with an estimated valuation of $4.6 billion; the new pricing strategy could generate between $400 million to $1 billion annually from their use in AWS services.
Meta oversight board calls company’s deepfake rule ‘incoherent’
- The Oversight Board criticizes Meta’s current rules against faked videos as “incoherent” and urges the company to urgently revise its policy to better prevent harm from manipulated media.
- It suggests that Meta should not only focus on how manipulated content is created but should also add labels to altered videos to inform users, rather than just relying on fact-checkers.
- Meta is reviewing the Oversight Board’s recommendations and will respond publicly within 60 days, while the altered video of President Biden continues to spread on other platforms like X (formerly Twitter).
- Read more
Snap lays off 10% of workforce to ‘reduce hierarchy’
- Snapchat’s parent company, Snap, announced plans to lay off 10% of its workforce, impacting over 500 employees, as part of a restructuring effort to promote growth and reduce hierarchy.
- The layoffs will result in pre-tax charges estimated between $55 million to $75 million, primarily for severance and related costs, with the majority of these costs expected in the first quarter of 2024.
- The decision for a second wave of layoffs comes after a previous reorganization focused on reducing layers within the product team and follows a reported increase in user growth and a net loss in Q3 earnings
First UK patients receive experimental messenger RNA cancer therapy
A revolutionary new cancer treatment known as mRNA therapy has been administered to patients at Hammersmith hospital in west London. The trial has been set up to evaluate the therapy’s safety and effectiveness in treating melanoma, lung cancer and other solid tumours.
The new treatment uses genetic material known as messenger RNA – or mRNA – and works by presenting common markers from tumours to the patient’s immune system.
The aim is to help it recognise and fight cancer cells that express those markers.
“New mRNA-based cancer immunotherapies offer an avenue for recruiting the patient’s own immune system to fight their cancer,” said Dr David Pinato of Imperial College London, an investigator with the trial’s UK arm.
Pinato said this research was still in its early stages and could take years before becoming available for patients. However, the new trial was laying crucial groundwork that could help develop less toxic and more precise new anti-cancer therapies. “We desperately need these to turn the tide against cancer,” he added.
A number of cancer vaccines have recently entered clinical trials across the globe. These fall into two categories: personalised cancer immunotherapies, which rely on extracting a patient’s own genetic material from their tumours; and therapeutic cancer immunotherapies, such as the mRNA therapy newly launched in London, which are “ready made” and tailored to a particular type of cancer.
The primary aim of the new trial – known as Mobilize – is to discover if this particular type of mRNA therapy is safe and tolerated by patients with lung or skin cancers and can shrink tumours. It will be administered alone in some cases and in combination with the existing cancer drug pembrolizumab in others.
Researchers say that while the experimental therapy is still in the early stages of testing, they hope it may ultimately lead to a new treatment option for difficult-to-treat cancers, should the approach be proven to be safe and effective.
Nearly one in two people in the UK will be diagnosed with cancer in their lifetime. A range of therapies have been developed to treat patients, including chemotherapy and immune therapies.
However, cancer cells can become resistant to drugs, making tumours more difficult to treat, and scientists are keen to seek new approaches for tackling cancers.
Preclinical testing in both cell and animal models of cancer provided evidence that new mRNA therapy had an effect on the immune system and could be offered to patients in early-phase clinical trials.
AI Coding Assistant Tools in 2024 Compared
The article explores and compares most popular AI coding assistants, examining their features, benefits, and transformative impact on developers, enabling them to write better code: 10 Best AI Coding Assistant Tools in 2024
GitHub Copilot
CodiumAI
Tabnine
MutableAI
Amazon CodeWhisperer
AskCodi
Codiga
Replit
CodeT5
OpenAI Codex
Challenges for programmers
Programmers and developers face various challenges when writing code. Outlined below are several common challenges experienced by developers.
- Syntax and Language Complexity: Programming languages often have intricate syntax rules and a steep learning curve. Understanding and applying the correct syntax can be challenging, especially for beginners or when working with unfamiliar languages.
- Bugs and Errors: Debugging is an essential part of the coding process. Identifying and fixing bugs and errors can be time-consuming and mentally demanding. It requires careful analysis of code behavior, tracing variables, and understanding the flow of execution.
- Code Efficiency and Performance: Writing code that is efficient, optimized, and performs well can be a challenge. Developers must consider algorithmic complexity, memory management, and resource utilization to ensure their code runs smoothly, especially in resource-constrained environments.
- Compatibility and Integration: Integrating different components, libraries, or third-party APIs can introduce compatibility challenges. Ensuring all the pieces work seamlessly together and correctly handle data interchangeably can be complex.
- Scaling and Maintainability: As projects grow, managing and scaling code becomes more challenging. Ensuring code remains maintainable, modular, and scalable can require careful design decisions and adherence to best practices.
- Collaboration and Version Control: Coordinating efforts, managing code changes, and resolving conflicts can be significant challenges when working in teams. Ensuring proper version control and effective collaboration becomes crucial to maintain a consistent and productive workflow.
- Time and Deadline Constraints: Developers often work under tight deadlines, adding pressure to the coding process. Balancing speed and quality becomes essential, and delivering code within specified timelines can be challenging.
- Keeping Up with Technological Advancements: The technology landscape continually evolves, with new frameworks, languages, and tools emerging regularly. Continuous learning and adaptation pose ongoing challenges for developers in their professional journey.
- Documentation and Code Readability: Writing clear, concise, and well-documented code is essential for seamless collaboration and ease of future maintenance. Ensuring code readability and comprehensibility can be challenging, especially when codebases become large and complex.
- Security and Vulnerability Mitigation: Building secure software requires careful consideration of potential vulnerabilities and implementing appropriate security measures. Addressing security concerns, protecting against cyber threats, and ensuring data privacy can be challenging aspects of coding.
Now let’s see how this type of tool can help developers to avoid these challenges.
Advantages of using these tools
- Reduce Syntax and Language Complexity: These tools help programmers tackle the complexity of programming languages by providing real-time suggestions and corrections for syntax errors. It assists in identifying and rectifying common mistakes such as missing brackets, semicolons, or mismatched parentheses.
- Autocompletion and Intelligent Code Suggestions: It excels at autocompleting code snippets, saving developers time and effort. They analyze the context of the written code and provide intelligent suggestions for completing code statements, variables, method names, or function parameters.
These suggestions are contextually relevant and can significantly speed up the coding process, reduce typos, and improve code accuracy. - Error Detection and Debugging Assistance: AI Code assistants can assist in detecting and resolving errors in code. They analyze the code in real time, flagging potential errors or bugs and providing suggestions for fixing them.
By offering insights into the root causes of errors, suggesting potential solutions, or providing links to relevant documentation, these tools facilitate debugging and help programmers identify and resolve issues more efficiently. - Code Efficiency and Performance Optimization: These tools can aid programmers in optimizing their code for efficiency and performance. They can analyze code snippets and identify areas that could be improved, such as inefficient algorithms, redundant loops, or suboptimal data structures.
By suggesting code refactorings or alternative implementations, developers write more efficient code, consume fewer resources, and perform better. - Compatibility and Integration Support: This type of tool can assist by suggesting compatible libraries or APIs based on the project’s requirements. They can also help with code snippets or guide seamlessly integrating specific functionalities.
This support ensures smoother integration of different components, reducing potential compatibility issues and saving developers time and effort. - Code Refactoring and Improvement Suggestions: It can analyze existing codebases and suggest refactoring and improving code quality. They can identify sections of code that are convoluted, difficult to understand or violate best practices.
Through this, programmers enhance code maintainability, readability, and performance by suggesting more readable, modular, or optimized alternatives. - Collaboration and Version Control Management: Users can integrate with version control systems and provide conflict resolution suggestions to minimize conflicts during code merging. They can also assist in tracking changes, highlighting modifications made by different team members, and ensuring smooth collaboration within a project.
- Documentation and Code Readability Enhancement: These tools can assist in improving code documentation and readability. They can prompt developers to add comments, provide documentation templates, or suggest more precise variable and function names.
By encouraging consistent documentation practices and promoting readable code, this tool can facilitate code comprehension, maintainability, and ease of future development. - Learning and Keeping Up with Technological Advancements: These tools can act as learning companions for programmers. They can provide documentation references, code examples, or tutorials to help developers understand new programming concepts, frameworks, or libraries. So developers can stay updated with the latest technological advancements and broaden their knowledge base.
- Security and Vulnerability Mitigation: It can help programmers address security concerns by providing suggestions and best practices for secure coding. They can flag potential security vulnerabilities, such as injection attacks or sensitive data exposure, and offer guidance on mitigating them.
GitHub Copilot
GitHub Copilot, developed by GitHub in collaboration with OpenAI, aims to transform the coding experience with its advanced features and capabilities. It utilizes the potential of AI and machine learning to enhance developers’ coding efficiency, offering a variety of features to facilitate more efficient code writing.
Features:
- Integration with Popular IDEs: It integrates with popular IDEs like Visual Studio, Neovim, Visual Studio Code, and JetBrains for a smooth development experience.
- Support for multiple languages: Supports various languages such as TypeScript, Golang, Python, Ruby, etc.
- Code Suggestions and Function Generation: Provides intelligent code suggestions while developers write code, offering snippets or entire functions to expedite the coding process and improve efficiency.
- Easy Auto-complete Navigation: Cycle through multiple auto-complete suggestions with ease, allowing them to explore different options and select the most suitable suggestion for their code.
While having those features, Github Copilot includes some weaknesses that need to be considered when using it.
- Code Duplication: GitHub Copilot generates code based on patterns it has learned from various sources. This can lead to code duplication, where developers may unintentionally use similar or identical code segments in different parts of their projects.
- Inefficient code: It sometimes generates code that is incorrect or inefficient. This can be a problem, especially for inexperienced developers who may not be able to spot the errors.
- Insufficient test case generation: When writing bigger codes, developers may start to lose touch with their code. So testing the code is a must. Copilot may lack the ability to generate a sufficient number of test cases for bigger codes. This can make it more difficult to identify and debug problems and to ensure the code’s quality.
Amazon CodeWhisperer
Amazon CodeWhisperer boosts developers’ coding speed and accuracy, enabling faster and more precise code writing. Amazon’s AI technology powers it and can suggest code, complete functions, and generate documentation.
Features:
- Code suggestion: Offers code snippets, functions, and even complete classes based on the context of your code, providing relevant and contextually accurate suggestions. This aids in saving time and mitigating errors, resulting in a more efficient and reliable coding process.
- Function completion: Helps complete functions by suggesting the following line of code or by filling in the entire function body.
- Documentation generation: Generates documentation for the code, including function summaries, parameter descriptions, and return values.
- Security scanning: It scans the code to identify possible security vulnerabilities. This aids in preemptively resolving security concerns, averting potential issues.
- Language support: Available for various programming languages, including Python, JavaScript, C#, Rust, PHP, Kotlin, C, SQL, etc.
- Integration with IDEs: It can be used with JetBrains IDEs, VS Code and more.
OpenAI Codex
This tool offers quick setup, AI-driven code completion, and natural language prompting, making it easier for developers to write code efficiently and effectively while interacting with the AI using plain English instructions.
Features:
- Quick Setup: OpenAI Codex provides a user-friendly and efficient setup process, allowing developers to use the tool quickly and seamlessly.
- AI Code Completion Tool: Codex offers advanced AI-powered code completion, providing accurate and contextually relevant suggestions to expedite the coding process and improve productivity.
- Natural Language Prompting: With natural language prompting, Codex enables developers to interact with the AI more intuitively, providing instructions and receiving code suggestions based on plain English descriptions.
AI Weekly Rundown (January 27 to February 04th, 2024)
Major AI announcements from OpenAI, Google, Meta, Amazon, Apple, Adobe, Shopify, and more.
OpenAI announced new upgrades to GPT models + new features leaked
– They are releasing 2 new embedding models
– Updated GPT-3.5 Turbo with 50% cost drop
– Updated GPT-4 Turbo preview model
– Updated text moderation model
– Introducing new ways for developers to manage API keys and understand API usage
– Quietly implemented a new ‘GPT mentions’ feature to ChatGPT (no official announcement yet). The feature allows users to integrate GPTs into a conversation by tagging them with an ‘@’.Prophetic introduces Morpheus-1, world’s 1st ‘multimodal generative ultrasonic transformer’
– This innovative AI device is crafted with the purpose of delving into the intricacies of human consciousness by facilitating control over lucid dreams. Morpheus-1 operates by monitoring sleep phases and gathering dream data to enhance its AI model. It is set to be accessible to beta users in the spring of 2024.Google MobileDiffusion: AI Image generation in <1s on phones
– MobileDiffusion is Google’s new text-to-image tool tailored for smartphones. It swiftly generates top-notch images from text in under a second. With just 520 million parameters, it’s notably smaller than other models like Stable Diffusion and SDXL, making it ideal for mobile use.New paper on MultiModal LLMs introduces over 200 research cases + 20 multimodal LLMs
– This paper ‘MM-LLMs’ discusses recent advancements in MultiModal LLMs which combine language understanding with multimodal inputs or outputs. The authors provide an overview of the design and training of MM-LLMs, introduce 26 existing models, and review their performance on various benchmarks. They also share key training techniques to improve MM-LLMs and suggest future research directions.Hugging Face enables custom chatbot creation in 2-clicks
– The tech lead of Hugging Face, Philipp Schmid, revealed that users can now create their own chatbot in “two clicks” using the “Hugging Chat Assistant.” The creation made by the users will be publicly available to the rest of the community.Meta released Code Llama 70B- a new, more performant version of its LLM for code generation.
It is available under the same license as previous Code Llama models. CodeLlama-70B-Instruct achieves 67.8 on HumanEval, beating GPT-4 and Gemini Pro.Elon Musk’s Neuralink implants its brain chip in the first human
– Musk’s brain-machine interface startup, Neuralink, has successfully implanted its brain chip in a human. In a post on X, he said “promising” brain activity had been detected after the procedure and the patient was “recovering well”.Google to release ChatGPT Plus competitor ‘Gemini Advanced’ next week
– Google might release its ChatGPT Plus competitor “Gemini Advanced” on February 7th. It suggests a name change for the Bard chatbot, after Google announced “Bard Advanced” at the end of last year. The Gemini Advanced Chatbot will be powered by eponymous Gemini model in the Ultra 1.0 release.Alibaba announces Qwen-VL; beats GPT-4V and Gemini
– Alibaba’s Qwen-VL series has undergone a significant upgrade with the launch of two enhanced versions, Qwen-VL-Plus and Qwen-VL-Max.These two models perform on par with Gemini Ultra and GPT-4V in multiple text-image multimodal tasks.GenAI to disrupt 200K U.S. entertainment industry jobs by 2026
– CVL Economics surveyed 300 executives from six U.S. entertainment industries between Nov 17 and Dec 22, 2023, to understand the impact of Generative AI. The survey found that 203,800 jobs could get disrupted in the entertainment space by 2026.Apple CEO Tim Cook hints at major AI announcement ‘later this year’
– Apple CEO Tim Cook hinted at Apple making a major AI announcement later this year during a meeting with the analysts during the first-quarter earnings showcase. He further added that there’s a massive opportunity for Apple in Gen AI and AI horizon.Microsoft released its annual ‘Future of Work 2023’ report with a focus on AI
– It highlights the 2 major shifts in how work is done in the past three years, driven by remote and hybrid work technologies and the advancement of Gen AI. This year’s edition focuses on integrating LLMs into work and offers a unique perspective on areas that deserve attention.Amazon researchers have developed “Diffuse to Choose” AI tool
– It’s a new image inpainting model that combines the strengths of diffusion models and personalization-driven models, It allows customers to virtually place products from online stores into their homes to visualize fit and appearance in real-time.Cambridge researchers developed a robotic sensor reading braille 2x faster than humans
– The sensor, which incorporates AI techniques, was able to read braille at 315 words per minute with 90% accuracy. It makes it ideal for testing the development of robot hands or prosthetics with comparable sensitivity to human fingertips.Shopify boosts its commerce platform with AI enhancements
– Shopify is releasing new features for its Winter Edition rollout, including an AI-powered media editor, improved semantic search, ad targeting with AI, and more. The headline feature is Shopify Magic, which applies different AI models to assist merchants in various ways.OpenAI is building an early warning system for LLM-aided biological threat creation
– In an evaluation involving both biology experts and students, it found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not large enough to be conclusive, the finding is a starting point for continued research and community deliberation.LLaVA-1.6 released with improved reasoning, OCR, and world knowledge
– It supports higher-res inputs, more tasks, and exceeds Gemini Pro on several benchmarks. It maintains the data efficiency of LLaVA-1.5, and LLaVA-1.6-34B is trained ~1 day with 32 A100s. LLaVA-1.6 comes with base LLMs of different sizes: Mistral-7B, Vicuna-7B/13B, Hermes-Yi-34B.Google rolls out huge AI updates:
Launches an AI image generator – ImageFX- It allows users to create and edit images using a prompt-based UI. It offers an “expressive chips” feature, which provides keyword suggestions to experiment with different dimensions of image creation. Google claims to have implemented technical safeguards to prevent the tool from being used for abusive or inappropriate content.
Google has released two new AI tools for music creation: MusicFX and TextFX- MusicFX generates music based on user prompts but has limitations with stringed instruments and filters out copyrighted content. TextFX, conversely, is a suite of modules designed to aid in the lyrics-writing process, drawing inspiration from rap artist Lupe Fiasco.
Google’s Bard is now powered by the Gemini Pro globally, supporting 40+ languages- The chatbot will have improved understanding and summarizing content, reasoning, brainstorming, writing, and planning capabilities. Google has also extended support for more than 40 languages in its “Double check” feature, which evaluates if search results are similar to what Bard generates.
Google’s Bard can now generate photos using its Imagen 2 text-to-image model, catching up to its rival ChatGPT Plus- Bard’s image generation feature is free, and Google has implemented safety measures to avoid generating explicit or offensive content.
Google Maps introduces a new AI feature to help users discover new places- The feature uses LLMs to analyze over 250M locations and contributions from over 300M Local Guides. Users can search for specific recommendations, and the AI will generate suggestions based on their preferences. Its currently being rolled out in the US.
Adobe to provide support for Firefly in the latest Vision Pro release
– Adobe’s popular image-generating software, Firefly, is now announced for the new version of Apple Vision Pro. It now joins the company’s previously announced Lightroom photo app.Amazon launches an AI shopping assistant called Rufus in its mobile app
– Rufus is trained on Amazon’s product catalog and information from the web, allowing customers to chat with it to help find products, compare them, and get recommendations. The AI assistant will initially be available in beta to select US customers, with plans to expand to more users in the coming weeks.Meta plans to deploy custom in-house chips later this year to power AI initiatives
– It could help reduce the company’s dependence on Nvidia chips and control the costs associated with running AI workloads. It could potentially save hundreds of millions of dollars in annual energy costs and billions in chip purchasing costs. The chip will work in coordination with commercially available GPUs.And there was more…
– Google’s Bard surpasses GPT-4 to the Second spot on the leaderboard
– Google Cloud has partnered with Hugging Face to advance Gen AI development
– Arc Search combines a browser, search engine, and AI for unique browsing experience
– PayPal is set to launch new AI-based products
– NYU’s latest AI innovation echoes a toddler’s language learning journey
– Apple Podcasts in iOS 17.4 now offers AI transcripts for almost every podcast
– OpenAI partners with Common Sense Media to collaborate on AI guidelines
– Apple’s ‘biggest’ iOS update may bring a lot of AI to iPhones
– Shortwave email client will show AI-powered summaries automatically
– OpenAI CEO Sam Altman explores AI chip collaboration with Samsung and SK Group
– Generative AI is seen as helping to identify merger & acquisition targets
– OpenAI bringing GPTs (AI models) into conversations, Type @ and select the GPT
– Midjourney Niji V6 is out
– The U.S. Police Department turns to AI to review bodycam footage
– Yelp uses AI to provide summary reviews on its iOS app and much more
– The New York Times is creating a team to explore the use of AI in its newsroom
– Semron aims to replace chip transistors with ‘memcapacitors’
– Microsoft LASERs away LLM inaccuracies with a new method
– Mistral CEO confirms ‘leak’ of new open source model nearing GPT-4 performance
– Synthesia launches LLM-powered assistant to turn any text file into video in minutes
– Fashion forecasters are using AI to make decisions about future trends and styles
– Twin Labs automates repetitive tasks by letting AI take over your mouse cursor
– The Arc browser is incorporating AI to improve bookmarks and search results
– The Allen Institute for AI is open-sourcing its text-generating AI models
– Apple CEO Tim Cook confirmed that AI features are coming ‘later this year’
– Scientists use AI to create an early diagnostic test for ovarian cancer
– Anthropic launches ‘dark mode’ visual option for its Claude chatbot
A Daily Chronicle of AI Innovations in February 2024 – Day 03: AI Daily News – February 03rd, 2024
Google plans to launch ChatGPT Plus competitor next week
- Google is set to launch “Gemini Advanced,” a ChatGPT Plus competitor, possibly on February 7th, signaling a name change from “Bard Advanced” announced last year.
- The Gemini Advanced chatbot, powered by the Ultra 1.0 model, aims to excel in complex tasks such as coding, logical reasoning, and creative collaboration.
- Gemini Advanced, likely a paid service, aims to outperform ChatGPT by integrating with Google services for task completion and information retrieval, while also incorporating an image generator similar to DALL-E 3 and reaching GPT-4 levels with the Gemini Pro model.
- Source
Apple tested its self-driving car tech more than ever last year
- Apple significantly increased its autonomous vehicle testing in 2023, almost quadrupling its self-driving miles on California’s public roads compared to the previous year.
- The company’s testing peaked in August with 83,900 miles, although it remains behind more advanced companies like Waymo and Cruise in total miles tested.
- Apple has reportedly scaled back its ambitions for a fully autonomous vehicle, now focusing on developing automated driving-assistance features similar to those offered by other automakers.
- Source
Hugging Face launches open source AI assistant maker to rival OpenAI’s custom GPTs
- Hugging Face has launched Hugging Chat Assistants, a free, customizable AI assistant maker that rivals OpenAI’s subscription-based custom GPTs.
- The new tool allows users to choose from a variety of open source large language models (LLMs) for their AI assistants, unlike OpenAI’s reliance on proprietary models.
- An aggregator page for third-party customized Hugging Chat Assistants mimics OpenAI’s GPT Store, offering users various assistants to choose from and use.
- Source
Google’s MobileDiffusion generates AI images on mobile devices in less than a second
- Google’s MobileDiffusion enables the creation of high-quality images from text on smartphones in less than a second, leveraging a model that is significantly smaller than existing counterparts.
- It achieves this rapid and efficient text-to-image conversion through a novel architecture including a text encoder, a diffusion network, and an image decoder, producing 512 x 512-pixel images swiftly on both Android and iOS devices.
- While demonstrating a significant advance in mobile AI capabilities, Google has not yet released MobileDiffusion publicly, viewing this development as a step towards making text-to-image generation widely accessible on mobile platforms.
- Source
Meta warns investors Mark Zuckerberg’s hobbies could kill him in SEC filing
- Meta warned investors in its latest SEC filing that CEO Mark Zuckerberg’s engagement in “high-risk activities” could result in serious injury or death, impacting the company’s operations.
- The company’s 10-K filing listed combat sports, extreme sports, and recreational aviation as risky hobbies of Zuckerberg, noting his achievements in Brazilian jiu-jitsu and pursuit of a pilot’s license.
- This cautionary statement, highlighting the potential risks of Zuckerberg’s personal hobbies to Meta’s future, was newly included in the 2023 filing and is a departure from the company’s previous filings.
- Source
A Daily Chronicle of AI Innovations in February 2024 – Day 02: AI Daily News – February 02nd, 2024
Google bets big on AI with huge upgrades
1. Launches an AI image generator – ImageFX
It allows users to create and edit images using a prompt-based UI. It offers an “expressive chips” feature, which provides keyword suggestions to experiment with different dimensions of image creation. Google claims to have implemented technical safeguards to prevent the tool from being used for abusive or inappropriate content.
Additionally, images generated using ImageFX will be tagged with a digital watermark called SynthID for identification purposes. Google is also expanding the use of Imagen 2, the image model, across its products and services.
2. Google has released two new AI tools for music creation: MusicFX and TextFX
MusicFX generates music based on user prompts but has limitations with stringed instruments and filters out copyrighted content.
TextFX, conversely, is a suite of modules designed to aid in the lyrics-writing process, drawing inspiration from rap artist Lupe Fiasco.
3. Google’s Bard is now Gemini Pro-powered globally, supporting 40+ languages
The chatbot will have improved understanding and summarizing content, reasoning, brainstorming, writing, and planning capabilities. Google has also extended support for more than 40 languages in its “Double check” feature, which evaluates if search results are similar to what Bard generates.
4. Google’s Bard can now generate photos using its Imagen 2 text-to-image model
Bard’s image generation feature is free, and Google has implemented safety measures to avoid generating explicit or offensive content.
5. Google Maps introduces a new AI feature to help users discover new places
The feature uses LLMs to analyze over 250M locations and contributions from over 300M Local Guides. Users can search for specific recommendations, and the AI will generate suggestions based on their preferences. It’s currently being rolled out in the US.
(Source)

Amazon launches an AI shopping assistant for product recommendations

Amazon has launched an AI-powered shopping assistant called Rufus in its mobile app. Rufus is trained on Amazon’s product catalog and information from the web, allowing customers to chat with it to get help with finding products, comparing them, and getting recommendations.
The AI assistant will initially be available in beta to select US customers, with plans to expand to more users in the coming weeks. Customers can type or speak their questions into the chat dialog box, and Rufus will provide answers based on their training.
Why does this matter?
Rufus can save time and effort compared to traditional search and browsing. However, the quality of responses remains to be seen. For Amazon, this positions them at the forefront of leveraging AI to enhance the shopping experience. If effective, Rufus could increase customer engagement on Amazon and drive more sales. It also sets them apart from competitors.
Meta to deploy custom in-house chips to reduce dependence on costly NVIDIA
Meta plans to deploy a new version of its custom chip aimed at supporting its AI push in its data centers this year, according to an internal company document. The chip, a second generation of Meta’s in-house silicon line, could help reduce the company’s dependence on Nvidia chips and control the costs associated with running AI workloads. The chip will work in coordination with commercially available graphics processing units (GPUs).
Why does this matter?
Meta’s deployment of its own chip could potentially save hundreds of millions of dollars in annual energy costs and billions in chip purchasing costs. It also gives them more control over the core hardware for their AI systems versus relying on vendors.
AI, EO, DPA
The Biden administration plans to use the Defense Production Act to force tech companies to inform the government when they train AI models above a compute threshold.
Between the lines:
- These actions are one of the first implementations of the broad AI Executive Order passed last year. In the coming months, more provisions from the EO will come into effect.
- OpenAI and Google will likely need to disclose training details for the successors to GPT-4 and Gemini. The compute thresholds are still a pretty murky area – it’s unclear exactly when companies need to involve the government.
- And while the EO was a direct response from the executive branch, Senators on both sides of the aisle are eager to take action on AI (and Big Tech more broadly).
Elsewhere in AI regulation:
- Bipartisan senators unveil the DEFIANCE Act, which would federally criminalize deepfake porn, in the wake of Taylor Swift’s viral AI images.
- The FCC wants to officially recognize AI-generated voices as “artificial,” which would make AI-powered robocalls illegal.
- And a look at the US Copyright Office, which plans to release three very consequential reports this year on AI and copyright law.
What Else Is Happening in AI on February 02nd, 2024
The Arc browser is incorporating AI to improve bookmarks and search results
The new features in Arc for Mac and Windows include “Instant Links,” which allows users to skip search engines and directly ask the AI bot for specific links. Another feature, called Live Folders, will provide live-updating streams of data from various sources. (Link)
The Allen Institute for AI is open-sourcing its text-generating AI models
The model is OLMo, along with the dataset used to train them. These models are designed to be more “open” than others, allowing developers to use them freely for training, experimentation, and commercialization. (Link)
Apple CEO Tim Cook confirmed that AI features are coming ‘later this year’
This aligns with reports that iOS 18 could be the biggest update in the operating system’s history. Apple’s integration of AI into its software platforms, including iOS, iPadOS, and macOS, is expected to include advanced photo manipulation and word processing enhancements. This announcement suggests that Apple has ambitious plans to compete with Google and Samsung in the AI space. (Link)
Scientists use AI to create an early diagnostic test for ovarian cancer
Researchers at the Georgia Tech Integrated Cancer Research Center have developed a new test for ovarian cancer using AI and blood metabolite information. The test has shown 93% accuracy in detecting ovarian cancer in samples from the study group, outperforming existing tests. They have also developed a personalized approach to ovarian cancer diagnosis, using a patient’s individual metabolic profile to determine the probability of the disease’s presence. (Link)
Anthropic launches a new ‘dark mode’ visual option for its Claude chatbot. (Link)
Just click on the Profile > Appearance > Select Dark.
Meta’s plans to crush Google and Microsoft in AI
- Mark Zuckerberg announced Meta’s intent to aggressively enter the AI market, aiming to outpace Microsoft and Google by leveraging the vast amount of data on its platforms.
- Meta plans to make an ambitious long-term investment in AI, estimated to cost over $30 billion yearly, on top of its existing expenses.
- The company’s strategy includes building advanced AI products and services for users of Instagram and WhatsApp, focusing on achieving general intelligence (AGI).
Tim Cook says big Apple AI announcement is coming later this year
- Apple CEO Tim Cook confirmed that generative AI software features are expected to be released to customers later this year, during Apple’s quarterly earnings call.
- The upcoming generative AI features are anticipated to be part of what could be the “biggest update” in iOS history, according to Bloomberg’s Mark Gurman.
- Tim Cook emphasized Apple’s commitment to not disclose too much before the actual release but hinted at significant advancements in AI, including applications in iOS, iPadOS, and macOS.
Meta plans new in-house AI chip ‘Artemis’
- Meta is set to deploy its new AI chip “Artemis” to reduce dependence on Nvidia chips, aiming for cost savings and enhanced computing to power AI-driven experiences.
- By developing in-house AI silicon like Artemis, Meta aims to save on energy and chip costs while maintaining a competitive edge in AI technologies against rivals.
- The Artemis chip is focused on inference processes, complementing the GPUs Meta uses, with plans for a broader in-house AI silicon project to support its computational needs.
Google’s Bard gets a free AI image generator to compete with ChatGPT
- Google introduced a free image generation feature to Bard, using Imagen 2, to create images from text, offering competition to OpenAI’s multimodal chatbots like ChatGPT.
- The feature introduces a watermark for AI-generated images and implements safeguards against creating images of known people or explicit content, but it’s not available in the EU, Switzerland, and the UK.
- Bard with Gemini Pro has expanded to over 40 languages and 230 countries, and Google is also integrating Imagen 2 into its products and making it available for developers via Google Cloud Vertex AI.
Former CIA hacker sentenced to 40 years in prison
- Joshua Schulte, a former CIA software engineer, was sentenced to 40 years in prison for passing classified information to WikiLeaks, marking the most damaging disclosure of classified information in U.S. history.
- The information leaked, known as the Vault 7 release in 2017, exposed CIA’s hacking tools and methods, including techniques for spying on smartphones and converting internet-connected TVs into listening devices.
- Schulte’s actions have been described as causing exceptionally grave harm to U.S. national security by severely compromising CIA’s operational capabilities and putting both personnel and intelligence missions at risk.
A Daily Chronicle of AI Innovations in February 2024 – Day 01: AI Daily News – February 01st, 2024


Shopify boosts its commerce platform with AI enhancements

Shopify unveiled over 100 new updates to its commerce platform, with AI emerging as a key theme. The new AI-powered capabilities are aimed at helping merchants work smarter, sell more, and create better customer experiences.
The headline feature is Shopify Magic, which applies different AI models to assist merchants in various ways. This includes automatically generating product descriptions, FAQ pages, and other marketing copy. Early tests showed Magic can create SEO-optimized text in seconds versus the minutes typically required to write high-converting product blurbs.
On the marketing front, Shopify is infusing its Audiences ad targeting tool with more AI to optimize campaign performance. Its new semantic search capability better understands search intent using natural language processing.
Why does this matter?
The AI advancements could provide Shopify an edge over rivals. In addition, the new features will help merchants capitalize on the ongoing boom in online commerce and attract more customers across different channels and markets. This also reflects broader trends in retail and e-commerce, where AI is transforming everything from supply chains to customer service.
OpenAI explores how good GPT-4 is at creating bioweapons
OpenAI is developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat.
In an evaluation involving both biology experts and students, it found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not large enough to be conclusive, the finding is a starting point for continued research and community deliberation.
Why does this matter?
LLMs could accelerate the development of bioweapons or make them accessible to more people. OpenAI is working on an early warning system that could serve as a “tripwire” for potential misuse and development of biological weapons.
LLaVA-1.6: Improved reasoning, OCR, and world knowledge
LLaVA-1.6 releases with improved reasoning, OCR, and world knowledge. It even exceeds Gemini Pro on several benchmarks. Compared with LLaVA-1.5, LLaVA-1.6 has several improvements:
- Increasing the input image resolution to 4x more pixels.
- Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
- Better visual conversation for more scenarios, covering different applications. Better world knowledge and logical reasoning.
- Efficient deployment and inference with SGLang.
Along with performance improvements, LLaVA-1.6 maintains the minimalist design and data efficiency of LLaVA-1.5. The largest 34B variant finishes training in ~1 day with 32 A100s.
Why does this matter?
LLaVA-1.6 is an upgrade to LLaVA-1.5, which has a simple and efficient design and great performance akin to GPT-4V.. LLaVA-1.5 has since served as the foundation of many comprehensive studies of data, models, and capabilities of large multimodal models (LMM) and has enabled various new applications. It shows the growing open-source AI community with fast-moving and freewheeling standards.
The uncomfortable truth about AI’s impact on the workforce is playing out inside the big AI companies themselves.
The article discusses how the increasing investment in AI by tech giants like Microsoft and Google is affecting the global workforce. It highlights that these companies are slowing hiring in non-AI areas and, in some cases, cutting jobs in those divisions as they ramp up spending on AI. For example, Alphabet’s workforce decreased from over 190,000 employees in 2022 to around 182,000 at the end of 2023, with further layoffs in 2024. The article emphasizes that the integration of AI has raised concerns about job displacement and the need for a workforce strategy that integrates AI and keeps jobs through the modification of roles. It also mentions the importance of being adaptable and learning about the new wave of jobs that may emerge due to technological advances. The impact of AI on different types of jobs, including white-collar and high-paid positions, is also discussed
The article provides insights into how the adoption of AI by major tech companies is reshaping the workforce and the potential implications for job stability and creation. It underscores the need for a proactive workforce strategy to integrate AI and mitigate job displacement, emphasizing the importance of adaptability and learning to navigate the evolving job market. The discussion on the impact of AI on different types of jobs, including high-paid white-collar positions, offers a comprehensive view of the challenges and opportunities associated with AI integration in the workforce.
Cisco’s head of security thinks that we’re headed into an AI phishing nightmare
The article discusses the potential impact of AI on cybersecurity, particularly in the context of phishing attacks. Jeetu Patel, Cisco’s executive vice president and general manager of security and collaboration, expresses concerns about the increasing sophistication of phishing scams facilitated by generative AI tools. These tools can produce written work that is challenging for humans to detect, making it easier for attackers to create convincing email traps. Patel emphasizes that this trend could make it harder for individuals to distinguish between legitimate activity and malicious attacks, posing a significant challenge for cybersecurity. The article highlights the potential implications of AI advancement for cybersecurity and the need for proactive measures to address these emerging threats.
The article provides insights into the growing concern about the potential misuse of AI in the context of cybersecurity, specifically in relation to phishing attacks. It underscores the need for heightened awareness and proactive strategies to counter the increasing sophistication of AI-enabled cyber threats. The concerns raised by Cisco’s head of security shed light on the evolving nature of cybersecurity challenges in the face of advancing AI technology, emphasizing the importance of staying ahead of potential threats and vulnerabilities.
What Else Is Happening in AI on February 01st, 2024
Microsoft LASERs away LLM inaccuracies.
Microsoft Research introduces Layer-Selective Rank Reduction (or LASER). While the method seems counterintuitive, it makes models trained on large amounts of data smaller and more accurate. With LASER, researchers can “intervene” and replace one weight matrix with an approximate smaller one. (Link)
Mistral CEO confirms ‘leak’ of new open source model nearing GPT-4 performance.
A user with the handle “Miqu Dev” posted a set of files on HuggingFace that together comprised a seemingly new open-source LLM labeled “miqu-1-70b.” Mistral co-founder and CEO Arthur Mensch took to X to clarify and confirm. Some X users also shared what appeared to be its exceptionally high performance at common LLM tasks, approaching OpenAI’s GPT-4 on the EQ-Bench. (Link)
Synthesia launches LLM-powered assistant to turn any text file or link into AI video.
Synthesia launched a tool to turn text-based sources into full-fledged synthetic videos in minutes. It builds on Synthesia’s existing offerings and can work with any document or web link, making it easier for enterprise teams to create videos for internal and external use cases. (Link)
AI is helping pick what you’ll wear in two years.
Fashion forecasters are leveraging AI to make decisions about the trends and styles you’ll be scrambling to wear. A McKinsey survey found that 73% of fashion executives said GenAI will be a business priority next year. AI predicts trends by scraping social media, evaluating runway looks, analyzing search data, and generating images. (Link)
Twin Labs automates repetitive tasks by letting AI take over your mouse cursor.
Paris-based startup Twin Labs wants to build an automation product for repetitive tasks, but what’s interesting is how they’re doing it. The company relies on models like GPT-4V) to replicate what humans usually do. Twin Labs is more like a web browser. The tool can automatically load web pages, click on buttons, and enter text. (Link)
SpaceX signs deal to launch private space station Link
- Starlab Space has chosen SpaceX’s Starship megarocket to launch its large and heavy space station, Starlab, into orbit, aiming for a launch in a single flight.
- Starlab, a venture between Voyager Space and Airbus, is designed to be fully operational from a single launch without the need for space assembly, targeting a 2028 operational date.
- The space station will serve various users including space agencies, researchers, and companies, with SpaceX’s Starship being the only current launch vehicle capable of handling its size and weight.
Mistral CEO confirms ‘leak’ of new open source AI model nearing GPT-4 performance. Link
- Mistral’s CEO Arthur Mensch confirmed that an ‘over-enthusiastic employee’ from an early access customer leaked a quantized and watermarked version of an old model, hinting at Mistral’s ongoing development of a new AI model nearing GPT-4’s performance.
- The leaked model, labeled “miqu-1-70b,” was shared on HuggingFace and 4chan, attracting attention for its high performance on common language model benchmarks, leading to speculation it might be a new Mistral model.
- Despite the leak, Mensch hinted at further advancements with Mistral’s AI models, suggesting the company is close to matching or even exceeding GPT-4’s performance with upcoming versions.
OpenAI says GPT-4 poses little risk of helping create bioweapons Link
- OpenAI released a study indicating that GPT-4 poses at most slight risk in assisting in the creation of a bioweapon, according to their conducted research involving biology experts and students.
- The study, motivated by concerns highlighted in President Biden’s AI Executive Order, aimed to reassure that while GPT-4 may slightly facilitate the creation of bioweapons, the impact is not statistically significant.
- In experiments with 100 participants, GPT-4 marginally improved the ability to plan a bioweapon, with biology experts showing an 8.8% increase in plan accuracy, underscoring the need for further research on AI’s potential risks.
Microsoft, OpenAI to invest $500 million in AI robotics startup Link
- Microsoft and OpenAI are leading a funding round to invest $500 million in Figure AI, a robotics startup competing with Tesla’s Optimus.
- Figure AI, known for its commercial autonomous humanoid robot, could reach a valuation of $1.9 billion with this investment.
- The startup, which partnered with BMW for deploying its robots, aims to address labor shortages and increase productivity through automation.
An AI headband to control your dreams. Link
- Tech startup Prophetic introduced Halo, an AI-powered headband designed to induce lucid dreams, allowing wearers to control their dream experiences.
- Prophetic is seeking beta users, particularly from previous lucid dream studies, to help create a large EEG dataset to refine Halo’s effectiveness in inducing lucid dreams.
- Interested individuals can reserve the Halo headband with a $100 deposit, leading towards an estimated price of $2,000, with shipments expected in winter 2025.
Playing Doom using gut bacteria Link
- The latest, weirdest way to play Doom involves using genetically modified E. coli bacteria, as explored in a paper by MIT’s Media Lab PhD student Lauren “Ren” Ramlan.
- Ramlan’s method doesn’t turn E. coli into a computer but uses the bacteria’s ability to fluoresce as pixels on an organic screen to display Doom screenshots.
- Although innovative, the process is impractical for gameplay, with the organic display managing only 2.5 frames in 24 hours, amounting to a game speed of 0.00003 FPS.
How to generate a PowerPoint in seconds with Copilot
- ChatGPT Plus Customers Are Being Screwed Over by Secret Updates — Here's What’s Really Happeningby /u/Emotional-Basis-8564 (Artificial Intelligence) on April 28, 2025 at 6:49 am
I’m a paying ChatGPT Plus user ($20/month) who has been using the system consistently and heavily for months. Today, I caught something major that OpenAI doesn’t seem to want users to notice. In the last 3–5 days (especially today, April 27, 2025), OpenAI has quietly pushed updates that are massively degrading the ChatGPT user experience — especially for Plus members. Here’s what’s happening: Forced Session Expiry: If you stop typing or interacting for even a few minutes, the session immediately expires. You’re forced to start a new chat even if you never closed the app. Hard Limits on Number of Messages: After about 20–30 messages back and forth, even during active conversations, ChatGPT now forcibly ends the session with no warning ("too many responses in this chat"). This used to happen only after hundreds of messages. Shorter Maximum Chat Size: Long conversations are now cut off way earlier — even if you’re staying active. There’s now an invisible "size" limit based on total words, not just time. Silent Wiping of Conversation Drafts: If the chat resets or you close the app, anything you were working on disappears permanently unless manually saved to "Memory" ahead of time. There is no longer a safe auto-recovery. Broken Continuity for Deep Users: If you were working on large projects, personal writing, or emotional timelines over days/weeks? Forget it. The system no longer supports carrying over deep, connected conversations easily. No Transparency or Warning: OpenAI made these changes without notifying Plus users. No changelog. No heads-up. Nothing. The end result? Users who rely on ChatGPT for serious work, personal continuity, disability support, mental health tracking, memory aid, or longform projects are being actively harmed. Paying customers are being treated like casual, free-tier users who are expected to "chat quickly and leave." Conversations are now treated like disposable TikTok videos — not meaningful interactions. This isn’t a technical glitch. This is a deliberate policy shift to prioritize server load and quick responses over real conversation quality — and they didn’t think we would notice. Well, we noticed. And it’s not acceptable. I’m posting this because other users deserve to know what's happening behind the scenes. If you’re seeing more forced resets, shorter chats, lost continuity, and broken sessions — you’re not crazy. It’s real. We deserve answers. We deserve respect. And we deserve the service we are paying for. chatgpt #chatgptplus #openai #aiethics #customerexperience submitted by /u/Emotional-Basis-8564 [link] [comments]
- Nobody talks about how AI is about to make "learning how to learn" the most important skillby /u/elektrikpann (Artificial Intelligence) on April 28, 2025 at 5:40 am
Everyone is jumping on the AI bandwagon to enhance their learning, but are we truly mastering the art of learning itself, or are we just becoming overly reliant on AI? With new AI models and workflows emerging every week, the real advantage lies not in memorizing information but in our ability to adapt and evolve as the landscape shifts. In this fast-paced environment, those who can quickly relearn, pivot, and experiment will thrive, while those who simply accumulate knowledge may find themselves left behind. Adaptability is now more valuable than raw intelligence, and that gap is only widening. Are we really learning, or just leaning on AI? submitted by /u/elektrikpann [link] [comments]
- Are you typing?by /u/0__O0--O0_0 (Artificial Intelligence) on April 28, 2025 at 5:01 am
I see a lot of posts of people saying they’re getting caught up in conversations with ai. I’m just curious if you are typing or using voice speech software? Is it worth it? submitted by /u/0__O0--O0_0 [link] [comments]
- What do you guys predict the future of movies and tv series will look like with generative ai?by /u/Elbess91 (Artificial Intelligence) on April 28, 2025 at 4:07 am
With the advancement of generative ai I can see a future where anybody or atleast talented writers and other kind of creatives can become creators of amazing motion pictures. I could also imagine big box producers and already popular series making their IP available for a fee so that people can create their own episodes or sequels and prequels. Maybe we would even be able to buy scripts of some website created by random users and use that to create our own movies or settings or actors. Celebrities as we know them today will vanish and the new celebrities will be the creators. Maybe Amazon will have a service like KDP but instead of people self publishing books they can self publish movies and series to make money with it. Cable networks will try to adapt but the sheer quantity of creatives will swallow them. I see it as not just an upcoming revolution of the motion picture industry but also a liberation where creativity will not be bound by set rules. Let me know what you guys think.. submitted by /u/Elbess91 [link] [comments]
- One-Minute Daily AI News 4/27/2025by /u/Excellent-Target-847 (Artificial Intelligence) on April 28, 2025 at 4:00 am
China’s Huawei develops new AI chip, seeking to match Nvidia, WSJ reports.[1] ChatGPT Made Me an AI Action Figure, Then 3D Printing Did This.[2] Malaysia temple unveils first ‘AI Mazu’ for devotees to interact with, address concerns.[3] Google DeepMind CEO Demis Hassabis on AI in the Military and What AGI Could Mean for Humanity.[4] Sources included at: https://bushaicave.com/2025/04/27/one-minute-daily-ai-news-4-27-2025/ submitted by /u/Excellent-Target-847 [link] [comments]
- Integrating yourself with AI... Literally.by /u/FlyingN00dles (Artificial Intelligence) on April 28, 2025 at 12:25 am
I'm trying to see if anyone else is also working on personal AI projects using open AI. Specifically, if anyone has built their own AI chatbots that they are integrating with their own thoughts/ memories/ feelings so it can be a digital copy of yourself. I have started working on this project but would love to connect with anyone else that may be doing the same thing. submitted by /u/FlyingN00dles [link] [comments]
- What is your go-to response when someone criticizes everything about AI?by /u/StaticSand (Artificial Intelligence) on April 27, 2025 at 11:41 pm
When you encounter people who are extremely critical of AI (not just specific applications, but AI in general), how do you usually respond? I'm not talking about thoughtful skepticism or debates over particular use cases. I mean the people who are convinced that all AI is inherently bad, dangerous, useless, or unethical no matter what. Do you try to engage with them? Do you offer examples of positive use cases? Do you just let it go? Would love to hear how others handle it, especially since opinions about AI seem to be getting more polarized lately. submitted by /u/StaticSand [link] [comments]
- Good readby /u/Electrical_Ad4120 (Artificial Intelligence) on April 27, 2025 at 10:34 pm
https://arxiv.org/abs/2504.01990 The above link is to an interesting paper that explains the current state of affairs in LLM’s in plain approachable terms, the challenges ahead and what “could be”. submitted by /u/Electrical_Ad4120 [link] [comments]
- Exploring MIT's Periodic Table of Machine Learning and the Promise of High-Dimensional AI Discoveryby /u/CreativeEnergy3900 (Artificial Intelligence) on April 27, 2025 at 10:32 pm
MIT researchers recently proposed a periodic table to organize machine learning algorithms. I explored how this framework could open new opportunities by pushing beyond the 2D structure — into high-dimensional manifolds where more complex AI relationships form. I also added mathematical insights and a Python clustering demonstration comparing K-Means vs GMM. Thought this community might find it interesting: https://itechguide.com/mit-periodic-table-of-machine-learning/ Curious if others here have thoughts about using high-dimensional representations for unsupervised learning? submitted by /u/CreativeEnergy3900 [link] [comments]
- Is reddit data being used to train AI?by /u/Resident-Stage-3759 (Artificial Intelligence) on April 27, 2025 at 9:13 pm
I’ve been noticing more discussion lately on Reddit about AI, especially about the new Answers beta section. Also people accusing users of being bots or AI, and some mentioning AI training. I recently came across a post on r/singularity talking about how the new ChatGPT-4o has been “talking weird,” and saw a comment mentioning reddit data. Now, I know there’s always ongoing debate about the potential of AI can become autonomous, self-aware, or conscious in the future. We do have some understanding of consciousness thanks to psychologists,philosophers and scientists but even then, we can’t actually even prove that humans are conscious. Meaning, we don’t fully understand consciousness itself. That had me thinking: Reddit is one of the biggest platforms for real human reviews, conversations, and interactions; that’s part of why it’s so popular. What if AI is being trained more on Reddit data? Right now, AI can understand language and hold conversations based mainly on probability patterns i think, follow the right grammar and sentence structure, and conversate objectively. But what if, by training on Reddit data, it is able to emulate more human like responses with potential to mimic real emotion? It gets a better understanding of human interactions just as more data is given to it. Whether true consciousness is possible for AI is still up for debate, but this feels like a step closer to creating something that could replicate a human. And if something becomes a good enough replica… maybe it could even be argued that it’s conscious in some sense. I might be wrong tho, this was just a thought I had. Feel free to correct/criticize edit: Something i’ve noticed is also many users on platforms not just on reddit but also linkedin too using emojis or adding random text to make it undetectable for ai or disrupt the data collection process by ai. submitted by /u/Resident-Stage-3759 [link] [comments]
How to use Google Search and ChatGPT side be side?


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How to use Google Search and ChatGPT side by side?
Google and ChatGPT are two powerful tools for searching the internet, but Google can provide you with a much larger variety of results. To get the best of both worlds, try using Google Search and ChatGPT side by side:
- First, download the Google Chrome or Firefox browser extension;
- then open Google in one tab and ChatGPT in another. This way, you can quickly compare results from Google with those provided by ChatGPT. It’s a sure-fire way to get the kind of search results that perfectly fit your needs!
- If Google Chrome is not available on your device, don’t worry – simply install the Opera browser extension to get Google Search and ChatGPT working together even more smoothly.

Google Search and ChatGPT can work side by side. Google Search can be used to find specific information on the internet, while ChatGPT can be used to understand and generate human-like text. They can be integrated together in various ways, such as providing answers to user queries by combining information found through Google Search with the language generation capabilities of ChatGPT. It could be used to provide more accurate, complete and human-like answers to the user.
Use a browser extension to display ChatGPT response alongside search engine results

Prerequisite:
1- You have Google chrome or Firefox browser
2- You have a valid ChatGPT account at https://chat.openai.com/
To use ChatGPT and Google Search on the same page:
Add ChatGPT extension to Google Chrome browser from this link
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Install from Mozilla Add-on Store

How to make it work in Opera

Enable “Allow access to search page results” in the extension management page
Google Search and ChatGPT are an unbeatable duo when it comes to finding information. Google is the world’s foremost web search engine, whereas ChatGPT has current, informative content from intelligent chatbots. Together they make a great combination for research and education purposes. Google can be used through Chrome, Firefox, or Opera browsers – all you need is a Google account and the browser extension. Once installed in your chosen browser, you can find out about anything via Google Search and speak with ChatGPT for even more details! Google and ChatGPT are constantly updating their content, making them up-to-date sources of knowledge so you can stay ahead of the game. Why not pair up Google Search and ChatGPT today?
Reference:
1- https://github.com/wong2/chat-gpt-google-extension
2- How can I add ChatGPT to my website
Optimizing Your Blog for Google’s 2023 Algorithm Update


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Optimizing Your Blog for Google’s 2023 Algorithm
Google’s Ranking Factors
Google uses hundreds of different factors to determine where a page appears in its SERPs (Search Engine Result Pages). These factors range from user experience metrics such as page speed and mobile-friendliness, to content quality indicators such as topic relevance and keyword usage. In order to optimize your blog for the 2023 algorithm update, you must consider all of these ranking factors when structuring your blog posts.

Content Quality
Content quality is one of the most important ranking factors in any given algorithm update. Google wants to ensure that searchers find relevant, accurate information when they perform a query – so it’s important that you create content with this goal in mind. When crafting blog posts, focus on providing useful information instead of just “filler” content; this will help you rank higher in Google’s search results. Additionally, make sure that you use keywords throughout your post; doing so will make it easier for Google to identify what the content is about and rank it accordingly.
User Experience Metrics
Google also takes user experience metrics into account when determining rankings. This means that if your website takes too long to load or isn’t mobile-friendly, then it won’t rank as highly as other pages with better user experience metrics. Make sure that your website is optimized for both desktop and mobile devices; this will improve page load times and make it easier for readers to access your content on their preferred device. Additionally, utilize caching techniques to reduce server response time and ensure that visitors have a pleasant browsing experience on your site.
Research Before Writing
No matter what kind of content you’re creating, research is key. Before writing a blog post, make sure that you have done thorough research on the topic and its related keywords. This will help you create content that is relevant and accurate. Additionally, it’s important to do regular keyword audits and track how often certain terms are being used in order to ensure that your content remains up-to-date with current trends.
Optimize Your Content
It’s not enough just to write great content; you also need to make sure that it’s properly optimized for search engines like Google. That means using appropriate keywords in key places (title tags, meta descriptions, headings) and making sure that all of your content is well-structured and easy-to-read. Additionally, optimizing images and videos will help your website load faster which can improve user experience—something Google values highly when ranking websites.
Stay Updated on SEO Best Practices
Google regularly updates their algorithms in order to deliver better search results for users—which means SEO best practices are constantly changing as well. To stay ahead of the curve and ensure that your blog remains visible online, pay close attention to any changes or updates in SEO best practices for 2023. Read industry blogs and newsletters or talk with experts about what techniques might be most effective this year. By staying informed about these changes, you can make sure that your blog remains compliant with Google’s algorithm throughout the year.
How to structure a blog to be compliant with Google latest search algorithm in 2023?
To structure a blog that is compliant with Google’s latest search algorithm, you should focus on the following:
- Use keywords in your content that are relevant to your topic and are commonly searched by your target audience.
- Optimize your blog’s title, meta description, and headings (H1, H2, etc.) to include your keywords and provide a clear and concise summary of your content.
- Use internal linking to connect your blog post to other relevant content on your website, and external linking to credible sources to show that your content is well-researched.
- Use images and videos to break up text and make your content more visually appealing. Be sure to optimize them with descriptive file names and alt tags that include keywords.
- Optimize your website for mobile devices and ensure it loads quickly.
- Use structured data markups to help search engines understand what your content is about and how to display it in search results.
- Make sure your blog is easy to navigate and has a clear hierarchy of information.
- Publish high-quality, original content on a regular basis.
- Use Google Search Console to submit your sitemap and monitor your website’s performance on Google search.
- Keep an eye on Google’s webmaster guidelines and updates to their algorithm to stay compliant and improve your website’s visibility on search engine.
What techniques do reliable SEO agencies use to improve organic rankings on Google?
Reliable SEO agencies use a variety of techniques to improve organic rankings on Google. Some of the most common techniques include:
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- Keyword research: Identifying the most relevant and profitable keywords for a business and incorporating them into the website’s content, meta tags, and URLs.
- On-page optimization: Optimizing the website’s content and structure to make it more search engine friendly. This includes things like header tags, meta descriptions, and alt tags.
- Content creation: Creating high-quality, relevant, and engaging content that provides value to users and helps to establish the website as an authority in its industry.
- Link building: Acquiring backlinks from other websites that point to the website. These backlinks help to improve the website’s visibility and search engine rankings.
- Technical SEO: Ensuring that the website’s technical infrastructure is optimized for search engines. This includes things like site speed, mobile-friendliness, and crawlability.
- Local SEO: Optimizing the website for local search results, by including location-specific keywords and information, and claiming and verifying business listings on local directories.
- Analytics and Reporting: Analysing website data and user behavior to track progress, identify areas for improvement and report the results to the client.
- Continuous Optimization: Continuously monitoring and optimizing the website to keep up with the latest search engine algorithms and industry trends.
Please note that SEO is a complex and dynamic field, and these techniques are not exhaustive. Additionally, SEO agencies that rely on manipulative techniques such as buying backlinks or using hidden text, can get their clients penalized by Google.
In what ways have Google’s algorithm updates impacted organic SEO strategies over time?
Google’s algorithm updates have had a significant impact on organic SEO strategies over time. Some of the key ways that these updates have affected SEO include:
- Prioritizing mobile-friendly websites: With the increase in mobile usage, Google has placed a greater emphasis on websites that are optimized for mobile devices. This means that if a website is not mobile-friendly, it may be penalized in search rankings.
- Focusing on quality content: Google’s algorithm updates have placed a greater emphasis on high-quality, relevant, and unique content. Websites with thin or low-quality content may be penalized in search rankings.
- Valuing backlinks: Backlinks, or links from other websites to a particular website, have traditionally been a key factor in determining a website’s search ranking. However, Google’s algorithm updates have placed more emphasis on the quality of backlinks, rather than the quantity.
- Using secure connections: Google has also begun to favor websites that use secure connections (HTTPS) over those that use unsecured connections (HTTP).
- Using structured data (schema markups) : Google has been using structured data (schema markups) to understand the context of the webpage and to show rich snippets in SERPs.
It is important to note that Google’s algorithm updates are ongoing, and SEO strategies will need to adapt to these changes in order to be successful.
How has Google’s latest algorithmic updates changed the landscape of SEO best practices?
Google’s latest algorithmic updates have shifted the focus of SEO best practices towards creating a more user-centric experience. Some of the ways in which these updates have changed the landscape of SEO include:
- Prioritizing user experience: Google’s algorithm updates have placed greater emphasis on factors that contribute to a positive user experience, such as website speed, mobile-friendliness, and accessibility. This means that websites that provide a good user experience are likely to rank higher in search results.
- Focusing on quality content: Google’s updates have also emphasized the importance of high-quality, relevant, and unique content. Websites with thin or low-quality content may be penalized in search rankings.
- Valuing natural language and user intent: Google’s updates have also placed more emphasis on natural language and user intent. This means that content that is written in a way that is easy to understand, and that is tailored to the specific needs and interests of the user, is more likely to rank well.
- Emphasizing the importance of technical SEO: Google’s updates have also made it more important than ever to ensure that your website is technically sound. This includes things like using structured data, optimizing page speed, and making sure your website is mobile-friendly.
- Focusing on local SEO: Google’s updates have also placed more emphasis on local SEO. This means that businesses that want to rank well in local search results need to ensure that they have accurate and up-to-date information on their Google My Business listing and that they have a strong presence on local review sites.
It is important to note that Google’s algorithm updates are ongoing and SEO best practices are also evolving constantly, so keeping up with the latest trends and changes is crucial for SEO success.
How does Google Panda update affect on-page content and how could it be optimized for better performance?
Google’s Panda update is a algorithm that was first released in 2011 and is designed to lower the rank of low-quality or “thin” websites while promoting high-quality content. It particularly looks at the quality of the on-page content, and the user engagement metrics.
To optimize for better performance with Panda, your on-page content should:
- Be high-quality, informative, and useful for the user
- Be original and not duplicated from other sources
- Be well-written and free of grammatical errors
- Include keywords that are relevant to the topic of the page
- Provide a good user experience, with a clear and easy-to-use layout
- Be of sufficient length, with at least 300 words of content per page
- Be regularly updated with fresh, relevant content
- Have engagement signals like comments, social shares and time spent on site.
Additionally, you should avoid:
- Creating content that is thin or low-quality
- Duplicating content from other websites
- Using keyword stuffing tactics
- Creating pages with little or no content
- Creating pages with a lot of ads and not enough content
- Creating pages with a lot of low-quality user-generated content
By following these guidelines, you can help ensure that your website is providing high-quality content that will be well-received by both users and the Panda algorithm.
How can A/B testing be effectively used to improve content’s performance on a SERP (Search Engine Results Page)?
A/B testing, also known as split testing, is a method of comparing two versions of a webpage or other content to see which one performs better. It can be effectively used to improve content’s performance on a search engine results page (SERP) by allowing you to make data-driven decisions about how to optimize your content for better visibility and engagement.
Here are a few ways you can use A/B testing to improve your content’s performance on SERP:
- Test different headlines: A/B test different headlines for your content to see which one is more likely to attract clicks from users.
- Test different meta descriptions: A/B test different meta descriptions to see which one is more likely to be clicked on by users.
- Test different content layouts: A/B test different layouts for your content to see which one is more likely to be engaged with by users.
- Test different images and videos: A/B test different images and videos to see which one is more likely to be engaged with by users.
- Test different calls to action: A/B test different calls to action to see which one is more likely to be clicked on by users.
- Test different keywords: A/B test different keywords to see which one is more likely to be clicked on by users.
It’s important to note that A/B testing should be used as part of a comprehensive optimization strategy, not as a standalone method. Also, it’s essential to have a significant amount of data to make a decision and make sure to test one variable at a time to ensure the results are meaningful.
By using A/B testing to optimize your content, you can make data-driven decisions about how to improve your content’s visibility and engagement on SERP.
What is trending in January 2023?


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What is trending in January 2023?
What’s trending in January 2023?
Google Trend has the answer! Every month, millions of people turn to Google search to find out what everyone is talking about. According to Google Trend insights, January 2023 is all about the latest metamorphic technology and virtual entertainment. People are searching for new ways to stay connected with friends, work from home, and so much more. It’s quite remarkable how far we have come since the start of the century; even now, innovation continues unabated and shows no sign of stopping anytime soon!
Top Trends January 31th, 2023
The unemployment rate across the US and the EU in January 2023. The US average unemployment rate is 3.5%. The EU average unemployment rate is 6.1% 🇺🇸🇪🇺

What is the retirement age in Europe: Generally between 65 and 67.
What is the Retirement age in America: Generally 67.
What is the Retirement age in Texas: 67.
What is the Retirement age in France: 62.
What is the Retirement age in California: 67.
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Is $1.5 million enough to retire at 62? It depends on various factors such as your expected lifestyle, healthcare costs, inflation, and taxes. A general rule of thumb is to have savings equivalent to 80% of your pre-retirement income, which in this case would be around $60,000 per year. $1.5 million can provide this amount with a 4% withdrawal rate, but this may not be sufficient for everyone.
How much will I get a month if I retire at 62? The amount you will receive per month will depend on how you choose to receive your retirement benefits, such as through Social Security or through withdrawals from a savings account.
How much can I earn if I retire at 62 in 2023? Again, the amount you can earn in retirement will depend on various factors, including Social Security benefits, pension plans, and personal savings.
Why retire at 62? Retiring at 62 may be appealing to some people as it allows them to leave the workforce earlier and potentially enjoy a longer retirement. It is important to consider factors such as your financial situation, healthcare needs, and life expectancy before making a decision to retire.
How much is needed to retire at 62? The amount needed to retire at 62 depends on various factors such as lifestyle, healthcare costs, inflation, and taxes. A general rule of thumb is to have savings equivalent to 80% of your pre-retirement income. It is recommended to speak to a financial advisor for a personalized plan.
How old is Patrick Mahomes? Patrick Mahomes was born on September 17, 1995, so as of 2023 he is 27 years old.
How tall is Patrick Mahomes? Patrick Mahomes is 6 feet 3 inches tall.
Where is Patrick Mahomes from? Patrick Mahomes was born in Tyler, Texas, USA.
How many super bowls has Patrick Mahomes won? Patrick Mahomes has won 1 Super Bowl, Super Bowl LIV in 2020.
What nationality is Patrick Mahomes? Patrick Mahomes is American.
Where did Jalen Hurts go to high school? Jalen Hurts went to Channelview High School in Channelview, Texas.
When did Jalen Hurts get drafted? Jalen Hurts was drafted by the Philadelphia Eagles in the second round (53rd overall) of the 2020 NFL Draft.
Where is Jalen Hurts from? Jalen Hurts is from Houston, Texas, USA.
What ethnicity is Jalen Hurts? Jalen Hurts is African American.
Top Trends January 30th, 2023
Serbian tennis player, Novak Djokovic is a top trending person, spiking +450%, in the world over the past day as he won the 2023 Australian Open men’s singles.
After American actress Annie Wersching passed away on Sunday, she became a top trending person in the US over the past day. “annie wersching cancer type” is a top related search.
In the US, all of the other top ten trending topics are related to the NFL over the past day. San Francisco 49ers quarterback Brock Purdy spiked +950% in the same time period.
Jill Biden became a top trending person in the US as she appeared at the NFC Championship Eagles-49ers game on Sunday.
“school closings” spiked +2,200% over the past day in the US. The top state searching for this is Missouri, followed by Oklahoma and Michigan.
“pakistan mosque bombing” is a global top trending topic related to Pakistan over the past day.
Top searches with Tyre Nichols, past day, US
Tyre Nichols body cam footage: https://www.youtube.com/watch?v=SlbdY9H-xTc
Top trending questions about police reform, past week, worldwide
What would police reform look like? Police reform refers to changes and improvements made to the policies, training, and practices of law enforcement agencies with the aim of improving the relationship between the police and the communities they serve, increasing accountability and transparency, and reducing police violence.
How to support police reform?
There are several ways to support police reform. You can get involved in local advocacy groups, write to your elected officials, support organizations that promote reform, attend public meetings and protests, and educate yourself and others on the issues.
Why won’t police reform work? There are several reasons why police reform may not work, including resistance from law enforcement agencies, lack of political will, limited funding, and difficulty in implementing changes. Reform also requires buy-in and commitment from all stakeholders, including police departments, elected officials, and the public.
What is police reform? Police reform refers to the changes that are made to the way law enforcement agencies operate to improve their behavior and accountability towards the public. The aim of reform is to address issues of police misconduct, brutality, and discrimination and to improve relationships between law enforcement and the communities they serve.
What states have police reform? Several states have implemented police reform measures in recent years, including California, Colorado, Illinois, Massachusetts, Minnesota, New York, and others. The specifics of these reforms vary by state, but common reforms include changes to the use of force policies, hiring practices, and training programs.
Top trends January 29th, 2023
Top Trends January 27th, 2023
“memphis police officer charged” was a breakout search in the US in the past day, after five officers were charged with the murder of Tyre Nicolas.
“kobe bryant” was a breakout search in the past day, Worldwide, after the third anniversary of his tragic death along with his daughter Gianna Bryant.
“teen wolf” was a breakout search in the past day Worldwide after the movie spinoff was released today. Jamaica is the top country searching for “teen wolf the movie”
“colon cancer” is a breakout search in the past day, Worldwide, after TikTok star Randy Gonzalez, 35, passes away from the disease. This news also comes amid studies that colorectal cancer rates are rising amongst younger people.
Searches for “when to check for colon cancer” and “what causes colon cancer in males” were up +200% in the past 7 days, Worldwide
Palestine Israel
“Jenin refugee camp” was a breakout search in the past day, Worldwide.
Searches for “israel palestine conflict explained” increased 200% in the past day, Worldwide
“Why do israel and palestine fight”was a breakout search in the past day, Worldwide
Ireland is the top country searching for “Jenin refugee camp” in the past 7 days
Top questions on Jenin, Palestine in the past day, Worldwide
Where is Jenin? Palestinian city in the northern West Bank. It serves as the administrative center of the Jenin Governorate of the State of Palestine and is a major center for the surrounding towns.
Is Jenin in Israel? No
How to pronounce Jenin? (/dʒəˈniːn/; Arabic:
جنين (help·info)
Is Jenin Safe? Jenin is a city in the West Bank and the level of safety in the area can be influenced by the ongoing political and security situation in the region. It’s best to check current travel warnings and advice from local authorities and international organizations before traveling to Jenin or any other city in the West Bank. Additionally, it’s always recommended to exercise caution and be aware of your surroundings when traveling to any location
Is Jenin in the West Bank? Jenin is a city located in the northern part of the West Bank, in the Palestinian territories.
Rent and Housing
“rent burdened definition” is a breakout search in the US, past 7 days after Moody’s Analytics found that renters in the US now pay more than 30% of their median income for rent
Searches for “housing market recession” increased 600% in the past 7 days, US
Searches for “when will the housing market crash” increased +150%, past 7 days, US
Florida is the top state searching for Rent, 2004 – present
Top questions on affording rent, past day US
How much rent can I afford? The amount of rent you can afford depends on several factors such as your monthly income, credit score, employment history, and other debts and expenses you may have. A general rule of thumb is that your monthly housing expenses should not exceed 30% of your gross monthly income. This means that if you make $3,000 per month, you should aim to spend no more than $900 on rent and utilities. However, this is just a guideline and you should consider your individual financial situation and needs when determining how much you can afford to spend on rent.
How much mortgage can I afford? The amount of mortgage you can afford depends on several factors, including your income, monthly debts, credit score, and down payment. A general rule of thumb is to spend no more than 28% of your gross monthly income on housing expenses, including mortgage payments, insurance, and property taxes. However, the best way to determine how much mortgage you can afford is to speak with a lender and get pre-approved for a loan. They will take into account your specific financial situation and provide you with a more accurate estimate.
How much rent can I afford on 40k salary? The amount of rent you can afford on a 40k salary can vary based on several factors, such as the cost of living in your area, your monthly expenses, and your desired level of savings. Generally, it’s recommended to spend no more than 30% of your gross monthly income on housing. For a 40k salary, that would be $1,000-$1,200 per month for rent. However, it’s important to take into account other expenses such as utilities, groceries, transportation, and insurance to determine the most realistic amount you can afford for rent. It may also be helpful to have a savings cushion for emergencies and unexpected expenses.
How much rent can I afford making 18k? As a general rule of thumb, it is recommended to spend no more than 30% of your monthly income on housing expenses, including rent, utilities, and any other housing-related expenses.
Based on this rule, if you earn $18,000 per year, your monthly income would be $1,500. Therefore, you could afford to spend about $450 per month on rent.
Keep in mind that this is a general guideline, and other factors, such as your location, the cost of living, and your personal financial situation, can affect how much rent you can afford. It is always advisable to also consider your monthly expenses, such as food, transportation, and other bills, when determining your budget for housing expenses.
How to calculate how much rent you can afford? To calculate how much rent you can afford, follow these steps:
Determine your monthly net income: Subtract your monthly expenses from your monthly income, including taxes, insurance, and other deductions.
Calculate your debt-to-income ratio (DTI): Divide your monthly debt payments by your monthly net income. A general guideline is to keep your DTI under 40%.
Consider other expenses: Don’t forget to factor in utilities, transportation costs, and other monthly expenses when determining how much rent you can afford.
Set a budget: Based on your DTI and monthly expenses, set a budget for your monthly rent payment. A good rule of thumb is to spend no more than 30% of your monthly net income on housing.
Adjust as needed: If your rent budget is higher than what you can afford, consider finding a roommate, reducing your other expenses, or finding a less expensive housing option.
Top Trends January 26th, 2023
“was there an earthquake in los angeles today” was a breakout search in California in the past day
“imdb pathaan rating” was a breakout search worldwide in the past day after the film premiered January 25
“what does it mean to sell music catalog“ was a breakout search in the past day in the US when Justin Bieber sold his music catalog to an investment company
Bond girl was a breakout search in the US in the past day related to the Academy Award-nominated actress Michelle Yeoh. Yeoh is the first Malaysian actress to receive a nomination for the Academy Award for Best Actress for her role in Everything Everywhere All at Once.
“tiktok mascara meaning” was a breakout search in the past day in the US related to the popular TikTok hashtag
“goldman sachs housing market crash” was a breakout search worldwide in the past day
Ukraine
“how many tanks is ukraine getting” spiked +4,350% and was a top trending search related to Ukraine in the US in the past day
“how much does an abrams tank cost” was a breakout search in the past day in the US after President Biden announced he will be sending the Ukrainian army the tanks. M88 Recovery Vehicle was also a breakout search yesterday in the US as they are included in the White House’s Ukraine package.
“how many leopard tanks does germany have” and “how many abrams tanks does the us have” were breakout searches in the past day in the US after Germany also agreed to send armored vehicles to Ukraine
Top questions about Ukraine, past day, US:
When did Russia invade Ukraine? On 24 February 2022, Russia invaded Ukraine in a major escalation of the Russo-Ukrainian War, which began in 2014. The invasion has caused tens of thousands of deaths on both sides and Europe’s largest refugee crisis since World War II.
Why did Russia invade Ukraine? On 24 February 2022, Russia launched a military invasion of Ukraine in a steep escalation of the Russo-Ukrainian War. The campaign had been preceded by a Russian military buildup since early 2021 and numerous Russian demands for security measures and legal prohibitions against Ukraine joining NATO.
Is Ukraine winning the war?
Guns in California
“half moon bay” and “mushroom farm” were breakout searches in California this past week in the aftermath of the mass shooting that took place at a mushroom farm in the city of Half Moon Bay, CA
“gun reform meaning” was a breakout search in California in the last 7 days after multiple mass shootings occurred in the state in the past week.
“ronald reagan gun laws” was a breakout search in the past day in the United States. The 1967 Mulford Act was signed into effect by then-Governor Ronald Reagan and prohibited the public carrying of loaded firearms without a permit.
Top questions on Gun control, past week, California
What state has the strictest gun laws? California has some of the strictest gun laws in the United States. These laws include a ban on assault weapons, a 10-day waiting period for firearm purchases, and a requirement for background checks for all firearms sales and transfers.
What are the gun laws in California 2022? California has some of the strictest gun laws in the United States. In 2022, California’s gun laws include: -A waiting period of 10 days for all firearm purchases -A ban on assault weapons -A requirement for all firearm transactions to go through a licensed dealer -A requirement for background checks for all firearm purchases -A requirement for all firearm owners to have a Firearm Safety Certificate -Restrictions on the possession of large capacity ammunition magazines -A “red flag” law that allows for the temporary removal of firearms from individuals deemed to be a danger to themselves or others -A process to remove firearms from individuals convicted of certain crimes or placed under certain restraining orders -A process for voluntarily surrendering firearms to law enforcement agencies.
When was the constitution written? The United States Constitution was written in 1787.
What is gun control? Gun reform refers to changes or adjustments to laws and regulations related to the possession, sale, and use of firearms. This can include measures such as background checks, waiting periods, and limits on certain types of weapons or accessories. The goal of gun reform is to reduce the incidence of gun violence and improve public safety.
What is gun reform? Gun reform refers to changes or proposed changes to laws and regulations related to firearms and their ownership. This can include measures such as background checks, waiting periods, limits on certain types of weapons or accessories, and increased penalties for crimes committed with firearms. The goal of gun reform is generally to reduce the number of deaths and injuries caused by firearms.
Top Trends January 25th, 2023
Panic! At The Disco was the top trending topic related to Breakup after the pop rock band announced that its next tour would be its last, past day, US
“tornado watch” was a breakout search, past day, US, after weather forecasters issued a warning about a developing storm to parts of the Gulf Coast on Tuesday. It was most searched in Texas
“oscar nominations 2023” was the top trending topic, past day, worldwide, after the nominees were announced on Tuesday morning. See yesterday’s special Oscars newsletter for more Academy Awards-related trends
“ind vs nz” was the top trending sports game worldwide after a Tuesday cricket match, past day, worldwide. It was most searched in India, Nepal and Sri Lanka
Earth’s inner core was a breakout search and was searched in every US state, past day, US, following the publication of a new study, which describes potential changes the Earth’s inner core’s rotation
World Population
“most populated country” was a worldwide breakout search in the past week. It was most searched in India, followed by Nepal and the United Arab Emirates
Search interest in Birth Rate hit a five year-high in 2022, past five years, worldwide
Japan and Prime Minister of Japan were two of the top trending topics related to the Birth Rate, past week, worldwide
Top questions about Population, past week, worldwide:
What are the 10 countries with the largest population?
- China
- India
- United States
- Indonesia
- Brazil
- Pakistan
- Nigeria
- Bangladesh
- Russia
- Mexico
What is population?
What is the population of India? 1,375,586,000 as 0f 2023
What country has the highest population? China
What is the population of China? 1,411,750,000
Top “birth rate in” searches, past week, worldwide:
Birth rate in India: The birth rate in India is currently around 20 births per 1,000 people. However, this rate has been decreasing in recent years due to factors such as increased access to education and family planning resources.
Birth rate in US: The birth rate in the United States has been on a decline in recent years. In 2020, the birth rate in the United States was 13.5 births per 1,000 total population, which is the lowest it has been in the country’s history. This decline in the birth rate can be attributed to a variety of factors, including economic uncertainty, delays in starting families, and changes in cultural attitudes towards having children.
Birth rate in Japan: The birth rate in Japan has been declining for several decades. In 2020, the birth rate in Japan was 7.9 births per 1,000 population. This is significantly lower than the replacement rate of 2.1 children per woman, which is the number of children needed to maintain a stable population. Factors contributing to the low birth rate in Japan include a lack of affordable childcare, a lack of support for working mothers, and a cultural preference for small families.
Birth rate in China: The birth rate in China has been decreasing in recent years due to the country’s one-child policy and increasing urbanization. The policy, which was implemented in 1979 and officially ended in 2015, limited most urban couples to one child and many rural couples to two children. As a result, the birth rate in China has been below the replacement level for some time. However, the Chinese government has recently loosened its population control policies, allowing couples to have two children. But the decrease in birth rate remains a concern.
Birth rate in Canada: The birth rate in Canada is around 10 births per 1,000 people. This is considered a low birth rate compared to other countries. Factors that contribute to this include access to birth control and family planning, as well as economic and social factors such as the high cost of raising children and women’s increasing participation in the workforce.
Advanced Placement
Advanced Placement was searched in every US state in the past day. It was most searched in Georgia, followed by New Jersey and Florida
The top question about Advanced Placement is “what is ap african american studies“, past week, US
Advanced Placement peaks every May and September, all time, US
In 2022, AP Computer Science Principles was searched two times more than AP Computer Science for the first time ever. AP Computer Science Principles also saw a huge spike last year, reaching an all-time high in terms of search interest
Top trending AP classes, 2023, US
Top trends January 24th, 2023
The San Francisco 49ers are the top trending topic in the world following their playoff defeat of the Dallas Cowboys and Brock Purdy is the top trending topic in the US, past day
“Pays de Cassel vs PSG” and “india women vs west indies women” are the top two sporting events being searched worldwide over the past day
“when will light come in pakistan today” is the top trending question over the past day in Pakistan following a countrywide power outage
Search interest in “maya rudolph m&m” is more than twice that of both “blue m&m” and “red m&m” following news that actress Maya Rudolph will be a spokesperson for M&Ms, past day, US
Doja Cat is the most searched Paris Fashion Week attendee, followed by Kylie Jenner, past day, worldwide
AFC Championship Game 2023: Winner, Score Predictions for Bengals vs. Chiefs: Bengals has 53% chance of winning
Oscars Special
Washington DC, followed by California and New York are the top US states searching for “oscar nominations” following the release of the nominations, past four hours:
Best PictureTop Gun: MaverickTom Cruise, Jerry Bruckheimer, Christopher McQuarrie, …Women TalkingFrances McDormand, Dede Gardner, Jeremy KleinerEverything Everywhere All at OnceDaniel Kwan, Daniel Scheinert, Jonathan WangThe Banshees of InisherinMartin McDonagh, Graham Broadbent, Peter CzerninTriangle of SadnessErik Hemmendorff, Philippe BoberThe FabelmansSteven Spielberg, Tony Kushner, Kristie Macosko KriegerAll Quiet on the Western FrontMalte GrunertAvatar: The Way of WaterJames Cameron, Jon LandauElvisBaz Luhrmann, Catherine Martin, Gail Berman, …TárTodd Field, Alexandra Milchan, Scott LambertACTOR IN A SUPPORTING ROLE
NOMINEES
BRENDAN GLEESON
The Banshees of InisherinBRIAN TYREE HENRY
CausewayJUDD HIRSCH
The FabelmansBARRY KEOGHAN
The Banshees of InisherinKE HUY QUAN
Everything Everywhere All at OnceACTRESS IN A LEADING ROLE
NOMINEES
CATE BLANCHETT
TárANA DE ARMAS
BlondeANDREA RISEBOROUGH
To LeslieMICHELLE WILLIAMS
The FabelmansMICHELLE YEOH
Everything Everywhere All at OnceACTRESS IN A SUPPORTING ROLE
NOMINEES
ANGELA BASSETT
Black Panther: Wakanda ForeverHONG CHAU
The WhaleKERRY CONDON
The Banshees of InisherinJAMIE LEE CURTIS
Everything Everywhere All at OnceSTEPHANIE HSU
Everything Everywhere All at OnceANIMATED FEATURE FILM
NOMINEES
GUILLERMO DEL TORO’S PINOCCHIO
Guillermo del Toro, Mark Gustafson, Gary Ungar and Alex BulkleyMARCEL THE SHELL WITH SHOES ON
Dean Fleischer Camp, Elisabeth Holm, Andrew Goldman, Caroline Kaplan and Paul MezeyPUSS IN BOOTS: THE LAST WISH
Joel Crawford and Mark SwiftTHE SEA BEAST
Chris Williams and Jed SchlangerTURNING RED
Domee Shi and Lindsey CollinsCINEMATOGRAPHY
NOMINEES
ALL QUIET ON THE WESTERN FRONT
James FriendBARDO, FALSE CHRONICLE OF A HANDFUL OF TRUTHS
Darius KhondjiELVIS
Mandy WalkerEMPIRE OF LIGHT
Roger DeakinsTÁR
Florian HoffmeisterCOSTUME DESIGN
NOMINEES
BABYLON
Mary ZophresBLACK PANTHER: WAKANDA FOREVER
Ruth CarterELVIS
Catherine MartinEVERYTHING EVERYWHERE ALL AT ONCE
Shirley KurataMRS. HARRIS GOES TO PARIS
Jenny BeavanDIRECTING
NOMINEES
THE BANSHEES OF INISHERIN
Martin McDonaghEVERYTHING EVERYWHERE ALL AT ONCE
Daniel Kwan and Daniel ScheinertTHE FABELMANS
Steven SpielbergTÁR
Todd FieldTRIANGLE OF SADNESS
Ruben ÖstlundDOCUMENTARY FEATURE FILM
NOMINEES
ALL THAT BREATHES
Shaunak Sen, Aman Mann and Teddy LeiferALL THE BEAUTY AND THE BLOODSHED
Laura Poitras, Howard Gertler, John Lyons, Nan Goldin and Yoni GolijovFIRE OF LOVE
Sara Dosa, Shane Boris and Ina FichmanA HOUSE MADE OF SPLINTERS
Simon Lereng Wilmont and Monica HellströmNAVALNY
Daniel Roher, Odessa Rae, Diane Becker, Melanie Miller and Shane BorisDOCUMENTARY SHORT FILM
NOMINEES
THE ELEPHANT WHISPERERS
Kartiki Gonsalves and Guneet MongaHAULOUT
Evgenia Arbugaeva and Maxim ArbugaevHOW DO YOU MEASURE A YEAR?
Jay RosenblattTHE MARTHA MITCHELL EFFECT
Anne Alvergue and Beth LevisonSTRANGER AT THE GATE
Joshua Seftel and Conall JonesFILM EDITING
NOMINEES
THE BANSHEES OF INISHERIN
Mikkel E.G. NielsenELVIS
Matt Villa and Jonathan RedmondEVERYTHING EVERYWHERE ALL AT ONCE
Paul RogersTÁR
Monika WilliTOP GUN: MAVERICK
Eddie HamiltonINTERNATIONAL FEATURE FILM
NOMINEES
ALL QUIET ON THE WESTERN FRONT
GermanyARGENTINA, 1985
ArgentinaCLOSE
BelgiumEO
PolandTHE QUIET GIRL
IrelandMAKEUP AND HAIRSTYLING
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Heike Merker and Linda EisenhamerováTHE BATMAN
Naomi Donne, Mike Marino and Mike FontaineBLACK PANTHER: WAKANDA FOREVER
Camille Friend and Joel HarlowELVIS
Mark Coulier, Jason Baird and Aldo SignorettiTHE WHALE
Adrien Morot, Judy Chin and Anne Marie BradleyMUSIC (ORIGINAL SCORE)
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Volker BertelmannBABYLON
Justin HurwitzTHE BANSHEES OF INISHERIN
Carter BurwellEVERYTHING EVERYWHERE ALL AT ONCE
Son LuxTHE FABELMANS
John WilliamsMUSIC (ORIGINAL SONG)
NOMINEES
APPLAUSE
from Tell It like a Woman; Music and Lyric by Diane WarrenHOLD MY HAND
from Top Gun: Maverick; Music and Lyric by Lady Gaga and BloodPopLIFT ME UP
from Black Panther: Wakanda Forever; Music by Tems, Rihanna, Ryan Coogler and Ludwig Goransson; Lyric by Tems and Ryan CooglerNAATU NAATU
from RRR; Music by M.M. Keeravaani; Lyric by ChandraboseTHIS IS A LIFE
from Everything Everywhere All at Once; Music by Ryan Lott, David Byrne and Mitski; Lyric by Ryan Lott and David ByrneBEST PICTURE
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Malte Grunert, ProducerAVATAR: THE WAY OF WATER
James Cameron and Jon Landau, ProducersTHE BANSHEES OF INISHERIN
Graham Broadbent, Pete Czernin and Martin McDonagh, ProducersELVIS
Baz Luhrmann, Catherine Martin, Gail Berman, Patrick McCormick and Schuyler Weiss, ProducersEVERYTHING EVERYWHERE ALL AT ONCE
Daniel Kwan, Daniel Scheinert and Jonathan Wang, ProducersTHE FABELMANS
Kristie Macosko Krieger, Steven Spielberg and Tony Kushner, ProducersTÁR
Todd Field, Alexandra Milchan and Scott Lambert, ProducersTOP GUN: MAVERICK
Tom Cruise, Christopher McQuarrie, David Ellison and Jerry Bruckheimer, ProducersTRIANGLE OF SADNESS
Erik Hemmendorff and Philippe Bober, ProducersWOMEN TALKING
Dede Gardner, Jeremy Kleiner and Frances McDormand, ProducersPRODUCTION DESIGN
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Production Design: Christian M. Goldbeck; Set Decoration: Ernestine HipperAVATAR: THE WAY OF WATER
Production Design: Dylan Cole and Ben Procter; Set Decoration: Vanessa ColeBABYLON
Production Design: Florencia Martin; Set Decoration: Anthony CarlinoELVIS
Production Design: Catherine Martin and Karen Murphy; Set Decoration: Bev DunnTHE FABELMANS
Production Design: Rick Carter; Set Decoration: Karen O’HaraSHORT FILM (ANIMATED)
NOMINEES
THE BOY, THE MOLE, THE FOX AND THE HORSE
Charlie Mackesy and Matthew FreudTHE FLYING SAILOR
Amanda Forbis and Wendy TilbyICE MERCHANTS
João Gonzalez and Bruno CaetanoMY YEAR OF DICKS
Sara Gunnarsdóttir and Pamela RibonAN OSTRICH TOLD ME THE WORLD IS FAKE AND I THINK I BELIEVE IT
Lachlan PendragonSHORT FILM (LIVE ACTION)
NOMINEES
AN IRISH GOODBYE
Tom Berkeley and Ross WhiteIVALU
Anders Walter and Rebecca PruzanLE PUPILLE
Alice Rohrwacher and Alfonso CuarónNIGHT RIDE
Eirik Tveiten and Gaute Lid LarssenTHE RED SUITCASE
Cyrus NeshvadSOUND
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Viktor Prášil, Frank Kruse, Markus Stemler, Lars Ginzel and Stefan KorteAVATAR: THE WAY OF WATER
Julian Howarth, Gwendolyn Yates Whittle, Dick Bernstein, Christopher Boyes, Gary Summers and Michael HedgesTHE BATMAN
Stuart Wilson, William Files, Douglas Murray and Andy NelsonELVIS
David Lee, Wayne Pashley, Andy Nelson and Michael KellerTOP GUN: MAVERICK
Mark Weingarten, James H. Mather, Al Nelson, Chris Burdon and Mark TaylorVISUAL EFFECTS
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Frank Petzold, Viktor Müller, Markus Frank and Kamil JafarAVATAR: THE WAY OF WATER
Joe Letteri, Richard Baneham, Eric Saindon and Daniel BarrettTHE BATMAN
Dan Lemmon, Russell Earl, Anders Langlands and Dominic TuohyBLACK PANTHER: WAKANDA FOREVER
Geoffrey Baumann, Craig Hammack, R. Christopher White and Dan SudickTOP GUN: MAVERICK
Ryan Tudhope, Seth Hill, Bryan Litson and Scott R. FisherWRITING (ADAPTED SCREENPLAY)
NOMINEES
ALL QUIET ON THE WESTERN FRONT
Screenplay – Edward Berger, Lesley Paterson & Ian StokellGLASS ONION: A KNIVES OUT MYSTERY
Written by Rian JohnsonLIVING
Written by Kazuo IshiguroTOP GUN: MAVERICK
Screenplay by Ehren Kruger and Eric Warren Singer and Christopher McQuarrie; Story by Peter Craig and Justin MarksWOMEN TALKING
Screenplay by Sarah PolleyWRITING (ORIGINAL SCREENPLAY)
NOMINEES
THE BANSHEES OF INISHERIN
Written by Martin McDonaghEVERYTHING EVERYWHERE ALL AT ONCE
Written by Daniel Kwan & Daniel ScheinertTHE FABELMANS
Written by Steven Spielberg & Tony KushnerTÁR
Written by Todd FieldTRIANGLE OF SADNESS
Written by Ruben ÖstlundAvatar: The Way of Water is the most searched Best Picture nominee, followed by Everything Everywhere All at Once, past day, US
Brendan Fraser is the most searched Best Actor nominee, followed by Austin Butler, past day, US
Ana de Armas is the most searched Best Actress nominee, followed by Cate Blanchett, past day, US
British actor, Riz Ahmed +450% and American actress Allison Williams +400% spiked, past week, US ahead of the nominations announcement
Ellen DeGeneres is the most searched Oscars host of all time in the US, followed by Jimmy Kimmel
Most searched movies released in 2022, 2022, US
The Batman
Top Gun: Maverick
Avatar: The Way of Water
Doctor Strange in the Multiverse of Madness
Nope
Top searched “will…be nominated for an Oscar?”, past month ahead of the nominations announcement, US
Will Austin Butler be nominated for an Oscar? Yes
Will Tom Cruise be nominated for an Oscar? Yes
Will Nope be nominated for an Oscar? Yes
Will Elvis be nominated for an Oscar? Yes
Will Top Gun: Maverick be nominated for an Oscar? Yes
Top searched “how many Oscars does…have?”, past month ahead of the nominations announcement, US
How many Oscars does Leonardo DiCaprio have? 1
How many Oscars does Christian Bale have? 1
How many Oscars does Meryl Streep have? 3
How many Oscars does Denzel Washington have? 2
How many Oscars does Brad Pitt have? 2
Most searched “…oscar snub” following the nominations announcement, past four hours, US
Tom Cruise Oscar snub
RRR Oscar snub
The Batman Oscar snub
Taylor Swift Oscar snub
Viola Davis Oscar snub
Top Trends January 23rd, 2023
Mass shooting is a top trending topic, which search interest more than tripled, past day, US. “why are flags at half mast today” is a breakout search over the same time period
“how many countries celebrate lunar new year” +3,800% and “lunar new year video for kids” is up +2,550%, past day, worldwide: Many countries in East and Southeast Asia, including China, Vietnam, Korea, and Singapore, celebrate Lunar New Year. Other countries with significant Asian populations, such as Malaysia, Indonesia, and the Philippines, also observe the holiday. In addition, some countries in the West also celebrate Lunar New Year, such as the United States, Canada, and Australia.
Global search interest in “love character test” tripled, past day, since its popularity on TikTok
Search interest in “snow day calculator” increased fivefold, past day, US. The top state searching for this is Maine.
Mycology is a top trending topic related to The Last of US, TV series, past day, worldwide.
Remembering David Crosby
David Crosby was remembered yesterday after his death was announced. The world searched for his songs and for Crosby, Stills, Nash & Young
Suite: Judy Blue Eyes and Almost Cut My Hair are David Crosby’s top trending songs in the US since yesterday
david crosby was the top trending YouTube search in the US in the past day
Searches for Crosby’s former band The Byrds spiked by +140% in the hours before this newsletter was published
Top trending David Crosby Lyrics, past day
Teach Your Children
Southern Cross
Almost Cut My Hair
Long Time Gone
Laughing
NFL Divisional Round 🏈
People searching for the NFL Divisional Round were also searching for History of the National Football League championship, past day, US
Search interest in The NFC Championship Game is 1.3x that of the AFC Championship Game, past day, US
“cowboys vs 49ers rivalry” is the top trending Rivalry-related search, past week, US
“best bets nfl divisional round” +2,550%, past week, US
Trending questions on the NFL over divisional weekend, US
Where are the Bills playing today? Cincinnati Bengals
Is Damar Hamlin playing today? No, he is still recovering from cardiac arrest.
Who won the Eagles game? Philadelphia Eagles
Who won the Chiefs game? Kansas City Chiefs
Who won the Super Bowl last year? Los Angeles RAMS
Top searched NFL Divisional Round players over divisional weekend, US
Patrick Mahomes II (QB) – Kansas City Chiefs
Joe Burrow (QB) – Cincinnati Bengals
Trevor Lawrence (QB) – Jacksonville Jaguars
Jalen Hurts (QB) – Philadelphia Eagles
Josh Allen (QB) – Buffalo Bills
Travis Kelce (TE) – Kansas City Chiefs
Chad Henne (QB) – Kansas City Chiefs
Brock Purdy (QB) – San Francisco 49ers
Dak Prescott (QB) – Dallas Cowboys
Daniel Jones (QB) – New York Giants
Top Trends January 19th-20th, 2023
New Zealand Prime Minister, “Jacinda Arden” became the top trending woman in the US over the past day after announcing her resignation.
Bank of America became the top trending topic across the US after an outage with their Zelle services.
“Nadal” became the top trending person across the globe after the Spanish tennis player was injured and exited from the Australian Open.
US searches for “Ron Jeremy” spiked +350% after the former adult film actor was declared unfit to stand trial for his crimes.
Gut Health
Worldwide searches for gut health reached an all-time high in June 2022, with a second all-time high in January 2023.
Over the past week, “how to improve gut health” is the 7th top searched “how to improve” in the US.
There are several ways to improve gut health:
Eat a balanced diet: Include a variety of fruits, vegetables, whole grains, and lean proteins in your diet. Avoid processed foods and added sugars, which can disrupt the balance of gut bacteria.
Take probiotics: Probiotics are live microorganisms that can help to maintain a healthy balance of gut bacteria. They can be found in supplements, fermented foods such as yogurt, kefir, sauerkraut and kimchi, and in some non-fermented foods like pickles.
Consume prebiotics: Prebiotics are non-digestible carbohydrates that act as food for probiotics. They can be found in foods such as bananas, onions, garlic, leeks, asparagus, and oats.
Stay hydrated: Drinking enough water can help to keep your digestion regular and prevent constipation.
Exercise regularly: Physical activity can help to stimulate the movement of food through the gut, promoting healthy digestion.
Manage stress: Chronic stress can disrupt the balance of gut bacteria and contribute to digestive issues. Find ways to manage stress, such as through exercise, yoga, or meditation.
Avoid antibiotics: Antibiotics can kill off both bad and good bacteria in the gut, disrupting the balance of gut microbiome. Be sure to only take antibiotics when it is necessary and as prescribed by a healthcare professional.
It’s also worth noting that everyone’s gut health is different, it’s important to experiment and find what works best for you. Always consult with a healthcare professional if you have any concerns about your gut health.
More than ever before are Americans searching for “fermented food” in January 2023.
“food sensitivity test” +550%, past week, US
Trending “do probiotics…” past week, US
Do probiotics Stop diarrhea? Probiotics have been shown to be effective in reducing the duration and severity of diarrhea caused by certain types of infections, such as those caused by bacteria or viruses. However, it’s important to note that probiotics are not effective for all types of diarrhea, such as that caused by certain medications or underlying medical conditions. It’s also important to consult with a healthcare provider before taking probiotics, especially if you have a weakened immune system or a chronic medical condition.
Do probiotics Cause acne? There is currently limited scientific evidence to support the claim that probiotics cause acne. While some studies have suggested a possible link between probiotics and acne, the results are not conclusive and more research is needed to determine a definitive cause-and-effect relationship. It’s also important to note that individual factors, such as diet, genetics, and skin care regimen, can also play a role in the development of acne. That being said, if you have a history of acne and are considering taking probiotics, it may be a good idea to consult with a healthcare provider or a dermatologist first.
Do probiotics Help with infections? Probiotics have been shown to be beneficial in the prevention and treatment of certain types of infections, particularly those that affect the digestive tract. For example, probiotics may help to prevent and treat diarrhea caused by bacterial or viral infections. They may also help to reduce the risk of urinary tract infections, and can improve symptoms of inflammatory bowel disease. Probiotics may also help to improve the balance of the gut microbiome which can help to boost the immune system and decrease the chance of infection. However, it’s important to note that probiotics are not effective for all types of infections, and it’s always best to consult with a healthcare provider before taking probiotics, especially if you are currently experiencing an infection or have a weakened immune system.
Do probiotics Cause bloating? Probiotics have been known to cause bloating and gas in some people, especially when they first start taking them. This is because probiotics may increase the production of gas in the gut as they ferment undigested food. However, these side effects are usually temporary and should subside within a few days to a week. It’s also worth noting that some people may be more sensitive to certain strains of probiotics than others, so it may be helpful to try different types of probiotics to see which one works best for you. If you are experiencing severe or persistent bloating, it is always best to consult with a healthcare provider to rule out other underlying causes.
Do probiotics Help acne? There is some evidence that suggests that probiotics may help to improve acne by regulating the balance of bacteria in the gut and reducing inflammation. Studies have shown that people with acne tend to have a less diverse gut microbiome compared to those without acne. By taking probiotics, it can help to restore the balance of gut bacteria and reduce inflammation which can help to improve acne symptoms. However, it’s important to note that research in this area is still ongoing and more studies are needed to fully understand the relationship between probiotics and acne. Also, it’s worth noting that probiotics may work differently for different people, what works for one person may not work for another, so it’s always best to consult with a healthcare provider before taking any new supplement.
Trending “does… help gut health” past week, US 
Does Collagen help gut health? Collagen is a protein that is found in the body and is known to play a role in supporting the health of the skin, joints, bones, and tendons. Some studies suggest that consuming collagen supplements may also help to support gut health by strengthening the gut lining, which can help to prevent leaky gut syndrome and other gut-related issues. However, more research is needed to fully understand the potential benefits of collagen for gut health.
Does Kefir help gut health?
Kefir is a fermented milk drink that has been traditionally used in Eastern Europe and Central Asia. It is made by fermenting milk with kefir grains, which are a combination of lactic acid bacteria and yeasts. Due to the fermentation process, Kefir is a probiotic-rich food, which means it contains beneficial microorganisms that can help to promote a healthy gut.
Research has shown that consuming kefir can help to improve the balance of gut bacteria, which can in turn improve gut health and boost the immune system. It has been found to help with diarrhea, constipation, IBS, and other digestive issues. It also has been found to have anti-inflammatory properties, which can help to reduce gut inflammation.
It’s worth noting that kefir is generally well tolerated, but as with any food, some people may be allergic or intolerant to the milk used to make it.
Does Magnesium help gut health?
Magnesium is an essential mineral that plays a role in many bodily functions, including muscle and nerve function, and the regulation of the heart’s rhythm. Some studies suggest that magnesium may also play a role in supporting gut health.
Magnesium has been found to have a relaxing effect on the muscles of the gut, which can help to ease symptoms of constipation and diarrhea. It also plays a role in maintaining the integrity of the gut lining, which can help to prevent leaky gut syndrome and other gut-related issues. Additionally, magnesium can help to regulate the activity of the immune system, which can help to reduce inflammation in the gut.
However, It is worth noting that not all forms of magnesium are easily absorbed by the body, and people with gut issues or malabsorption may have trouble getting enough magnesium from food or supplements.
It is always best to consult with a healthcare professional before starting any supplement regimen.
Does Apple cider vinegar help gut health?
Apple cider vinegar (ACV) is a popular natural remedy that is claimed to have many health benefits, including supporting gut health. ACV is made by fermenting apples, which gives it many of the same properties as other fermented foods, such as kefir.
Some research suggests that consuming ACV may help to improve the balance of gut bacteria, which can in turn improve gut health. It may also help to reduce inflammation in the gut, which can be beneficial for people with inflammatory bowel disease (IBD) or other gut issues.
ACV may also help to ease symptoms of constipation and diarrhea, and it has been found to have anti-inflammatory properties, which can help to reduce gut inflammation.
It’s worth noting that while ACV is generally considered safe, consuming too much of it can be harmful and lead to side effects such as throat burns, nausea, and tooth erosion. It’s best to consume it in moderate amounts and dilute it with water before consuming it.
It is also important to note that while there is some research suggesting that ACV may have health benefits, more research is needed to fully understand its effects on gut health, and it should not be used as a substitute for any medical treatment or medication.
Does Coconut oil help gut health?
Coconut oil is a popular natural remedy that is claimed to have many health benefits, including supporting gut health.
Coconut oil is high in medium-chain triglycerides (MCTs), which are a type of saturated fat that is easily digested and absorbed by the body. MCTs have been found to have a beneficial effect on gut health by promoting the growth of beneficial bacteria in the gut, which can improve the balance of gut bacteria.
Coconut oil has also been found to have anti-inflammatory properties, which can help to reduce inflammation in the gut, which is beneficial for people with inflammatory bowel disease (IBD) or other gut issues.
Additionally, Coconut oil has also been found to have a beneficial effect on the digestive system. It can help to ease symptoms of constipation and diarrhea, and it can also help to improve gut motility, which is the ability of the gut to move food through the digestive tract.
However, it’s worth noting that not all the research on coconut oil’s effects on gut health are conclusive, and more research is needed to fully understand its effects. Also, people who are sensitive to coconut oil or have a history of allergies should be cautious when consuming it, and it’s best to consult with a healthcare professional before starting any supplement regimen.
Revenge Songs
Over the past week, the top searched people worldwide are “Shakira”, “Pique” and “clara chia”
People searching for Jam over the past week in the US are also searching for Shakira after the singer hinted a half-eaten jar of jam led her to suspect infidelity.
The top trending “flowers” and “sample” searched this week are related to Miley’s new song.
Searches for Bruno Mars increased by +2,250% over the past week after Miley referenced one of his songs in her new single with “bruno mars response to flowers” as a breakout search.
Late night thoughts keeping you awake? Searches for cheating in a relationship peak between 3-6 AM EST in the US.
Trending “who is… about” past 12 months, US
Who is Vigilante Sh*t?
Who is Candle in the Wind? “Candle in the Wind” is a song by British singer Elton John. The original version of the song was released in 1973 and was a tribute to Marilyn Monroe. In 1997, the song was re-released as “Candle in the Wind 1997” in tribute to Princess Diana, and this version became one of the best-selling singles of all time.
Who is Ours?
Who is Obsessed?
Who is Hey Jude?
Trending songs, past week, US
Flowers
Shakira | BZRP Music Sessions #53
When I Was Your Man
Karma Chameleon
Hey Jude
Top Trends on January 18th, 2023
All top trending searches related to The White House are about the Golden State Warriors’ visit to celebrate their recent NBA Championship
Madonna is a breakout topic following the announcement of her upcoming tour. Vogue is the most searched Madonna song of all time in the US.
“detained meaning” and “detained vs arrested” are global breakout searches over the past day following Greta Thunberg’s detainment in Germany
“cowboys kicker” is the top trending search and Brett Maher is the top trending top related to American football, past day, US
Oleksiy Arestovych is up +1,500% after resigning as an advisor to Volodymyr Zelenskyy, past day, US
The Last of Us
Depeche Mode’s Never Let Me Down Again is being searched over 100x more this week than last week in the US
Cordyceps is the top trending topic related to zombie, past day, US
“last of us zombie types” is up +550% and “clickers last of us” nearly doubled, past week, US
“last of us no spores” nearly doubled and “tendrils the last of us” nearly tripled, past week, US
“who are the fireflies the last of us” is a breakout search, past week, US
Top trending questions on fungus, past week, US
Can fungi control humans? No, fungi cannot control humans. Fungi are a type of organism that belong to the kingdom of fungi and include species such as yeasts, molds, and mushrooms. While some fungi can cause infections in humans, they do not have the ability to control or manipulate human behavior.
Can fungus take over your body?
While it is possible for certain types of fungus to infect and cause damage to the body, it is highly unlikely for a fungus to completely take over the body. The human body has a number of mechanisms in place to prevent the overgrowth of fungus, including the immune system, which helps to fight off infection.
Fungal infections can occur in various parts of the body such as the skin, nails, hair, and the respiratory, urinary and gastrointestinal tracts. Some fungal infections are limited to certain areas of the body and are treated with topical or oral antifungal medications, however, some fungal infections can be invasive and can affect internal organs and systems, causing serious illness.
Examples of invasive fungal infections include candidemia (a bloodstream infection caused by Candida), aspergillosis (caused by Aspergillus), and mucormycosis (caused by Mucor and Rhizopus) which can affect people with weakened immune systems. These types of fungal infections are usually treated with antifungal drugs and may require hospitalization.
It’s important to keep in mind that fungal infections are not contagious, they are usually caused by the overgrowth of already present fungus in the body. If you suspect you have a fungal infection, it’s important to see a healthcare professional for proper diagnosis and treatment.
Can fungi infect humans? Yes, certain types of fungi can infect humans and cause a variety of illnesses, ranging from mild skin infections to life-threatening systemic infections
Can fungus survive heat? Yes, some fungi can survive high temperatures, but their survival depends on the type of fungus and the specific conditions of heat exposure. Some fungi can tolerate temperatures as high as 60°C, while others can only survive up to 30°C. The ability of fungi to withstand heat can vary based on factors such as the species, growth conditions, and surrounding environment. In general, high heat can damage or kill many fungi, but some heat-resistant species can persist and continue to grow in these conditions.
How does the fungus spread in The Last of Us? In the video game “The Last of Us,” the fungus that caused the outbreak of the pandemic is known as the Cordyceps fungus. It infects insects and small mammals, taking control of their bodies, then uses them to spread its spores to other animals or humans. The fungus infects the brain and alters the behavior of the host, causing it to become violent and spread the fungus further. The fungus then grows and spreads throughout the body of the infected host, eventually killing them and producing new fungal spores.
Top trending characters from The Last of Us
Sarah
Joel
Tess
Marlene
Tommy
Debt Ceiling
Janet Yellen is up +2,100% and “extraordinary measures” doubled, past week, US
“how much debt is the us in” and “who does the us owe money to” are breakout searches, past week, US
Search interest in both 2011 United States debt-ceiling crisis and “debt ceiling history” more than doubled, past week, US
“debt ceiling government shutdown” is up +850%, past week, US
Top trending questions related to the United States debt ceiling, past week, US
What is the US debt limit? What happens when we hit the debt ceiling? When the debt ceiling is reached, the government is unable to borrow any more money and is forced to limit its spending to the amount of money it is currently bringing in through revenue. This can lead to a government shutdown, as non-essential government services and programs will cease to be funded, and government employees may be furloughed. Additionally, the government will not be able to make payments on its debt, which could lead to a default. It is considered a serious issue, and in the past, raising the debt ceiling has been a contentious political issue.
What would happen if the US defaulted on debt?
How high is the debt ceiling?
Most searched “how much does the US spend on…”, past year, US
How much does the US spend on Military?
The United States spends a significant amount on its military. According to the Congressional Research Service, the U.S. spent an estimated $801 billion on national defense in fiscal year 2022, which includes all spending related to the military, including personnel, operations and maintenance, procurement, and research and development. This represents about 3.5% of the U.S. gross domestic product (GDP).
It’s worth noting that the U.S. military budget is one of the highest in the world, and it is significantly higher than the military spending of any other country. The U.S. military budget is larger than the combined military budgets of the next seven highest-spending countries, which include China, Russia, Saudi Arabia, India, France, the United Kingdom, and Germany.
It’s also worth noting that the amount of military spending can vary depending on the year and the current political climate. The budget is subject to change depending on the priorities of the government and the current events.
It’s important to note that the military budget is just a small part of the overall federal budget, which includes spending on a wide range of other programs such as education, healthcare, and social security.
How much does the US spend on Healthcare?
The United States spends a significant amount on healthcare. According to the Centers for Medicare and Medicaid Services (CMS), the U.S. spent an estimated $4.3 trillion on healthcare in 2022, which represents about 18% of the U.S. gross domestic product (GDP).
The U.S. healthcare spending is among the highest in the world, and it continues to grow each year. The high cost of healthcare in the United States can be attributed to a variety of factors, including an aging population, the high cost of prescription drugs, administrative costs and a high utilization of medical services.
It’s worth noting that the U.S. has a mixed system of healthcare, with a mix of public and private healthcare systems. The government funds programs such as Medicaid and Medicare, which provide healthcare coverage for low-income and older Americans, respectively. The majority of Americans receive their healthcare through private health insurance, which is provided by their employer or purchased individually.
It’s also worth noting that the U.S. healthcare system is complex, and the spending can vary depending on the state and the type of care. The U.S. healthcare spending is not only on health care services, but also on health care goods such as drugs, medical equipment and medical facilities.
It’s important to note that the healthcare spending is just a small part of the overall federal budget, which includes spending on a wide range of other programs such as education, military, and social security.
How much does the US spend on Education?
The United States spends a significant amount on education, but it varies depending on the level of education and the source of funding. According to the National Center for Education Statistics (NCES), the U.S. spent an estimated $1.5 trillion on education in 2022.
The U.S. federal government contributes a significant amount of funding for education, primarily through programs such as Title I and Individuals with Disabilities Education Act (IDEA), which provide funding to support disadvantaged students and students with special needs. State and local governments also contribute funding for education, primarily through property taxes.
The spending on education also varies depending on the level of education. The U.S. spend more on higher education than on primary and secondary education. According to the National Center for Education Statistics (NCES), in 2020, the U.S. spent $730 billion on elementary and secondary education and $567 billion on postsecondary education.
It’s worth noting that the U.S. education spending as a percentage of GDP is lower than most other developed countries. According to the Organization for Economic Cooperation and Development (OECD), the US spent about 4.6% of GDP on education in 2019, which is below the OECD average of 5.2%.
It’s important to note that the education spending is just a small part of the overall federal budget, which includes spending on a wide range of other programs such as healthcare, military, and social security.
How much does the US spend on Welfare? The United States government spends a significant amount of money on welfare programs aimed at assisting low-income individuals and families. The exact amount varies from year to year and depends on various factors, such as the state of the economy, the number of people in need of assistance, and the cost of living. In recent years, the total federal spending on welfare programs has been estimated to be in the hundreds of billions of dollars annually.
How much does the US spend on Prisons? As of 2021, the United States spends an estimated 80 billion dollars annually on its prison system. This amount covers various costs including construction and maintenance of prison facilities, staffing and employee salaries, and prisoner services such as medical care and rehabilitation programs. The cost of incarceration has risen dramatically in the US in recent decades, due to factors such as longer prison sentences, the War on Drugs, and increased spending on prison security measures.
Top Trends on January 17th, 2023
Martin Luther King Jr. ‘s I Have a Dream speech is the most searched speech of all-time in the US. The most searched MLK quote is “Injustice anywhere is a threat to justice everywhere.”
Matteo Messina Denaro is the top trending topic, worldwide, over the past day. “chi è il nuovo boss di cosa nostra” [Google Translate, Italian: “who is the new boss of cosa nostra”] is a breakout search
“Brendan fraser speech” is the top trending search related to Critics’ Choice Movie Awards, past day, US
“Nepal flight crash reason” spiked +1,850%, past day, worldwide.
Over the past week, Climate change and Cyberattack were the global top trending topics related to the World Economic Forum, which started on Monday.
Australian Open
Australian Open extreme heat policy is a breakout topic and “heat stress scale” is a breakout search, past day, worldwide
Search interest in “Rafa child” more than quadrupled and “Nadal ball boy” was a breakout search, past day, worldwide
“Nick Kyrgios girlfriend” is the top trending search related to Grand Slam, and “has Nick Kyrgios won a grand slam” is a breakout search, past week, worldwide
Search interest in “australian open 5th set rules” more than tripled, past week, worldwide
“Tennis player pregnant” is up +2,050% and “is Osaka pregnant” is a breakout search, past week, US
Top searched “what is…” related to tennis, past day, worldwide
What is break point in tennis? A break point in tennis refers to a point in a game where the receiving player has the opportunity to win the game by breaking their opponent’s serve. In other words, it is a point at which the serving player’s serve can be “broken” and the receiver can win the game. A break point occurs when the receiver is able to get to deuce (40-40) or advantage on the server’s side of the court. If the receiver wins the next point, they will have won the game. If the server wins the next point, the game will continue. Break point can be a crucial moment in a match, as it can change the momentum of the game and put the receiver in a strong position to win the set or match.
What is a set in tennis? A set in tennis is a unit of play that consists of several games. Typically, a set is won by the first player to win at least six games and be ahead by at least two games. In Grand Slam tournaments and many professional events, a set is usually the best of three or the best of five games. The winner of the match is the player who wins the most sets.
What is a tennis Grand Slam? A tennis Grand Slam refers to the four most prestigious annual events in the sport of tennis, namely the Australian Open, the French Open, Wimbledon, and the US Open. Winning all four events in a single calendar year is considered a Grand Slam, and is one of the greatest achievements in tennis.
What is an ace in tennis? An ace in tennis is a serve that lands in the opponent’s court and is not touched by the opponent, resulting in an immediate point for the serving player.
What is AD in tennis? AD in tennis refers to the term “advantage.” In tennis, the score is called “40-40” when both players have won three points each. When one player wins the next point, they are said to have the “advantage.” If the player who has the advantage wins the next point, they win the game. If the player who does not have the advantage wins the next point, the score is “deuce” and play continues until one player wins two consecutive points to win the game.
Ranked search interest in women’s singles players, past month, worldwide
Iga Świątek
Maria Sakkari
Caroline Garcia
Jessica Pegula
Ranked search interest in men’s singles players, past month, worldwide
Jannik Sinner
Daniil Medvedev
Andy Murray
Tax
Search interest in FairTax +3,300% and Consumption tax +1,800% spiked, past week, US
How does EV (Electrical Vehicles) tax credit work more than tripled, past week, US
In the United States, the federal government offers a tax credit for the purchase of new electric vehicles (EVs). The credit amount can vary depending on the make and model of the EV, and can range from $2,500 to $7,500. The credit begins to phase out once a manufacturer has sold 200,000 qualifying vehicles.
In Canada, the government offers a federal rebate of up to $5,000 for the purchase of new electric or hydrogen fuel cell vehicles, this rebate is non-refundable, so it can only be applied to reduce taxes payable to the government. The rebate also begins to phase out once a manufacturer has sold 2,500 units of the vehicle.
In Europe, the policies regarding EV tax credit vary from country to country. Some countries like Norway have a very generous EV purchase incentive with zero-emission vehicles being exempt from VAT, road tolls and other taxes, while other countries like France offer a bonus and malus system which rewards buyers of electric or hybrid vehicles with a discount on the purchase price while applying a surcharge on vehicles with high emissions.
It’s worth noting that these policies are subject to change depending on the government and regulations of each country. Before making a purchase, it’s always best to check the current policies and regulations in the country you’re in, to ensure you’re getting the most out of any available tax credit or rebate.
“Why is my tax refund so low 2023” is up +850%, past week, US
There are several reasons why your tax refund might be lower than expected in 2023. Some possible reasons include:
- Your income has increased: If you earned more money in 2023, you may have moved into a higher tax bracket and paid more taxes.
- Changes in deductions and credits: The Tax Cuts and Jobs Act of 2017 made significant changes to the tax code, including limiting certain deductions and credits, which may have affected your refund.
- More taxes were withheld from your paychecks: The IRS encourages taxpayers to adjust their withholding so that they don’t get a large refund, but rather pay the right amount of taxes throughout the year, thus avoiding owing taxes or getting a refund. If you have adjusted your withholding, you may have paid more taxes throughout the year and therefore have a smaller refund.
- You owe money to other government agencies: If you owe money for things like unpaid student loans or back taxes, your refund can be offset to pay those debts.
- You made a mistake on your tax return: If you made a mistake on your tax return, it could result in a lower refund. Double-checking your return and seeking help from a tax professional or using tax software can help you avoid errors.
It’s important to note that receiving a smaller refund or owing taxes is not necessarily a bad thing, it means that you paid the right amount of taxes throughout the year and avoided overpaying the government.
“What is child tax credit for 2023” quadrupled, past 30 days, US. Top state searching for Child tax credit during the same time period was West Virginia, followed by Mississippi and Arkansas.
Top question about tax, past week, US
When can you file taxes in 2023?
In the United States, the traditional tax filing season usually starts on January 1st and ends on April 15th, 2023. However, due to the COVID-19 pandemic, the deadline was extended to May 17th, 2023. So, you can file your taxes between January 1st and May 17th, 2023.
It’s important to note that the deadline to file taxes may change in the future, and it’s always best to check with the Internal Revenue Service (IRS) or a tax professional for the most up-to-date information.
It’s also worth noting that even though the deadline to file taxes is April 15th, 2023, you can file for an extension if you need more time. An extension allows you to file your taxes up to October 15th, 2023. But even if you file an extension, any taxes due still need to be paid by the April 15th deadline to avoid penalties and interest.
When are taxes due in 2023? April 15th, 2023 (unless you request an extension)
What is a consumption tax?
A consumption tax is a type of indirect tax that is imposed on goods and services when they are purchased by consumers. The tax is typically added to the price of the goods or services, and the consumer pays the tax when they make the purchase. Consumption taxes are also known as sales taxes, value-added taxes (VAT), or goods and services taxes (GST).
The idea behind a consumption tax is that it is paid by the end consumer, rather than by the business or producer. It is considered to be a “regressive” tax, as it takes a larger percentage of income from low-income individuals than from high-income individuals.
In the United States, consumption taxes vary from state to state, with some states having no sales tax, while others have a high sales tax rate. Additionally, some localities within states may also impose their own consumption taxes.
It’s important to note that consumption taxes are not the same as income taxes, which are taxes imposed on the income earned by individuals and businesses. Income taxes are considered to be a “progressive” tax as the tax rate increases with the income level.
Is social security taxable?
In the United States, the taxation of Social Security benefits is determined by the recipient’s income and filing status. Social Security benefits can be subject to federal income tax if a recipient’s combined income exceeds certain thresholds. The combined income is calculated by adding together the recipient’s adjusted gross income, nontaxable interest, and half of their Social Security benefits.
For the tax year 2021, if the recipient’s combined income is less than $25,000 for an individual or $32,000 for a married couple filing jointly, their Social Security benefits will not be taxed. If the combined income is between $25,000 and $34,000 for an individual or between $32,000 and $44,000 for a married couple filing jointly, up to 50% of the Social Security benefits may be subject to federal income tax. If the combined income is more than $34,000 for an individual or more than $44,000 for a married couple filing jointly, up to 85% of the Social Security benefits may be subject to federal income tax.
In Canada, the Old Age Security (OAS) pension is not subject to tax on its own, however, if you have other income and it exceeds a certain amount, you may have to repay some or all of your OAS pension.
It’s important to check with a tax professional to determine if and how much of your Social Security benefits may be subject to federal income tax, as there are different rules and regulations that apply.
How much is the child tax credit for 2023?
Top trending “what is…” related to tax, past week, US
What is a national consumption tax?
A national consumption tax is a type of indirect tax that is imposed on goods and services consumed within a country. It is also known as a value-added tax (VAT) or a goods and services tax (GST). The idea behind a national consumption tax is to tax the final consumer, rather than the producers and sellers of goods and services.
The way a national consumption tax works is that businesses must register and collect the tax from consumers on behalf of the government. The tax is typically levied at a percentage of the retail price, and is usually included in the advertised price of goods and services. Businesses can claim back the tax they have paid on their inputs (goods and services they bought to produce their own goods and services) as a credit against the tax they collect. This is known as the credit-invoice method.
National consumption taxes are widely used around the world, with many countries levying VAT or GST on a wide range of goods and services. The rate of tax varies from country to country, and can range from 5% to 25% or more.
It’s worth noting that consumption tax is not universally accepted and there are arguments for and against it. The main argument for consumption taxes is that they are considered more efficient and less distortionary than other types of taxes. On the other hand, it could disproportionately affect lower income households, as they tend to spend a larger proportion of their income on consumption.
What is the FairTax Act of 2023?
What is Tesla’s tax credit?
Tesla’s tax credit refers to the federal tax credit available in the United States for the purchase of certain electric vehicles (EVs), including those made by Tesla. The credit amount can vary depending on the make and model of the EV, and can range from $2,500 to $7,500.
The credit begins to phase out once a manufacturer has sold 200,000 qualifying vehicles. For Tesla, the full $7,500 credit began to phase out on January 1, 2020, and will be gradually reduced by 50% every six months until it reaches zero in 2022.
It’s worth noting that this is a federal tax credit and it’s not a refundable credit, meaning that it can only be applied to reduce taxes payable to the government. Additionally, the credit is only available to individuals who purchase the vehicle for personal use and not for business or commercial use. It’s also important to check with a tax professional to determine if and how much of the credit you may be eligible for, as there are different rules and regulations that apply.
What is a 1098-E form?
What is a federal tax credit?
Top trending tax credit, past week, US
Electric vehicle tax credits
Premium tax credit
Child tax credit
Working families tax credit
American opportunity tax credit
Air Travel • Inflation
Top Trends
Search interest in “tornado watch” spiked in the past day +1550% in the US as severe weather warnings are issued across the country. Georgia is the state most searching for tornado watches in the US.
Searches for “bacterial meningitis” spiked +2200% in the US after it was reported that guitarist Jeff Beck passed after contracting the illness
“flights grounded” spiked +4950% and “faa outage” spiked +4700% in the past day in the US
“date night ideas” hit an all-time high worldwide this January with the US and South Africa as the top countries searching for them. Pleasant and cheap are two of the top trending topics related to “date night ideas”
“special counsel” and Chevrolet Corvette are breakout searches in the past day in the US
Air Travel
“faa” was a breakout search, past week, US, after a Federal Aviation Administration (FAA) system outage led to a temporary stoppage of thousands of domestic flights on Wednesday morning
“Is air travel back to normal?” was the top question on Air Travel, past week, US
“Pete buttigieg,” the United States Secretary of Transportation, was a breakout search, past week, US
Search interest in Flight cancellation and delay reached a five-year high in December of 2022 after scores of holiday travelers’ plans were upended amid a winter storm, past five years, US
The United States was the top country searching for Flight cancellation and delay, followed by Canada and Jamaica, past week, worldwide
Inflation
Searches for inflation reached a global all-time high in 2022
The top country searching for Inflation worldwide is Turkey in 2023
“how to calculate inflation” was a breakout search, past week, US
“what is inflation” is a breakout search, past week, US
“what is stagflation” is a breakout search, past week, US
“cost of eggs” is a breakout search and “why is the cost of eggs rising” is up +700%, past week, US
Top trending questions on “inflation rate”, past day, US
1. What is the current inflation rate? you can find the most recent inflation rate by consulting the Bureau of Labor Statistics or the Federal Reserve. They typically release updates on inflation on a regular basis.
2. How to calculate inflation rate?
The inflation rate can be calculated using the Consumer Price Index (CPI). The CPI is a measure of the average change over time in the prices paid by consumers for a basket of goods and services. To calculate the inflation rate, the following formula can be used:
Inflation rate = (CPI in current period – CPI in base period) / CPI in base period * 100
For example, if the CPI in the current period is 110 and the CPI in the base period is 100, the inflation rate would be (110 – 100) / 100 * 100 = 10%. This means that prices have increased by 10% over the base period.
It’s also worth noting that there’s different types of inflation measures, like the Producer Price Index (PPI) that measure the average change over time in the prices received by domestic producers for their output.
3. What was the inflation rate under Trump?
4. What is the inflation rate in Italy?
5. What was the 2022 inflation rate?
Top trending questions on “inflation”, past day, US
Inflation is the rate at which the general level of prices for goods and services is rising and subsequently, purchasing power is falling. It is measured as an annual percentage increase. Central banks and governments use different measures to calculate inflation, such as the Consumer Price Index (CPI) or the Producer Price Index (PPI).
Inflation occurs when there is an increase in the money supply and a decrease in the demand for goods and services. When the supply of money increases, the value of money decreases, and prices of goods and services go up. This decrease in purchasing power causes inflation.
Inflation can have both positive and negative effects on an economy and people. Moderate inflation can be a sign of a growing and healthy economy, as it can signal increased demand for goods and services. However, high and persistent inflation can lead to economic instability and can harm the purchasing power of people, particularly those on fixed incomes.
Central banks and governments use different tools to control and stabilize inflation. These tools include setting interest rates, adjusting money supply, and implementing fiscal policies such as taxation, government spending and regulations.
It’s worth noting that, while inflation is usually measured by the increase in the general price level, there are different types of inflation such as cost-push, demand-pull and built-in inflation each with different causes and effects on the economy.
Inflation is caused by an overall increase in the level of prices in an economy. There are several factors that can contribute to inflation, including:
Demand-pull inflation: This occurs when there is an increase in demand for goods and services that outpaces the growth in supply. This can lead to higher prices as businesses try to meet the increased demand.
Cost-push inflation: This occurs when the cost of production increases, such as an increase in the cost of raw materials or wages. Businesses will pass these increased costs onto consumers in the form of higher prices.
Monetarism: This occurs when there is an increase in the money supply that outpaces the growth in the economy. This can lead to more money chasing the same amount of goods, driving up prices.
Built-in inflation: This is the increase in prices that is built into the economy due to past inflation. Businesses and workers may expect prices to rise, and therefore increase wages and prices to keep pace with inflation.
Structural inflation: This occurs when there is a mismatch between supply and demand due to structural changes in the economy. For example, a natural disaster that disrupts production or a sudden increase in the price of oil can lead to inflation.
It’s worth noting that inflation can be caused by a combination of different factors and can also vary in different countries and regions.
3. When is inflation data released?
4. Is inflation slowing down?
5. What is the current inflation rate?
6. When will inflation go down?
Top trending questions on “eggs”, past day, US
2. How long to boil eggs?
3. Why is there an egg shortage?
4. How to boil eggs?
5. How much protein is in an egg? 13 g
Top trending “price of…”, past day, US
1. Price of eggs
2. Price of gold
3. Price of silver
4. Price of bitcoin
5. Price of oil
Top questions on Flight cancellation and delay, past week, US:
1. How long flight delay before compensation?
2. How to get compensation for delayed flight?
3. What is NOTAM? Notice TO AIRMEN
4. Why are there flight delays?
5. What is FAA system?”
Prince Harry
Over the past day, Prince Harry’s memoir, Spare, was the top trending book in the US.
The top trending interview over the past 7 days is “Harry interview Michael Strahan” in the US.
Americans searching for Taliban over the past 7 days are also searching for Prince Harry after the author wrote about his time in the military.
Trending questions about or revealed from Spare, past day, US
What is a biro in England? Pen
How much is Prince Harry’s book? Hardcover: Amazon, $32 · Walmart, $33 · Chapters-Indigo, $35 ; Paperback: Amazon, $50
What does spare mean to Prince Harry? Prince Harry nods to the old adage, “an heir and spare” referring to the tradition of aristocratic families having at least two children; first “an heir” to the title and then a “spare” to bolster the family line, just in case
Trending types of loan calculators, past 7 days, US
Trending “should I consolidate…” past 7 days, US
Should I consolidate Student loans?
Consolidating student loans can be a good option for some borrowers, but it may not be the best choice for everyone. Here are a few things to consider when deciding whether to consolidate your student loans:
Interest rates: If you have multiple student loans with different interest rates, consolidating them into a single loan may lower your overall interest rate. This can help you save money on interest over the life of the loan.
Repayment terms: Consolidating your student loans may also allow you to extend your repayment term, which can lower your monthly payments. However, keep in mind that this will also increase the total amount of interest you pay over the life of the loan.
Eligibility: Not all student loans are eligible for consolidation, so it’s important to check with your loan servicer to see if your loans qualify.
Flexibility: Consolidating your student loans may limit your options for loan forgiveness or income-driven repayment plans. It’s important to weigh these options and see what works best for you.
Fees: Consolidation may come with fees, it’s important to weigh the benefits of consolidation against the cost of the fees.
It’s also worth noting that consolidation may also have negative effects on your credit score, so it’s recommended to consult with a financial advisor or loan servicer before making a decision.
Should I consolidate Retirement accounts
Should I consolidate Parent plus loans
Should I consolidate Credit card debt
Should I consolidate 401k
Shakira and Bizarrap collaborate on an explosive new song, leading their music session to become the top trending “lyrics” over the past day in the US.
Searches for “Naomi Osaka” climbed by +1,750% in the US after the tennis star announced her pregnancy.
Tatjana Patitz, a 90s supermodel who appeared in George Michael’s iconic “Freedom! ’90” music video, passed away at 56. Over the past day, her native Germany hads the highest search interest in the supermodel, followed by Austria and Luxembourg.
British rock guitarist, Jeff Beck dies at 78. Across the globe, he was searched most in his native United Kingdom, followed by the United States and Canada over the past day. In that same time frame, “blow by blow” became his top trending album and “freeway jam” his top trending song worldwide.
The Mega Millions prize money reached its second highest jackpot ever this week. Over the past day, Wisconsin became the state with the highest search interest in Mega Millions, followed by New Hampshire and Delaware.
Consumer Debt
Over the past 7 days, Americans are searching for credit card debt 1.5x more than student debt.
US searches for “How to pay off credit card debt” reached a five-year high within the past month.
The second top-searched “snowball” in the US over the past 7 days is “debt snowball”
The second top-searched “how to get out of…” over the past 7 days is “how to get out of debt”, just behind “how to get out of jury duty”
Golden Globes • FA Cup • Mediterranean Diet
Golden Globes
Avatar: The Way of Water and Everything Everywhere All at Once are the most searched Golden Globe nominees for Best Picture, Drama and Best Picture, Musical or Comedy
Most searched celebrities on the red carpet, past four hours, US
Most searched acceptance speeches, past four hours, US
FA Cup
Global search interest in FA Cup spikes annually in January. Uganda is the country with the highest search interest since the 2022-2023 tournament began in August 2022
Josh Windass is a breakout topic following this weekend’s Newcastle game and “is josh windass related to dean windass
Mediterranean Diet
Myocardial infarction (heart attack)
Strained yogurt (Greek yogurt)
Most searched “mediterranean diet for…” health reasons, past month, US
Mediterranean diet for Arthritis:
The Mediterranean diet is a dietary pattern that is rich in fruits, vegetables, whole grains, lean protein, and healthy fats, and it has been shown to be beneficial for people with arthritis.
Some specific foods and nutrients that may be particularly beneficial for people with arthritis include:
Fish: Fish such as salmon, tuna, and sardines are rich in omega-3 fatty acids, which have anti-inflammatory properties.
Fruits and vegetables: Fruits and vegetables are rich in antioxidants, which can help to reduce inflammation. Some particularly good options include berries, tomatoes, leafy greens, and cruciferous vegetables like broccoli and cauliflower.
Nuts and seeds: Nuts and seeds such as almonds, walnuts, and flaxseed are a great source of healthy fats and can also provide anti-inflammatory benefits.
Olive oil: Olive oil is a staple of the Mediterranean diet, and it is a good source of monounsaturated fats which can help to reduce inflammation.
Whole grains: Whole grains such as quinoa, barley, and whole wheat bread are a great source of fiber and have anti-inflammatory properties.
Herbs and spices: Herbs and spices such as turmeric, ginger, and garlic are great sources of anti-inflammatory compounds.
Moderate amount of red meat and processed meat should be avoided as they contain high level of saturated fat.
It’s also important to note that the Mediterranean diet is not only about the foods you eat, but also about the way of eating. It encourages a way of eating that is relaxed, social, and often involves shared meals.
It’s always best to consult with a healthcare professional, a dietitian, or a nutritionist before making any significant dietary changes, especially if you have any underlying health condition or taking any medication.
Best Mediterranean diet for Pregnancy:
Here are a few key components of the Mediterranean diet that can be beneficial for pregnant women:
Fruits and vegetables: These foods are rich in vitamins, minerals, and antioxidants that are important for both the mother and the developing baby. Eating a variety of fruits and vegetables can help ensure that pregnant women get the nutrients they need.
Whole grains: Whole grains are a good source of fiber and B vitamins, which are important for a healthy pregnancy. Whole grains also have a lower glycemic index than refined grains, which can help keep blood sugar levels steady.
Fish and seafood: Fish and seafood are rich in omega-3 fatty acids, which are important for the development of the baby’s brain and eyes. Pregnant women should aim to eat at least two servings of fish per week, but should avoid certain types of fish that are high in mercury, such as swordfish and tilefish.
Healthy fats: Olive oil, avocado, and nuts are all good sources of healthy fats that can help support a healthy pregnancy.
Iron: Iron is essential for the development of the baby’s blood cells. Legumes and leafy greens are a good source of iron.
It’s worth noting that pregnant women should avoid certain foods such as raw fish, deli meats, and soft cheeses, as they may contain bacteria that can harm the developing baby. It’s always recommended to consult with a dietitian or a physician to create a personalized plan that fits your nutritional needs and health conditions.
Mediterranean diet for High cholesterol:
The Mediterranean diet has been shown to be effective in reducing high cholesterol levels. This diet is characterized by a high intake of fruits, vegetables, whole grains, legumes, nuts, and seeds, and a moderate intake of fish and seafood. It also includes healthy fats, such as olive oil and avocado, and a moderate intake of red wine.
The Mediterranean diet emphasizes the consumption of monounsaturated fats, which have been shown to reduce LDL (bad) cholesterol levels and increase HDL (good) cholesterol levels. The diet is also low in saturated fats, which have been linked to increased cholesterol levels.
The Mediterranean diet also includes foods that are high in fiber, such as fruits, vegetables, and whole grains. Fiber can help lower cholesterol levels by binding with bile acids, which are made from cholesterol, and carrying them out of the body.
Eating fish, especially fatty fish like salmon, mackerel, and sardines, is a key feature of Mediterranean diet. These fish are rich in omega-3 fatty acids, which have been shown to help lower triglycerides and reduce the risk of heart disease.
Additionally, the Mediterranean diet is rich in antioxidants, which can help reduce inflammation in the body, which has been linked to an increased risk of heart disease. It’s worth noting that there’s no one-size-fits-all approach, therefore, it’s recommended to consult with a dietitian or a physician to create a personalized plan that fits your nutritional needs and health conditions.
Most searched recipes related to Mediterranean diet, past month, US
College Football National Championship
Top searched players during the game, US
Stetson Bennett, Georgia
Brock Bowers, Georgia
Max Duggan, TCU
Ladd McConkey, Georgia
Carson Beck, Georgia
Trending questions on Georgia Bulldogs football, past day, US
Who did Georgia beat last year?
What stadium is Georgia playing at today?
Who is favored to win TCU vs Georgia?
How many times has Georgia won the national championship?
What is the spread for the Georgia game?
Trending questions on TCU Horned Frogs football, past day, US
Why are TCU the horned frogs?
Where are Georgia and TCU playing?
What conference is TCU in football?
When did TCU last win the national championship?
Where is the TCU football team from?
Mental Health
Over the last 2 years, Monday was the day with the highest search for depression than any other day in the US
Personal Goals and Health
debt free Tips
Top trending questions on New Year’s Resolutions, past week, US
What is a New Year’s resolution?
What is a New Year’s resolution for kids?
What does resolution mean?
What is a good New Year’s resolution? Lose weight, stop drinking, save money
What is the most popular New Year’s resolution? Saving more money
- The 2010 children’s book, Squirrel new year resolution
Top trending “how to…” searches related to Personal Finances, past week, US
Personal Health
Top trending “how to…” searches related to Physical Fitness, past week, US
How to improve cardio fitness?
Improving cardio fitness involves increasing the strength and efficiency of your heart, lungs, and blood vessels. Here are a few ways to improve cardio fitness:
Aerobic exercise: Engage in regular aerobic activities such as running, cycling, swimming, or brisk walking, as these activities will increase your heart rate and improve your lung function. Aim for at least 150 minutes of moderate-intensity aerobic activity or 75 minutes of vigorous-intensity aerobic activity per week, according to the physical activity guidelines for Americans.
High-Intensity Interval Training (HIIT): This type of training involves short, intense bursts of activity followed by a recovery period. It is known to be more effective than steady-state cardio in improving cardiovascular fitness.
Resistance Training: Resistance training helps to improve cardiovascular fitness by increasing muscle mass and improving the body’s ability to use oxygen. This type of training includes exercises such as weightlifting, calisthenics, and bodyweight exercises.
Yoga and stretching: Yoga and stretching can help to improve cardiovascular fitness by increasing flexibility, balance, and breathing.
Monitor your heart rate: Keep track of your heart rate during exercise to ensure that you’re working at the right intensity level.
Consistency: Regular exercise is key to improving cardiovascular fitness, so it’s important to make it a part of your weekly routine.
Adequate rest: Give your body enough time to recover from intense workouts to prevent overtraining and injury.
It’s important to consult with a healthcare professional or a trainer before starting any new exercise program, especially if you have any underlying health condition. They can help you to determine the best type and intensity of exercise for your fitness level and goals.
How to take body measurements for fitness?
Taking body measurements is a useful tool for tracking your progress and monitoring changes in your body composition as you work towards your fitness goals. Here are a few steps to follow when taking body measurements:
Gather your tools: You will need a tape measure, a pen, and a notebook or a measuring tape app on your phone.
Measure your body in several places: Common measurement areas include the chest, waist, hips, thighs, upper arms, and calves.
Take measurements in the same place every time: It’s important to measure the same area of your body each time, so you can track changes over time.
Measure at the same time of day: Try to measure at the same time of day, as your measurements can be affected by factors such as hydration levels and digestion.
Take measurements standing: Stand up straight and breathe normally when measuring, as this will give you the most accurate measurements.
Record your measurements: Write down your measurements in a notebook or in a fitness tracking app, so you can track your progress over time.
Repeat measurements every 4-6 weeks: It’s useful to repeat measurements every 4-6 weeks to monitor any changes in your body composition.
It’s important to note that body measurements are not the only way to track your fitness progress, it’s also important to pay attention to how you feel, how your clothes fit, and how your performance improves in physical activities.
It’s always best to consult with a healthcare professional, a personal trainer, or a nutritionist before making any significant changes to your diet or exercise routine, especially if you have any underlying health condition.
How to maintain a healthy weight?
Maintaining a healthy weight is important for overall health and wellness. Here are a few ways to maintain a healthy weight:
Eat a balanced diet: A healthy diet should include a variety of nutrient-dense foods such as fruits, vegetables, whole grains, lean protein, and healthy fats. Avoid processed foods, sugary drinks, and excessive amounts of saturated and trans fats.
Watch your portion sizes: Eating smaller portions can help you to manage your calorie intake and maintain a healthy weight.
Be active: Engage in regular physical activity, such as brisk walking, cycling, swimming, or running. The Physical Activity Guidelines for Americans recommend at least 150 minutes of moderate-intensity aerobic activity or 75 minutes of vigorous-intensity aerobic activity per week for adults.
Avoid fad diets: Crash diets or fad diets that promise rapid weight loss are often not sustainable in the long term, and can be harmful to your health.
Get enough sleep: Adequate sleep is important for weight management, as lack of sleep can lead to weight gain and obesity.
Manage stress: High levels of stress can lead to overeating and weight gain, so it’s important to find healthy ways to manage stress such as yoga, meditation, or talking to a therapist.
Keep track of your progress: Use a journal or an app to track your food intake and physical activity, it will help you to stay on track and make adjustments as needed.
It’s important to note that weight management is different for each individual and it’s not always about weight loss. It’s about reaching and maintaining a healthy weight for your body type, age, and overall health. It’s always best to consult with a healthcare professional, a dietitian, or a nutritionist before making any significant changes to your diet or exercise routine.
Golden Globes
Top searched nominated Golden Globe TV shows
Top searched Golden Globe dresses since 2004
House Speaker
Top questions on speaker of the House, US
Who is the speaker of the house in 2023?
How many votes are needed to become speaker of the house? [Majority of members elect]
Top why questions on speaker of the House, past day, US
Minimum Wage
When does the federal pay raise take effect:
The federal pay raise is typically announced by the President in the budget proposal and then must be passed by Congress. The exact timing of when a federal pay raise would take effect would depend on the specifics of the proposal and the legislative process.
It’s worth noting that the federal pay raise could be different each year and also could depend on the budget availability, economic conditions, and political considerations. It’s recommended to check for updates on the official government websites or consult with the human resources department of your agency for more information.
Asking for a raise can be nerve-wracking, but it’s important to remember that you deserve to be compensated fairly for your work. Here are a few tips to help you prepare for a conversation with your manager about a raise:
Research: Look up the average salary for your position in your area and industry. This will give you a benchmark to use when discussing your salary with your manager.
Prepare a case: Make a list of your accomplishments and contributions to the company. Be specific and use data and examples to show how you have added value to the company.
Choose the right time: Timing is important when asking for a raise. Try to schedule your meeting when your manager is less busy and more likely to have time for a thoughtful conversation.
Practice: Rehearse what you want to say so you feel more confident during the meeting.
Be professional: During the meeting, be calm, polite, and professional. Avoid getting emotional or confrontational.
Be open to negotiation: Be prepared to discuss different options, such as a raise or other benefits like additional vacation days or flexible working hours.
It’s important to remember that the answer may not be yes immediately or in the amount you expect, but it is important to express your value and worth to the company. Also, it’s recommended to check your company’s policies or guidelines regarding pay raises and performance evaluations.
Most searched “how does raising minimum wage/increase in minimum wage affect…”, past week, US
How does raising minimum wage affect Small businesses?
Raising the minimum wage can have both positive and negative effects on small businesses.
On the positive side, raising the minimum wage can lead to increased consumer spending, as workers will have more money to spend on goods and services. This can lead to increased sales and revenue for small businesses. Additionally, raising the minimum wage can also lead to decreased employee turnover and recruitment costs, as workers will be more satisfied with their wages.
On the negative side, raising the minimum wage can lead to increased labor costs for small businesses. This can be a significant burden for small businesses with tight profit margins, as they may not have the financial resources to absorb the increased costs. As a result, some small businesses may be forced to reduce their workforce, reduce employee hours, or raise prices to offset the increased labor costs.
It’s also worth noting that the effects of raising the minimum wage can vary depending on the specific industry and location. For example, small businesses in high-cost areas may be more affected by a minimum wage increase than those in low-cost areas.
It’s important to note that the effects of raising the minimum wage are not clear cut and there are arguments for and against it. It’s important for policymakers to consider the potential effects on small businesses when making decisions about the minimum wage. It’s also important for small business owners to stay informed about potential changes to the minimum wage and plan accordingly.
How does raising minimum wage affect the economy?
How does raising minimum wage affect quantity demanded?
How does raising minimum wage affect cost of living?
How does raising minimum wage affect Inflation?
Top why questions on minimum wage, past week, US
Minimum wage laws were created to protect workers from being exploited by employers. The idea behind a minimum wage is to ensure that workers are paid a fair wage for their labor. Without a minimum wage, employers could pay workers very low wages, which would make it difficult for them to make ends meet.
The first minimum wage law was passed in New Zealand in 1894, followed by Australia in 1896. The United States passed its first federal minimum wage law, the Fair Labor Standards Act (FLSA), in 1938. The FLSA established a minimum wage of 25 cents per hour for covered workers.
The purpose of the FLSA was to reduce poverty and inequality by ensuring that workers were paid a fair wage. It aimed to achieve this by setting a minimum wage that would provide workers with enough money to meet their basic needs. Additionally, it was created to reduce competition among workers for jobs by preventing employers from undercutting each other by paying lower wages, which would benefit employees and employers.
Minimum wage laws have been updated and changed over time, reflecting the changes in the economy and the cost of living. The current federal minimum wage in the United States is $7.25 per hour, but many states and municipalities have set their own higher minimum wage rates.
It’s worth noting that there’s ongoing debate on the effects of minimum wage on employment, with some arguments saying it could lead to job loss and others stating it could increase purchasing power and reduce poverty.
Contact Sports
What is… searches are related to Damar Hamlin.
Commotio cordis is a type of sudden cardiac arrest that occurs as a result of a blow to the chest, typically from a blunt object such as a ball or a puck. The blow causes the heart to momentarily stop beating properly, leading to a loss of consciousness and cardiac arrest. It most commonly occurs in young athletes and it’s most common in baseball, hockey, and lacrosse.
Commotio cordis is caused by a specific type of heart rhythm disturbance called ventricular fibrillation. Ventricular fibrillation is a chaotic, ineffective contraction of the ventricles (the lower chambers of the heart) that prevents the heart from pumping blood effectively.
Commotio cordis is a very rare condition and it’s estimated that it occurs in 1 out of every 50,000 to 80,000 athletes who participate in chest-contact sports. However, when it happens, it’s often fatal if not treated immediately with CPR and defibrillation.
There are steps that can be taken to prevent commotio cordis, such as wearing chest protectors and using safer equipment. It’s also crucial for those who participate in sports to learn CPR, and for organizations to have defibrillators available at events.
It’s important to note that if a person has a blow to the chest, and they lose consciousness or show any other signs of cardiac arrest, emergency medical services should be called immediately.
Steph Curry injury
Alex Smith injury
does the speaker of the house have to be from the majority party
The death of drummer, Jeremiah Green.
Float On” is the top searched song of all time by Modest Mouse
Most searched “is…a contact sport”
Is basketball a contact sport? Limited Contact
Is soccer a contact sport? Limited Contact
Is baseball a contact sport? Tagging only
Is lacrosse a contact sport? Limited contact
Is volleyball a contact sport? Tagging
Top questions related to the NFL, past day, US
What happened to Damar Hamlin? cardiac Arrest
What is cardiac arrest?
Cardiac arrest is a serious medical emergency that occurs when the heart stops pumping blood effectively to the body. It is caused by an electrical malfunction in the heart, which can lead to an abnormal heart rhythm called ventricular fibrillation. When this happens, the heart is unable to pump blood effectively and the person will lose consciousness and stop breathing. If left untreated, cardiac arrest can lead to brain damage and death within minutes.
There are several different causes of cardiac arrest, including heart attack, trauma, drowning, electrocution, and drug overdose. In some cases, the person may have an underlying heart condition that increases their risk of cardiac arrest.
Cardiac arrest is different from a heart attack, which is a circulation problem caused by a blocked blood flow to the heart. A heart attack can lead to cardiac arrest but not always.
The most important treatment for cardiac arrest is immediate CPR and defibrillation to restore the normal heart rhythm. Early recognition and treatment of cardiac arrest is crucial to increase the chances of survival.
It’s important to note that if someone is suspected of having a cardiac arrest, emergency medical services should be called immediately and CPR should be started right away if the person is unresponsive and not breathing. If a defibrillator is available, it should be used as soon as possible.
Who got injured in football today? Damar Hamlin
Why was the Bills game suspended? Damar Hamlin cardiac arrest during the game
What happens when a NFL game is suspended? It gets rescheduled or cancelled
CES
South Korea is searching for CES
The Day Before is the top trending game and Sony BRAVIA X85J is the top trending TV related to CES
Winter storms Trends
Create a flood emergency plan: Identify potential evacuation routes and shelter areas, and make sure everyone in your household knows what to do in case of a flood.
Elevate important items: elevate furniture and appliances that may be damaged by floodwater.
Seal basement walls: install a sealant or waterproofing membrane on basement walls to prevent water from entering.
Install a sump pump: if your basement is prone to flooding, a sump pump can help remove water from the area.
Keep sandbags on hand: Sandbags can be used to block water from entering your home.
Have a flood insurance: check your insurance policy to make sure you have adequate coverage for flood damage.
Be aware of flood-prone areas: know the areas in your community that are prone to flooding, and avoid these areas during heavy rainfall.
Keep an emergency kit: keep an emergency kit with essentials such as food, water, and flashlights in case you need to evacuate your home.
Keep important documents safe: Keep important documents such as ID cards, insurance papers, and emergency contact information in a safe and easily accessible place.
Keep your phone charged and have a way to charge it: Keep your phone charged, and have a way to charge it in case of power outages.
Keep a supply of rock salt, sand, or cat litter to create traction on walkways and driveways.
Insulate pipes: wrap pipes with insulation or newspapers and allow faucets to drip during freezing temperatures to prevent pipes from bursting.
Keep a supply of emergency heating sources such as firewood, portable heaters, and blankets.
Have a plan to keep warm: in case of a power outage, know where you can go to keep warm.
Keep a supply of non-perishable food and water in case you are unable to leave your home.
Make sure your car is winterized: Keep your gas tank at least half full, check your brakes, tires, battery, and windshield wipers.
Keep a winter emergency car kit, including blankets, a flashlight, and an ice scraper.
Keep a battery-powered radio on hand: Listen to weather updates and alerts.
Keep your phone charged: Keep your phone charged in case you need to call for help.
Be aware of the weather forecast: Stay informed about upcoming storms, and take necessary precautions.
How to prepare for a power outage
Create an emergency kit: Include items such as flashlights, batteries, a manual can opener, non-perishable food, and water.
Have backup power sources: Consider purchasing a generator or a portable power bank for charging devices.
Keep important documents safe: Keep important documents such as ID cards, insurance papers, and emergency contact information in a safe and easily accessible place.
Keep your fridge and freezer closed: This will help to keep food fresh for longer in case of a power outage.
Charge devices before an outage: Charge your phone, tablet, and other devices before a power outage so that you can use them if needed.
Keep extra cash on hand: In case of power outages, ATMs and credit card machines may not be able to process transactions.
Have a plan for communication: Make sure everyone in your household knows how to contact each other in case of an emergency.
Know how to manually operate essential equipment: Learn how to manually operate essential equipment such as your garage door and security system.
Familiarize yourself with utility company’s emergency plan: Contact your utility company to know their emergency plan and how they will inform you about power outages and when power will be restored.
Have a backup plan for medical needs: If you or a family member relies on powered medical equipment, make sure you have a backup plan in case of a power outage.
Top trending weather related “how to…”
Stay indoors: Stay inside as much as possible to avoid the dangerous conditions outside.
Prepare food and water: Stock up on non-perishable food and water supplies in case you get stuck at home for a few days.
Dress in layers: Wear multiple layers of clothing to stay warm and remove layers as needed to prevent overheating.
Stay warm: Keep your home warm by closing windows and doors, using blankets, and taking advantage of alternative heating sources if necessary.
Avoid travel: If you must travel, do so only if absolutely necessary and take your time. Use a shovel to clear a path if necessary and make sure your car is equipped with winter safety gear.
Keep a disaster supply kit: Make sure you have a disaster supply kit with essentials like flashlights, batteries, and a battery-operated radio.
Stay informed: Stay informed about weather conditions and any changes in the storm by listening to the radio or television, or checking online weather websites.
How to dry lightning connectors?
To dry a lightning connector, you can try the following steps:
Disconnect the lightning cable from any device or power source and leave it unplugged for a few hours to allow it to air dry.
Gently shake the cable to remove any excess moisture, then use a soft cloth to wipe the connector and remove any visible water droplets.
Place the lightning connector in a warm, dry place, away from direct heat sources or damp areas. You can use a fan or a small portable heater to help speed up the drying process.
If the lightning connector still does not work after a few hours, you may need to consider using a dryer or a desiccant bag, such as silica gel, to absorb any remaining moisture.
Note: It’s important to be patient and not force the cable into a device while it’s still wet, as this could cause damage to the device or the cable.
Driving in snow can be challenging but by following these steps, you can stay safe on the road:
Slow down: Snow and ice can reduce visibility and traction, so slow down and allow extra time to reach your destination.
Accelerate and decelerate slowly: Sudden acceleration or deceleration can cause the wheels to spin and lose traction.
Use lower gears: Use lower gears to help maintain traction when driving up or down hills.
Increase following distance: Snow and ice can reduce visibility and stopping distance, so increase the distance between your vehicle and the one in front of you.
Avoid sudden movements: Sudden movements, such as sudden steering or braking, can cause the vehicle to lose traction.
Brake gently: If you have to brake, do it gently and slowly to avoid skidding. If your vehicle has anti-lock brakes, apply steady pressure.
Avoid using cruise control: Cruise control can cause the wheels to spin and reduce traction.
Watch for black ice: Black ice is a thin layer of ice that can form on roads and is difficult to see. Keep an eye out for it, especially in shaded areas or on bridges and overpasses.
Prepare your vehicle: Make sure your vehicle is equipped with snow tires or chains and that the windshield wipers and defrost system are working properly.
By following these steps and taking it slow and steady, you can stay safe while driving in snow.
How to measure humidity at home? To measure humidity at home, you can use a hygrometer, which is a device that measures relative humidity levels. Hygrometers can be found at hardware stores and online, and can be analog or digital. Digital hygrometers are generally more accurate and easier to read, but analog hygrometers are less expensive. To use a hygrometer, simply place it in a room where you want to measure the humidity, and the device will give you a reading. If you want to measure the humidity in a specific area, such as a closet or room, you may want to invest in a more advanced hygrometer with a remote sensor that you can place in the specific area you want to measure.
- What is a polar vortex? A polar vortex is a large area of low pressure and cold air surrounding the Earth’s poles. These air masses can weaken and cause cold Arctic air to spill into lower latitudes, leading to frigid winter weather conditions in normally milder areas. The term “polar vortex” has become more commonly used in recent years due to an increase in instances of these events and their impacts on the mid-latitudes.
Racing in the rain can be a challenge due to reduced visibility and traction. Here are some tips for racing in wet conditions:
Slow down: Wet roads reduce traction, so it’s important to slow down to maintain control of your vehicle.
Maintain a safe distance: Keep a safe distance from the car in front of you to allow for extra stopping time.
Use brakes carefully: Avoid sudden braking or acceleration, which can cause your wheels to lock and lose traction.
Use lower gears: In wet conditions, it’s best to use lower gears when accelerating to maintain traction.
Avoid puddles: Puddles can reduce visibility and hide hazards. If you must drive through a puddle, do so slowly to minimize splashing and maintain control.
Use headlights: Turn on your headlights to improve visibility in the rain.
Stay focused: Stay focused on the road and avoid distractions, such as texting or using your phone.
By following these tips, you can increase your safety and chances of successfully racing in the rain.
7. Healthy meal prep ideas for weight loss – Healthy diet
- Grilled chicken or fish with roasted vegetables
- Turkey chili with black beans and bell peppers
- Vegetable stir-fry with tofu or tempeh
- Lentil and vegetable soup
- Baked salmon with a quinoa or brown rice pilaf
- Whole wheat pasta with marinara sauce and sautéed vegetables
- Turkey or chicken lettuce wraps with a side of sliced fruit
- Black bean and sweet potato enchiladas
- Greek yogurt with mixed berries and a drizzle of honey
- Whole wheat pita stuffed with hummus, vegetables, and a lean protein such as turkey or chicken.
I’m so High, a song by Three 6 Mafia
Penn State Nittany Lions football
Utah Utes football as the two teams go head-to-head in the Rose Bowl
Pele, the GOAT, the only man to win 3 World Cups, has died on December 29th, 2022. RIP PELE.
Remembering Pelé
Madre de pele [Google Translate, Spanish: mother of Pelé]
Que edad tiene la madre de pele [Google Translate, Spanish: how old is Pelé’s mother] 100 years old in 2022
Pele’s runaround move: Pele’s runaround move, also known as the “rainbow flick,” was a skillful move used by the Brazilian soccer player Pele during his career. The move involves the player lifting one leg, and using the other leg to control the ball and flick it over the opponent’s head. This move is considered to be quite difficult to execute and requires a high level of ball control and balance. Pele was known to use this move to great effect, catching many defenders off guard and leaving them behind. The move is considered to be one of Pele’s most iconic and memorable moments in the history of soccer.
Pele is the nickname of Edson Arantes do Nascimento, a Brazilian soccer player who is widely considered one of the greatest players of all time. He was given the nickname “Pele” at a young age by his schoolmates, who decided to call him after the American inventor and businessman Thomas Edison. The nickname was later shortened to “Pele,” and he became known by this name throughout his career.
Pele is considered one of the greatest soccer players of all time due to his impressive skills, speed, and goal-scoring ability. He won three World Cup titles with the Brazilian national team and scored a total of 1,281 goals in his career, a record that still stands today. Pele was also known for his sportsmanship and leadership on and off the field, and he has been recognized with numerous awards and accolades throughout his career.
Most searched Pelé goals on Youtube, all time, worldwide
El último gol de Pelé [ the last goal of Pelé]
El último gol de Pelé con Brasil [Pelé’s last goal with Brazil]
What is Problem Formulation in Machine Learning and Top 4 examples of Problem Formulation in Machine Learning?


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What is Problem Formulation in Machine Learning and Top 4 examples of Problem Formulation in Machine Learning?
Machine Learning (ML) is a field of Artificial Intelligence (AI) that enables computers to learn from data, without being explicitly programmed. Machine learning algorithms build models based on sample data, known as “training data”, in order to make predictions or decisions, rather than following rules written by humans. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also focuses on prediction-making through the use of computers. Machine learning can be applied in a wide variety of domains, such as medical diagnosis, stock trading, robot control, manufacturing and more.

The process of machine learning consists of several steps: first, data is collected; then, a model is selected or created; finally, the model is trained on the collected data and then applied to new data. This process is often referred to as the “machine learning pipeline”. Problem formulation is the second step in this pipeline and it consists of selecting or creating a suitable model for the task at hand and determining how to represent the collected data so that it can be used by the selected model. In other words, problem formulation is the process of taking a real-world problem and translating it into a format that can be solved by a machine learning algorithm.

There are many different types of machine learning problems, such as classification, regression, prediction and so on. The choice of which type of problem to formulate depends on the nature of the task at hand and the type of data available. For example, if we want to build a system that can automatically detect fraudulent credit card transactions, we would formulate a classification problem. On the other hand, if our goal is to predict the sale price of houses given information about their size, location and age, we would formulate a regression problem. In general, it is best to start with a simple problem formulation and then move on to more complex ones if needed.
Some common examples of problem formulations in machine learning are:
– Classification: given an input data point (e.g., an image), predict its category label (e.g., dog vs cat).
– Regression: given an input data point (e.g., size and location of a house), predict a continuous output value (e.g., sale price).
– Prediction: given an input sequence (e.g., a series of past stock prices), predict the next value in the sequence (e.g., future stock price).
– Anomaly detection: given an input data point (e.g., transaction details), decide whether it is normal or anomalous (i.e., fraudulent).
– Recommendation: given information about users (e.g., age and gender) and items (e.g., books and movies), recommend items to users (e.g., suggest books for someone who likes romance novels).
– Optimization: given a set of constraints (e.g., budget) and objectives (e.g., maximize profit), find the best solution (e.g., product mix).

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Problem Formulation: What this pipeline phase entails and why it’s important
The problem formulation phase of the ML Pipeline is critical, and it’s where everything begins. Typically, this phase is kicked off with a question of some kind. Examples of these kinds of questions include: Could cars really drive themselves? What additional product should we offer someone as they checkout? How much storage will clients need from a data center at a given time?
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The problem formulation phase starts by seeing a problem and thinking “what question, if I could answer it, would provide the most value to my business?” If I knew the next product a customer was going to buy, is that most valuable? If I knew what was going to be popular over the holidays, is that most valuable? If I better understood who my customers are, is that most valuable?
However, some problems are not so obvious. When sales drop, new competitors emerge, or there’s a big change to a company/team/org, it can be easy to say, “I see the problem!” But sometimes the problem isn’t so clear. Consider self-driving cars. How many people think to themselves, “driving cars is a huge problem”? Probably not many. In fact, there isn’t a problem in the traditional sense of the word but there is an opportunity. Creating self-driving cars is a huge opportunity. That doesn’t mean there isn’t a problem or challenge connected to that opportunity. How do you design a self-driving system? What data would you look at to inform the decisions you make? Will people purchase self-driving cars?
Part of the problem formulation phase includes seeing where there are opportunities to use machine learning.
In the following practice examples, you are presented with four different business scenarios. For each scenario, consider the following questions:
- Is machine learning appropriate for this problem, and why or why not?
- What is the ML problem if there is one, and what would a success metric look like?
- What kind of ML problem is this?
- Is the data appropriate?’
The solutions given in this article are one of the many ways you can formulate a business problem.
I) Amazon recently began advertising to its customers when they visit the company website. The Director in charge of the initiative wants the advertisements to be as tailored to the customer as possible. You will have access to all the data from the retail webpage, as well as all the customer data.
- ML is appropriate because of the scale, variety and speed required. There are potentially thousands of ads and millions of customers that need to be served customized ads immediately as they arrive to the site.
- The problem is ads that are not useful to customers are a wasted opportunity and a nuisance to customers, yet not serving ads at all is a wasted opportunity. So how does Amazon serve the most relevant advertisements to its retail customers?
- Success would be the purchase of a product that was advertised.
- This is a supervised learning problem because we have a labeled data point, our success metric, which is the purchase of a product.
- This data is appropriate because it is both the retail webpage data as well as the customer data.
II) You’re a Senior Business Analyst at a social media company that focuses on streaming. Streamers use a combination of hashtags and predefined categories to be discoverable by your platform’s consumers. You ran an analysis on unique streamer counts by hashtags and categories over the last month and found that out of tens of thousands of streamers, almost all use only 40 hashtags and 10 categories despite innumerable hashtags and hundreds of categories. You presume the predefined categories don’t represent all the possibilities very well, and that streamers are simply picking the closest fit. You figure there are likely many categories and groupings of streamers that are not accounted for. So you collect a dataset that consists of all streamer profile descriptions (all text), all the historical chat information for each streamer, and all their videos that have been streamed.
- ML is appropriate because of the scale and variability.
- The problem is the content of streamers is not being represented by the existing categories. Success would be naturally grouping the streamers into categories based on content and seeing if those align with the hashtags and categories that are being commonly used. If they do not, then the streamers are not being well represented and you can use these groupings to create new categories.
- There isn’t a specific outcome variable. There’s no target or label. So this is an unsupervised problem.
- The data is appropriate.
III) You’re a headphone manufacturer who sells directly to big and small electronic stores. As an attempt to increase competitive pricing, Store 1 and Store 2 decided to put together the pricing details for all headphone manufacturers and their products (about 350 products) and conduct daily releases of the data. You will have all the specs from each manufacturer and their product’s pricing. Your sales have recently been dropping so your first concern is whether there are competing products that are priced lower than your flagship product.
- ML is probably not necessary for this. You can just search the dataset to see which headphones are priced lower than the flagship, then compare their features and build quality.
IV) You’re a Senior Product Manager at a leading ridesharing company. You did some market research, collected customer feedback, and discovered that both customers and drivers are not happy with an app feature. This feature allows customers to place a pin exactly where they want to be picked up. The customers say drivers rarely stop at the pin location. Drivers say customers most often put the pin in a place they can’t stop. Your company has a relationship with the most used maps app for the driver’s navigation so you leverage this existing relationship to get direct, backend access to their data. This includes latitude and longitude, visual photos of each lat/long, traffic delay details, and regulation data if available (ie- No Parking zones, 3 minute parking zones, fire hydrants, etc.).
- ML is appropriate because of the scale and automation involved. It’s not feasible to drive everywhere and write down all the places that are ok for pickup. However, maybe we can predict whether a location is ok for pickup.
- The problem is drivers and customers are having poor experiences connecting for pickup, which is pushing customers away from the platform.
- Success would be properly identifying appropriate pickup locations so they can be integrated into the feature.
- This is a supervised learning problem even though there aren’t any labels, yet. Someone will have to go through a sample of the data to label where there are ok places to park and not park, giving the algorithms some target information.
- The data is appropriate once a sample of the dataset has been labeled. There may be some other data that could be included too. What about asking UPS for driver stop information? Where do they stop?
In conclusion, problem formulation is an important step in the machine learning pipeline that should not be overlooked or underestimated. It can make or break a machine learning project; therefore, it is important to take care when formulating machine learning problems.”

Step by Step Solution to a Machine Learning Problem – Feature Engineering
Feature Engineering is the act of reshaping and curating existing data to make patters more apparent. This process makes the data easier for an ML model to understand. Using knowledge of the data, features are engineered and tuned to make ML algorithms work more efficiently.
For this problem, imagine a scenario where you are running a real estate brokerage and you want to predict the selling price of a house. Using a specific county dataset and simple information (like the location, total square footage, and number of bedrooms), let’s practice training a baseline model, conducting feature engineering, and tuning a model to make a prediction.
First, load the dataset and take a look at its basic properties.
# Load the dataset
import pandas as pd
import boto3
df = pd.read_csv(“xxxxx_data_2.csv”)
df.head()

Output:

This dataset has 21 columns:
id
– Unique id numberdate
– Date of the house saleprice
– Price the house sold forbedrooms
– Number of bedroomsbathrooms
– Number of bathroomssqft_living
– Number of square feet of the living spacesqft_lot
– Number of square feet of the lotfloors
– Number of floors in the housewaterfront
– Whether the home is on the waterfrontview
– Number of lot sides with a viewcondition
– Condition of the housegrade
– Classification by construction qualitysqft_above
– Number of square feet above groundsqft_basement
– Number of square feet below groundyr_built
– Year builtyr_renovated
– Year renovatedzipcode
– ZIP codelat
– Latitudelong
– Longitudesqft_living15
– Number of square feet of living space in 2015 (can differ fromsqft_living
in the case of recent renovations)sqrt_lot15
– Nnumber of square feet of lot space in 2015 (can differ fromsqft_lot
in the case of recent renovations)
This dataset is rich and provides a fantastic playground for the exploration of feature engineering. This exercise will focus on a small number of columns. If you are interested, you could return to this dataset later to practice feature engineering on the remaining columns.
A baseline model
Now, let’s train a baseline model.
People often look at square footage first when evaluating a home. We will do the same in the oflorur model and ask how well can the cost of the house be approximated based on this number alone. We will train a simple linear learner model (documentation). We will compare to this after finishing the feature engineering.
import sagemaker
import numpy as np
from sklearn.model_selection import train_test_split
import time
t1 = time.time()
# Split training, validation, and test
ys = np.array(df[‘price’]).astype(“float32”)
xs = np.array(df[‘sqft_living’]).astype(“float32”).reshape(-1,1)
np.random.seed(8675309)
train_features, test_features, train_labels, test_labels = train_test_split(xs, ys, test_size=0.2)
val_features, test_features, val_labels, test_labels = train_test_split(test_features, test_labels, test_size=0.5)
# Train model
linear_model = sagemaker.LinearLearner(role=sagemaker.get_execution_role(),
instance_count=1,
instance_type=’ml.m4.xlarge’,
predictor_type=’regressor’)
train_records = linear_model.record_set(train_features, train_labels, channel=’train’)
val_records = linear_model.record_set(val_features, val_labels, channel=’validation’)
test_records = linear_model.record_set(test_features, test_labels, channel=’test’)
linear_model.fit([train_records, val_records, test_records], logs=False)
sagemaker.analytics.TrainingJobAnalytics(linear_model._current_job_name, metric_names = [‘test:mse’, ‘test:absolute_loss’]).dataframe()
If you examine the quality metrics, you will see that the absolute loss is about $175,000.00. This tells us that the model is able to predict within an average of $175k of the true price. For a model based upon a single variable, this is not bad. Let’s try to do some feature engineering to improve on it.
Throughout the following work, we will constantly be adding to a dataframe called encoded
. You will start by populating encoded
with just the square footage you used previously.
encoded = df[[‘sqft_living’]].copy()
Categorical variables
Let’s start by including some categorical variables, beginning with simple binary variables.
The dataset has the waterfront
feature, which is a binary variable. We should change the encoding from 'Y'
and 'N'
to 1
and 0
. This can be done using the map
function (documentation) provided by Pandas. It expects either a function to apply to that column or a dictionary to look up the correct transformation.
Binary categorical
Let’s write code to transform the waterfront
variable into binary values. The skeleton has been provided below.
encoded[‘waterfront’] = df[‘waterfront’].map({‘Y’:1, ‘N’:0})
You can also encode many class categorical variables. Look at column condition
, which gives a score of the quality of the house. Looking into the data source shows that the condition can be thought of as an ordinal categorical variable, so it makes sense to encode it with the order.
Ordinal categorical
Using the same method as in question 1, encode the ordinal categorical variable condition
into the numerical range of 1 through 5.
encoded[‘condition’] = df[‘condition’].map({‘Poor’:1, ‘Fair’:2, ‘Average’:3, ‘Good’:4, ‘Very Good’:5})
A slightly more complex categorical variable is ZIP code. If you have worked with geospatial data, you may know that the full ZIP code is often too fine-grained to use as a feature on its own. However, there are only 7070 unique ZIP codes in this dataset, so we may use them.
However, we do not want to use unencoded ZIP codes. There is no reason that a larger ZIP code should correspond to a higher or lower price, but it is likely that particular ZIP codes would. This is the perfect case to perform one-hot encoding. You can use the get_dummies
function (documentation) from Pandas to do this.
Nominal categorical
Using the Pandas get_dummies
function, add columns to one-hot encode the ZIP code and add it to the dataset.
encoded = pd.concat([encoded, pd.get_dummies(df[‘zipcode’])], axis=1)
In this way, you may freely encode whatever categorical variables you wish. Be aware that for categorical variables with many categories, something will need to be done to reduce the number of columns created.
One additional technique, which is simple but can be highly successful, involves turning the ZIP code into a single numerical column by creating a single feature that is the average price of a home in that ZIP code. This is called target encoding.
To do this, use groupby
(documentation) and mean
(documentation) to first group the rows of the DataFrame by ZIP code and then take the mean of each group. The resulting object can be mapped over the ZIP code column to encode the feature.
Nominal categorical II
Complete the following code snippet to provide a target encoding for the ZIP code.
means = df.groupby(‘zipcode’)[‘price’].mean()
encoded[‘zip_mean’] = df[‘zipcode’].map(means)
Normally, you only either one-hot encode or target encode. For this exercise, leave both in. In practice, you should try both, see which one performs better on a validation set, and then use that method.
Scaling
Take a look at the dataset. Print a summary of the encoded dataset using describe
(documentation).
encoded.describe()

One column ranges from 290290 to 1354013540 (sqft_living
), another column ranges from 11 to 55 (condition
), 7171 columns are all either 00 or 11 (one-hot encoded ZIP code), and then the final column ranges from a few hundred thousand to a couple million (zip_mean
).
In a linear model, these will not be on equal footing. The sqft_living
column will be approximately 1300013000 times easier for the model to find a pattern in than the other columns. To solve this, you often want to scale features to a standardized range. In this case, you will scale sqft_living
to lie within 00 and 11.
Feature scaling
Fill in the code skeleton below to scale the column of the DataFrame to be between 00 and 11.
sqft_min = encoded[‘sqft_living’].min()
sqft_max = encoded[‘sqft_living’].max()
encoded[‘sqft_living’] = encoded[‘sqft_living’].map(lambda x : (x-sqft_min)/(sqft_max – sqft_min))
cond_min = encoded[‘condition’].min()
cond_max = encoded[‘condition’].max()
encoded[‘condition’] = encoded[‘condition’].map(lambda x : (x-cond_min)/(cond_max – cond_min))]
Predicting Credit Card Fraud Solution
Predicting Airplane Delays Solution
Data Processing for Machine Learning Example
Google interview questions for various roles and How to Ace the Google Software Engineering Interview?


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Google interview questions for various roles and How to Ace the Google Software Engineering Interview?
Google is one of the most sought-after employers in the world, known for their cutting-edge technology and innovative products.
If you’re lucky enough to land an interview with Google, you can expect to be asked some challenging questions. Google is known for their brainteasers and algorithmic questions, so it’s important to brush up on your coding skills before the interview. However, Google also values creativity and out-of-the-box thinking, so don’t be afraid to think outside the box when answering questions. product managers need to be able to think strategically about Google’s products, while software engineers will need to demonstrate their technical expertise. No matter what role you’re interviewing for, remember to stay calm and confident, and you’ll be sure to ace the Google interview.
The interview process is notoriously difficult, with contenders being put through their paces with brain-teasers, algorithm questions, and intense coding challenges. However, Google interviews aren’t just designed to trip you up – they’re also an opportunity to show off your skills and demonstrate why you’re the perfect fit for the role. If you’re hoping to secure a Google career, preparation is key. Here are some top tips for acing the Google interview, whatever position you’re applying for.
Firstly, take some time to familiarize yourself with Google’s products and services. Google is such a huge company that it can be easy to get overwhelmed, but it’s important to remember that they started out as a search engine. Having a solid understanding of how Google works will give you a good foundation to build upon during the interview process. Secondly, practice your coding skills. Google interviews are notoriously difficult, and many contenders fail at the first hurdle because they’re not prepared for the level of difficulty.
The company is known for its rigorous interview process, which often includes a mix of coding, algorithm, and behavioral questions. While Google interview questions can vary depending on the role, there are some common themes that arise. For software engineering positions, candidates can expect to be asked questions about their coding skills and experience. For product manager roles, Google interviewers often focus on behavioral questions, such as how the candidate has handled difficult decisions in the past. Quantitative compensation analyst candidates may be asked math-based questions, while AdWords Associates may be asked about Google’s advertising products and policies. Google is known for being an intense place to work, so it’s important for interviewees to go into the process prepared and ready to impress. Ultimately, nailing the Google interview isn’t just about having the right answers – it’s also about having the right attitude.
Below are some of the questions asked during Google Interview for various roles:
Google Interview Questions: Product Marketing Manager
- Why do you want to join Google?
- What do you know about Google’s product and technology?
- If you are Product Manager for Google’s Adwords, how do you plan to market this?
- What would you say during an AdWords or AdSense product seminar?
- Who are Google’s competitors, and how does Google compete with them?
- Have you ever used Google’s products? Gmail?
- What’s a creative way of marketing Google’s brand name and product?
- If you are the product marketing manager for Google’s Gmail product, how do you plan to market it so as to achieve 100 million customers in 6 months?
- How much money you think Google makes daily from Gmail ads?
- Name a piece of technology you’ve read about recently. Now tell me your own creative execution for an ad for that product.
- Say an advertiser makes $0.10 every time someone clicks on their ad. Only 20% of people who visit the site click on their ad. How many people need to visit the site for the advertiser to make $20?
- Estimate the number of students who are college seniors, attend four-year schools, and graduate with a job in the United States every year.
Google Interview Questions: Product Manager
- How would you boost the GMail subscription base?
- What is the most efficient way to sort a million integers?
- How would you re-position Google’s offerings to counteract competitive threats from Microsoft?
- How many golf balls can fit in a school bus?
- You are shrunk to the height of a nickel and your mass is proportionally reduced so as to maintain your original density. You are then thrown into an empty glass blender. The blades will start moving in 60 seconds. What do you do?
- How much should you charge to wash all the windows in Seattle?
- How would you find out if a machine’s stack grows up or down in memory?
- Explain a database in three sentences to your eight-year-old nephew.
- How many times a day does a clock’s hands overlap?
- You have to get from point A to point B. You don’t know if you can get there. What would you do?
- Imagine you have a closet full of shirts. It’s very hard to find a shirt. So what can you do to organize your shirts for easy retrieval?
- Every man in a village of 100 married couples has cheated on his wife. Every wife in the village instantly knows when a man other than her husband has cheated, but does not know when her own husband has. The village has a law that does not allow for adultery. Any wife who can prove that her husband is unfaithful must kill him that very day. The women of the village would never disobey this law. One day, the queen of the village visits and announces that at least one husband has been unfaithful. What happens?
- In a country in which people only want boys, every family continues to have children until they have a boy. If they have a girl, they have another child. If they have a boy, they stop. What is the proportion of boys to girls in the country?
- If the probability of observing a car in 30 minutes on a highway is 0.95, what is the probability of observing a car in 10 minutes (assuming constant default probability)?
- If you look at a clock and the time is 3:15, what is the angle between the hour and the minute hands? (The answer to this is not zero!)
- Four people need to cross a rickety rope bridge to get back to their camp at night. Unfortunately, they only have one flashlight and it only has enough light left for seventeen minutes. The bridge is too dangerous to cross without a flashlight, and it’s only strong enough to support two people at any given time. Each of the campers walks at a different speed. One can cross the bridge in 1 minute, another in 2 minutes, the third in 5 minutes, and the slow poke takes 10 minutes to cross. How do the campers make it across in 17 minutes?
- You are at a party with a friend and 10 people are present including you and the friend. your friend makes you a wager that for every person you find that has the same birthday as you, you get $1; for every person he finds that does not have the same birthday as you, he gets $2. would you accept the wager?
- How many piano tuners are there in the entire world?
- You have eight balls all of the same size. 7 of them weigh the same, and one of them weighs slightly more. How can you find the ball that is heavier by using a balance and only two weighings?
- You have five pirates, ranked from 5 to 1 in descending order. The top pirate has the right to propose how 100 gold coins should be divided among them. But the others get to vote on his plan, and if fewer than half agree with him, he gets killed. How should he allocate the gold in order to maximize his share but live to enjoy it? (Hint: One pirate ends up with 98 percent of the gold.)
- You are given 2 eggs. You have access to a 100-story building. Eggs can be very hard or very fragile means it may break if dropped from the first floor or may not even break if dropped from 100th floor. Both eggs are identical. You need to figure out the highest floor of a 100-story building an egg can be dropped without breaking. The question is how many drops you need to make. You are allowed to break 2 eggs in the process.
- Describe a technical problem you had and how you solved it.
- How would you design a simple search engine?
- Design an evacuation plan for San Francisco.
- There’s a latency problem in South Africa. Diagnose it.
- What are three long term challenges facing Google?
- Name three non-Google websites that you visit often and like. What do you like about the user interface and design? Choose one of the three sites and comment on what new feature or project you would work on. How would you design it?
- If there is only one elevator in the building, how would you change the design? How about if there are only two elevators in the building?
- How many vacuum’s are made per year in USA?
Google Interview Questions: Software Engineer
- Why are manhole covers round?
- What is the difference between a mutex and a semaphore? Which one would you use to protect access to an increment operation?
- A man pushed his car to a hotel and lost his fortune. What happened?
- Explain the significance of “dead beef”.
- Write a C program which measures the the speed of a context switch on a UNIX/Linux system.
- Given a function which produces a random integer in the range 1 to 5, write a function which produces a random integer in the range 1 to 7.
- Describe the algorithm for a depth-first graph traversal.
- Design a class library for writing card games.
- You need to check that your friend, Bob, has your correct phone number, but you cannot ask him directly. You must write a the question on a card which and give it to Eve who will take the card to Bob and return the answer to you. What must you write on the card, besides the question, to ensure Bob can encode the message so that Eve cannot read your phone number?
- How are cookies passed in the HTTP protocol?
- Design the SQL database tables for a car rental database.
- Write a regular expression which matches a email address.
- Write a function f(a, b) which takes two character string arguments and returns a string containing only the characters found in both strings in the order of a. Write a version which is order N-squared and one which is order N.
- You are given a the source to a application which is crashing when run. After running it 10 times in a debugger, you find it never crashes in the same place. The application is single threaded, and uses only the C standard library. What programming errors could be causing this crash? How would you test each one?
- Explain how congestion control works in the TCP protocol.
- In Java, what is the difference between final, finally, and finalize?
- What is multithreaded programming? What is a deadlock?
- Write a function (with helper functions if needed) called to Excel that takes an excel column value (A,B,C,D…AA,AB,AC,… AAA..) and returns a corresponding integer value (A=1,B=2,… AA=26..).
- You have a stream of infinite queries (ie: real time Google search queries that people are entering). Describe how you would go about finding a good estimate of 1000 samples from this never ending set of data and then write code for it.
- Tree search algorithms. Write BFS and DFS code, explain run time and space requirements. Modify the code to handle trees with weighted edges and loops with BFS and DFS, make the code print out path to goal state.
- You are given a list of numbers. When you reach the end of the list you will come back to the beginning of the list (a circular list). Write the most efficient algorithm to find the minimum # in this list. Find any given # in the list. The numbers in the list are always increasing but you don’t know where the circular list begins, ie: 38, 40, 55, 89, 6, 13, 20, 23, 36.
- Describe the data structure that is used to manage memory. (stack)
- What’s the difference between local and global variables?
- If you have 1 million integers, how would you sort them efficiently? (modify a specific sorting algorithm to solve this)
- In Java, what is the difference between static, final, and const. (if you don’t know Java they will ask something similar for C or C++).
- Talk about your class projects or work projects (pick something easy)… then describe how you could make them more efficient (in terms of algorithms).
- Suppose you have an NxN matrix of positive and negative integers. Write some code that finds the sub-matrix with the maximum sum of its elements.
- Write some code to reverse a string.
- Implement division (without using the divide operator, obviously).
- Write some code to find all permutations of the letters in a particular string.
- What method would you use to look up a word in a dictionary?
- Imagine you have a closet full of shirts. It’s very hard to find a shirt. So what can you do to organize your shirts for easy retrieval?
- You have eight balls all of the same size. 7 of them weigh the same, and one of them weighs slightly more. How can you fine the ball that is heavier by using a balance and only two weighings?
- What is the C-language command for opening a connection with a foreign host over the internet?
- Design and describe a system/application that will most efficiently produce a report of the top 1 million Google search requests. These are the particulars: 1) You are given 12 servers to work with. They are all dual-processor machines with 4Gb of RAM, 4x400GB hard drives and networked together.(Basically, nothing more than high-end PC’s) 2) The log data has already been cleaned for you. It consists of 100 Billion log lines, broken down into 12 320 GB files of 40-byte search terms per line. 3) You can use only custom written applications or available free open-source software.
- There is an array A[N] of N numbers. You have to compose an array Output[N] such that Output[i] will be equal to multiplication of all the elements of A[N] except A[i]. For example Output[0] will be multiplication of A[1] to A[N-1] and Output[1] will be multiplication of A[0] and from A[2] to A[N-1]. Solve it without division operator and in O(n).
- There is a linked list of numbers of length N. N is very large and you don’t know N. You have to write a function that will return k random numbers from the list. Numbers should be completely random. Hint: 1. Use random function rand() (returns a number between 0 and 1) and irand() (return either 0 or 1) 2. It should be done in O(n).
- Find or determine non existence of a number in a sorted list of N numbers where the numbers range over M, M>> N and N large enough to span multiple disks. Algorithm to beat O(log n) bonus points for constant time algorithm.
- You are given a game of Tic Tac Toe. You have to write a function in which you pass the whole game and name of a player. The function will return whether the player has won the game or not. First you to decide which data structure you will use for the game. You need to tell the algorithm first and then need to write the code. Note: Some position may be blank in the game। So your data structure should consider this condition also.
- You are given an array [a1 To an] and we have to construct another array [b1 To bn] where bi = a1*a2*…*an/ai. you are allowed to use only constant space and the time complexity is O(n). No divisions are allowed.
- How do you put a Binary Search Tree in an array in a efficient manner. Hint :: If the node is stored at the ith position and its children are at 2i and 2i+1(I mean level order wise)Its not the most efficient way.
- How do you find out the fifth maximum element in an Binary Search Tree in efficient manner. Note: You should not use use any extra space. i.e sorting Binary Search Tree and storing the results in an array and listing out the fifth element.
- Given a Data Structure having first n integers and next n chars. A = i1 i2 i3 … iN c1 c2 c3 … cN.Write an in-place algorithm to rearrange the elements of the array ass A = i1 c1 i2 c2 … in cn
- Given two sequences of items, find the items whose absolute number increases or decreases the most when comparing one sequence with the other by reading the sequence only once.
- Given That One of the strings is very very long , and the other one could be of various sizes. Windowing will result in O(N+M) solution but could it be better? May be NlogM or even better?
- How many lines can be drawn in a 2D plane such that they are equidistant from 3 non-collinear points?
- Let’s say you have to construct Google maps from scratch and guide a person standing on Gateway of India (Mumbai) to India Gate(Delhi). How do you do the same?
- Given that you have one string of length N and M small strings of length L. How do you efficiently find the occurrence of each small string in the larger one?
- Given a binary tree, programmatically you need to prove it is a binary search tree.
- You are given a small sorted list of numbers, and a very very long sorted list of numbers – so long that it had to be put on a disk in different blocks. How would you find those short list numbers in the bigger one?
- Suppose you have given N companies, and we want to eventually merge them into one big company. How many ways are theres to merge?
- Given a file of 4 billion 32-bit integers, how to find one that appears at least twice?
- Write a program for displaying the ten most frequent words in a file such that your program should be efficient in all complexity measures.
- Design a stack. We want to push, pop, and also, retrieve the minimum element in constant time.
- Given a set of coin denominators, find the minimum number of coins to give a certain amount of change.
- Given an array, i) find the longest continuous increasing subsequence. ii) find the longest increasing subsequence.
- Suppose we have N companies, and we want to eventually merge them into one big company. How many ways are there to merge?
- Write a function to find the middle node of a single link list.
- Given two binary trees, write a compare function to check if they are equal or not. Being equal means that they have the same value and same structure.
- Implement put/get methods of a fixed size cache with LRU replacement algorithm.
- You are given with three sorted arrays ( in ascending order), you are required to find a triplet ( one element from each array) such that distance is minimum.
- Distance is defined like this : If a[i], b[j] and c[k] are three elements then distance=max(abs(a[i]-b[j]),
abs(a[i]-c[k]),abs(b[j]-c[k])) ” Please give a solution in O(n) time complexity - How does C++ deal with constructors and deconstructors of a class and its child class?
- Write a function that flips the bits inside a byte (either in C++ or Java). Write an algorithm that take a list of n words, and an integer m, and retrieves the mth most frequent word in that list.
- What’s 2 to the power of 64?
- Given that you have one string of length N and M small strings of length L. How do you efficiently find the occurrence of each small string in the larger one?
- How do you find out the fifth maximum element in an Binary Search Tree in efficient manner.
- Suppose we have N companies, and we want to eventually merge them into one big company. How many ways are there to merge?
- There is linked list of millions of node and you do not know the length of it. Write a function which will return a random number from the list.
- You need to check that your friend, Bob, has your correct phone number, but you cannot ask him directly. You must write a the question on a card which and give it to Eve who will take the card to Bob and return the answer to you. What must you write on the card, besides the question, to ensure Bob can encode the message so that Eve cannot read your phone number?
- How long it would take to sort 1 trillion numbers? Come up with a good estimate.
- Order the functions in order of their asymptotic performance: 1) 2^n 2) n^100 3) n! 4) n^n
- There are some data represented by(x,y,z). Now we want to find the Kth least data. We say (x1, y1, z1) > (x2, y2, z2) when value(x1, y1, z1) > value(x2, y2, z2) where value(x,y,z) = (2^x)*(3^y)*(5^z). Now we can not get it by calculating value(x,y,z) or through other indirect calculations as lg(value(x,y,z)). How to solve it?
- How many degrees are there in the angle between the hour and minute hands of a clock when the time is a quarter past three?
- Given an array whose elements are sorted, return the index of a the first occurrence of a specific integer. Do this in sub-linear time. I.e. do not just go through each element searching for that element.
- Given two linked lists, return the intersection of the two lists: i.e. return a list containing only the elements that occur in both of the input lists.
- What’s the difference between a hashtable and a hashmap?
- If a person dials a sequence of numbers on the telephone, what possible words/strings can be formed from the letters associated with those numbers?
- How would you reverse the image on an n by n matrix where each pixel is represented by a bit?
- Create a fast cached storage mechanism that, given a limitation on the amount of cache memory, will ensure that only the least recently used items are discarded when the cache memory is reached when inserting a new item. It supports 2 functions: String get(T t) and void put(String k, T t).
- Create a cost model that allows Google to make purchasing decisions on to compare the cost of purchasing more RAM memory for their servers vs. buying more disk space.
- Design an algorithm to play a game of Frogger and then code the solution. The object of the game is to direct a frog to avoid cars while crossing a busy road. You may represent a road lane via an array. Generalize the solution for an N-lane road.
- What sort would you use if you had a large data set on disk and a small amount of ram to work with?
- What sort would you use if you required tight max time bounds and wanted highly regular performance.
- How would you store 1 million phone numbers?
- Design a 2D dungeon crawling game. It must allow for various items in the maze – walls, objects, and computer-controlled characters. (The focus was on the class structures, and how to optimize the experience for the user as s/he travels through the dungeon.)
- What is the size of the C structure below on a 32-bit system? On a 64-bit?
struct foo {
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A triomino is formed by joining three unit-sized squares in an L-shape. A mutilated chessboard is made up of 64 unit-sized squares arranged in an 8-by-8 square, minus the top left square.
Design an algorithm which computes a placement of 21 triominos that covers the mutilated chessboard.2.
The mathematician G. H. Hardy was on his way to visit his collaborator S. Ramanujan who was in the hospital. Hardy remarked to Ramanujan that he traveled in a taxi cab with license plate 1729, which seemed a dull number. To this, Ramanujan replied that 1729 was a very interesting number – it was the smallest number expressible as the sum of cubes of two numbers in two different ways. Indeed, 10x10x10 + 9x9x9 = 12x12x12 + 1x1x1 = 1729.
Given an arbitrary positive integer, how would you determine if it can be expressed as a sum of two cubes?
There are fifty coins in a line—these could be pennies, nickels, dimes, or quarters. Two players, $F$ and $S$, take turns at choosing one coin each—they can only choose from the two coins at the ends of the line. The game ends when all the coins have been picked up. The player whose coins have the higher total value wins. Each player must select a coin when it is his turn, so the game ends in fifty turns.
If you want to ensure you do not lose, would you rather go first or second? Design an efficient algorithm for computing the maximum amount of money the first player can win.
You are given two sorted arrays. Design an efficient algorithm for computing the k-th smallest element in the union of the two arrays. (Keep in mind that the elements may be repeated.)
- How do you merge two sorted linked lists”?
It’s literally about 10 lines of code, give or take. It’s at the heart of merge sort.
Merge 2 sorted linked lists in C language Reference: Here
Google Interview: Software Engineer in Test
- Efficiently implement 3 stacks in a single array.
- Given an array of integers which is circularly sorted, how do you find a given integer.
- Write a program to find depth of binary search tree without using recursion.
- Find the maximum rectangle (in terms of area) under a histogram in linear time.
- Most phones now have full keyboards. Before there there three letters mapped to a number button. Describe how you would go about implementing spelling and word suggestions as people type.
- Describe recursive mergesort and its runtime. Write an iterative version in C++/Java/Python.
- How would you determine if someone has won a game of tic-tac-toe on a board of any size?
- Given an array of numbers, replace each number with the product of all the numbers in the array except the number itself *without* using division.
- Create a cache with fast look up that only stores the N most recently accessed items.
- How to design a search engine? If each document contains a set of keywords, and is associated with a numeric attribute, how to build indices?
- Given two files that has list of words (one per line), write a program to show the intersection.
- What kind of data structure would you use to index annagrams of words? e.g. if there exists the word “top” in the database, the query for “pot” should list that.
Google Interview: Quantitative Compensation Analyst
- What is the yearly standard deviation of a stock given the monthly standard deviation?
- How many resumes does Google receive each year for software engineering?
- Anywhere in the world, where would you open up a new Google office and how would you figure out compensation for all the employees at this new office?
- What is the probability of breaking a stick into 3 pieces and forming a triangle?
Google Interview: Engineering Manager
- You’re the captain of a pirate ship, and your crew gets to vote on how the gold is divided up. If fewer than half of the pirates agree with you, you die. How do you recommend apportioning the gold in such a way that you get a good share of the booty, but still survive?
Google Interview: AdWords Associate
- How would you work with an advertiser who was not seeing the benefits of the AdWords relationship due to poor conversions?
- How would you deal with an angry or frustrated advertisers on the phone?
Sources
To conclude:
Google is one of the most sought-after employers in the tech industry. The company is known for its rigorous interview process, which often includes a mix of coding, algorithm, and behavioural questions. While Google interview questions can vary depending on the role, there are some common themes that arise. For software engineering positions, candidates can expect to be asked questions about their coding skills and experience. For product manager roles, Google interviewers often focus on behavioral questions, such as how the candidate has handled difficult decisions in the past. Quantitative compensation analyst candidates may be asked math-based questions, while AdWords Associates may be asked about Google’s advertising products and policies. Google is known for being an intense place to work, so it’s important for interviewees to go into the process prepared and ready to impress. Ultimately, nailing the Google interview isn’t just about having the right answers – it’s also about having the right attitude.
Is “cracking the coding interview” enough to prepare you for Google onsite interview?
Simply put, no.
There’s no doubt that Cracking The Coding Interview (CTCI) is a great tool for honing your coding skills.
But in today’s competitive job landscape, you need a lot more than sharp coding skills to get hired by Google.
Think about it.
Google receives about 3 million job applications every year.
But it hires less than 1% of those people.
Most of those who get the job (if they’re software engineers, at least) spent weeks or months practicing problems in CTCI and LeetCode before their interview.
But so did the people who don’t get hired.
So if a mastery of coding problems isn’t whats set the winners apart from the losers, what is?
The soft skills.
Believe it or not, soft skills matter a lot, even as a software engineer.
Here are three soft skills Google looks for that CTCI won’t help you with.
#1 LEADERSHIP
You’d be amazed how many candidates overlook the importance of leadership as they try to get hired by Google.
They forget that recruiters are not looking for their ability to be a strong junior engineer, but their ability to develop into a strong senior engineer.
Recruiters need to know that you have the empathy to lead a team, and that you’re willing to pull up your socks when things go awry.
If you can’t show that you’re a leader in your interview, it won’t matter how good your code is—you won’t be getting hired.
#2 COMMUNICATION & TEAMWORK
Teamwork and communication are two other skill sets you won’t gain from CTCI.
And just like leadership, you need to demonstrate these skills if you expect to get an offer from Google.
Why?
Because building the world’s best technology is a team sport, and if you want to thrive on Team Google, you need to prove yourself as a team player.
Don’t overlook this.
Google and the other FAANG companies regularly pass up skilled engineers because they don’t believe they’ll be strong members of the larger team.
#3 MASTERY OVER AMBIGUITY
Google recruiters often throw highly ambiguous problems at candidates just to see how they handle them.
So if you can’t walk the recruiter through your process for solving it, they’re going to move on to someone else.
The ambiguous problems I’m talking about are not like the ones you face in CTCI. They’re much more open-ended, and there truly are no right answers.
These are the sort of questions you need a guide to help you navigate through. That’s why you need more guidance than what CTCI provides if you want to give yourself the best chance at getting an offer.
If you just want to hone your coding skills, CTCI is a good place to start.
But if you’re serious about getting a job at Google, I recommend a more comprehensive course like Tech Interview Pro, which was designed by ex-Google and ex-Facebook software engineers to help you succeed in all areas of the job hunt, from building your resume all the way to salary negotiations.
Whatever you do, don’t overlook the importance of soft skills on your journey to getting hired. They’ll be what clinches your spot.
Good luck!
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Machine Learning Engineer Interview Questions and Answers
Tech Jobs and Career at FAANG (now MAANGM): Facebook Meta Amazon Apple Netflix Google Microsoft


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Tech Jobs and Career at FAANG (now MAANGM): Facebook Meta Amazon Apple Netflix Google Microsoft
The FAANG companies (Facebook, Amazon, Apple, Netflix, Google, and Microsoft) are some of the most sought-after employers in the tech industry. They offer competitive salaries and benefits, and their employees are at the forefront of innovation.
The interview process for a job at a FAANG company is notoriously difficult. Candidates must be prepared to answer tough technical questions and demonstrate their problem-solving skills. The competition is fierce, but the rewards are worth it. Employees of FAANG companies enjoy perks like free food and transportation, and they often have the opportunity to work on cutting-edge projects.
If you’re interested in a career in tech, Google, Facebook, or Microsoft are great places to start your search. These companies are leaders in their field, and they offer endless opportunities for career growth.
This blog is about Clever Questions, Answers, Resources, Feeds, Discussions about Tech jobs and careers at MAANGM companies including:
- Meta (Facebook)
- Apple
- Amazon
- AWS
- Netflix
- Google (Alphabet)
- Microsoft

Top-paying Cloud certifications provided by MAANGM:
According to the 2020 Global Knowledge report, the top-paying cloud certifications for the year are (drumroll, please):
- Google Certified Professional Cloud Architect — $175,761
- AWS Certified Solutions Architect – Associate — $149,446
- AWS Certified Cloud Practitioner — $131,465
- Microsoft Certified: Azure Fundamentals — $126,653
- Microsoft Certified: Azure Administrator Associate — $125,993
FAANG – MAANGM Compensation
Legend – Base / Stocks (Total over 4 years) / Sign On
Google (Alphabet)
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– 145/270/30 (2017, L4)
– 150/400/30 (2018, L4)
*Google’s target annual bonus is 15%. Vesting is monthly and has no cliff.
Facebook ( Meta)
– 115/160/100 (2017, E3)
– 160/300/70 (2017, E4)
– 145/220/0 (2017, E4)
– 175/250/0 (2017, E5)
– 210/1000/100 (2017, E6)
*Facebook’s target annual bonus is 10% for E3 and E4. 15% for E5 and 20% for E6. Vesting is quarterly and has no cliff.
LinkedIn (Microsoft)
– 125/150/25 (2016, SE)
– 120/150/10 (2016, SE)
– 170/300/30 (2016, Senior SE)
– 140/250/50 (2017, Senior SE)
Apple
– 110/60/40 (2016, ICT2)
– 120/100/21 (2017, ICT3)
– 135/105/20 (2017, ICT3)
– 160/105/30 (2017, ICT4)
Amazon (AWS)
– 103/65/52 (2016, SDE I)
– 110/200/50 (2016, SDE I)
– 135/70/45 (2016, SDE I)
– 160/320/185 (2018, SDE III)
*Amazon stocks have a 5/15/40/40 vesting schedule and sign on is split almost evenly over the first two years*
Microsoft
– 106/120/15 (2016, SDE)
– 107/90/35 (2016, SDE)
– 130/200/20 (2016, SWE1)
– 160/600/50 (2017, SWE II)
Uber
– 110/180/0 (2016, L3)
– 110/150/0 (2016, L3)
– 140/590/0 (2017, L4)
Lyft
– 135/260/60 (2017, L3)
– 170/720/20 (2017, L4)
– 152/327/0 (2017, L4)
– 175/480/0 (2017, L4)
Dropbox
– 167/464/10 (2017, IC2)
– 160/250/10 (2017, IC2)
– 160/300/50 (2017, IC2)
That’s my guess. It hasn’t changed when Google became Alphabet.
FAANG stared as FANG circa 2013. The 2nd A became customary around 2016 as it wasn’t clear whether A referred to Apple or Amazon. Originally, FANG meant “large public, fast growing tech companies”. Now in 2021, the scope of what FANG referred to just doesn’t correspond to these 5 companies.
From an investment perspective (which is the origin of FANG) Facebook stock has grown the slowest of the 5 companies over the past 5 years. And they’re all dwarfed by Tesla.
From an employment desirability perspective (which is the context where FAANG is most used today). Microsoft is very similar to the group. It wasn’t “cool” around 2013 but its stock actually did better than Facebook or Alphabet over the past five years. Other companies like Airbnb, Twitter or Salesforce offer the same value proposition to employees, that is stability and tradable equity as part of the compensation.
FAANG refers to a category more than a specific list of companies.
As a side note, I expect people to routinely call the company Facebook, just like most people still say Google when they really mean Alphabet.
The technical interviews at FAANG companies, in the grand scheme, aren’t very difficult.
People frequently fail FAANG interviews because they choke — they experience anxiety and just forget their knowledge — or they don’t know the material to begin with.
Inverting a binary tree, matching up pairs of brackets, finding the duplicate in an array of distinct integers, etc., are all weeder-questions that should be solvable in 5–10 minutes, if you’re the type to suffer from interview jitters. You should know which data structures to use, intuitively, and you should be doing prep work to cover your knowledge gaps if you don’t.
Harder questions will take longer, but ultimately, you’ll have 45 minutes or so to solve 2–3 questions.
Technical interviews at FAANG companies are only difficult if you have shaky computer science fundamentals. Luckily, the process for cracking the code interview *cough* is very well-documented, hence, you only need to follow the already established strategies. If you’re interested in maximizing income while prioritizing career growth, it behooves you to spend a month or two studying these strategies.
In FAANG interview process, when you fail at the 1st (or 2nd stage), does it mean that single interviewer on the respective stage failed you, or is it still team collaboration /hiring manager decision?
If you were dropped after doing a single interview (usually called a “screen”) it means that this interviewer gave negative feedback. I would guess at some companies this feedback is reviewed by the hiring manager, but mostly I think a recruiter will just reject if the interviewer recommends no hire. Even if a hiring manager looks at it, they would probably reject almost always if the feedback is negative. The purpose of the screen is to quickly evaluate if a person is worth interviewing in depth.
If you were rejected after a whole interview panel, probably a hiring manager or similar did look at the entire feedback, and much of the time there was a discussion where interviewers looked at the entire feedback as well and shared their thoughts. However, if the feedback was clearly negative, it could’ve been just a snap decision by a manager without much discussion. Source.
What do you do after you absolutely flop a technical interview?
Take care of yourself / don’t beat yourself up.
It happens. It happened to me, it happened to smarter people. It’s ok.
Two thoughts to help here –
Getting to the interview stage is already a huge achievement. If you are interviewed, this means that in the expert opinion of the recruiters, people that did tech screens etc. you stand a chance to pass the interview. You earned your place in the interviewee seat. This is an accomplishment you can be proud of.
The consequences are probably* negligible in the long run. There’s at least 100 very desirable tech companies to work at at a given moment. You didn’t get in 1% of them at a moment in time. Big deal. You can probably retry in a few months. It’s very likely that you get an equivalent or even better opportunity, and there’s no use imagining what would have happened if you had had that job. (*“probably” because if you’re under time pressure to get a job rapidly… it may sting differently. But hey, there’s still the first thought).
As a bonus, you’ll probably remember very well the question on which you failed. Source: Jerome Cukier
If an interviewer says “we’re still interviewing other candidates at the moment”, and then walks you out into the lobby, does that mean they want to hire you potentially after or no?
Here’s a secret. I have been a recruiter for 24 years and when they walk you out after your interview and tell you that they are still interviewing other candidates at the moment, it really means they’re still interviewing other candidates at the moment. There’s no secret language here to try to interpret. It means what it means. You will have to wait for them to tell you what next steps are for you because, again, they have other people to interview. By Leah Roth
Which FAANGM software engineer interview do you think it’s the easiest? What about the hardest?
The difficulty of the interview is going to vary more interviewer to interviewer, than company to company. Also, how difficult the questions are is not directly related to how selective the process is; the latter being heavily influenced by business factors currently affecting these companies and what are their current hiring plans.
Comments:
#1: So, how do know you this? You don’t. An affirmative answer to this question can only come from data.
#Answer #1: Fair question. I have been very involved in interviewing in a number of large tech cos. I have read, by now, thousands of interview debriefs. I have also interviewed a fair amount as a candidate, although I have not interviewed in each of the “FAANG” and I have definitely be more often on the interviewing side.
As such, I have seen for the same position, very easy questions and brutally difficult ones; I have seen very promising candidates not brought to onsite interviews because the hiring organization didn’t currently have resources to hire, but also ok-ish candidates given offers because the organization had trouble meeting their hiring targets. As a candidate I also experienced: easy interview exercises but no offer, very hard interview exercises and offer (with the caveat that I never know exactly how well I do, but I certainly can tell if a coding question or a system design question is easy or hard).
So. I am well aware that it’s still anecdotal evidence, but it’s still based on a fairly large sample of interviews and candidates.
#Reply to #1: Nope, you’re wrong. I have experience in the interview process at Amazon and Microsoft and have a different conclusion. Moreover, “experts” in lots of disparate fields make claims that are a bunch of bullcrap due to their own experiential biases. Additionally, you would need to be involved at all of the companies listed, not just some of the them, for that experience to be relevant in answering this question. We need to look at the data. If you don’t have data, I will not trust you just because of “your experience”. I don’t think it’s possible for Jerry C to have the necessary information to justify the confidence that is projected in this answer.
What you need is not so much a list of “incidents” but more generally some self-awareness on what you care about and how you’ve progressed and how you see your career.
The best source for this material is your performance reviews. Ideally you also kept some document about your career goals and/or conversation with your manager. (If you haven’t such documents, it’s never too late to start them!).
You should have 5–6 situations that are fairly recent and that you know on the back of your hand. These must include something difficult, and some of these situations must be focused on interpersonal relationships (or more generally, you should be aware of more situations that involved a difficult interpersonal relation). They may or may not have had a great outcome – it’s ok if you didn’t save the day. But you should always know the outcome both in terms of business and on your personal growth.
Once you have your set of situations and you can easily access these stories / effortlessly remember all details, you’ll find it much easier to answer any behavioural question.
In a software engineering interview, How should one answer the question, ‘Could you tell me about some of the technical challenges in your previous projects’?
To take a few steps back, there are 2 things that interviewers care about in behavioural interviews – whether the candidate has the right level, and whether they exhibit certain skillsets.
When you look at this question from the first angle, it’s important to be able to present hard problems on which it’s clear what the candidate’s personal contribution was. Typically, later projects are better for that than earlier ones.
Now, in terms of skillsets, this really depends company by company but typically, how well a candidate is able to describe a problem especially to someone with a different expertise, and whether they spontaneously go on to describe impact metrics, goes a long way.
So great answer: hard, recent, large scale project, that the candidate is able to contextualize (why was is important, why was it hard, what was at stake), where they are able to describe what they’ve done and what was the potential impact, and what were the actual consequences.
Not so great answer: a project that no one asked the candidate to do, but which they insisted on doing because they thought it was cool/interesting, on which they worked alone and which didn’t have any business impact. Source.
This question (like many other things in life) is much more complicated than it appears on the surface. That’s because it is conflating several very different issues, including:
- What is retirement?
- What is “early”?
- At what age do most software engineers stop working in that role?
- How long do employees stay on average at the FAANGs?
In the “old” days (let’s arbitrarily call that mid-20th century America), the typical worker was white, male and middle class, employed on location at a job for 40–50 hours a week. He began his working career at 18 (after high school) or 22 (after college), and worked continuously for a salary until the age of 65. At that time he retired (“stopped working”) and spent his remaining 5–10 years of life sitting at home watching tv or traveling to places that he had always wanted to visit.
That world has, to a large extent, been transmogrified over the past 50 years. People are working longer, changing employment more frequently, even changing careers and professions as technology and the economy change. The work force is increasingly diverse, and virtually all occupations are open to virtually all people. Over the past two years we have seen that an astonishing number of jobs can be done remotely, and on an asynchronous basis. And all of these changes have disproportionately affected software engineering.
So, let’s begin by laying out some facts:
- When people plan to retire is a factor of their generation: Generation Y — ages 25 to 40 — plans to retire at an average age of 59. For Generation X — now 41 to 56 — the average age is 60. Baby boomers — who range from 57 to 75 — indicated they plan to work longer, with an average expected retirement age of 68.[1]
- The average actual retirement age in the US is 62[2]
- Most software engineers retire between the ages of 45 and 65, with less than 1% of developers working later than 65.[3]
- But those numbers are misleading because many software engineers experience rapid career progression and move out of a pure development role long before they retire.
- The average life expectancy in Silicon Valley is 85 years.[4]
- The tenure of employment at the FAANGs is much shorter than than one might imagine. Unlike in the past, when a person might spend his or her entire career working for one or two employers, here are the average lengths of time that people work at the FAANGs: Facebook 2.5 years, Google 3.2 years, Apple 5 years.[5]
Therefore, if the question assumes that a software engineer gets hired at a FAANG company in his or her 20s, works there for 20 or 30 years as a coder, and then “retires early”, that is just not the way things work.
Much more likely is the scenario in which an engineer graduates from college at 21, gets a masters degree in computer science by 23, starts as a junior engineer at a small or large company for a few years, gets hired into a FAANG by their early 30s, spends 3–5 years coding there, is recruited to join a non-FAANG by their early 40s in a more senior role, and moves into management by their late 40s.
At that point things become a matter of personal preference: truly “retire”, start your own venture; invest in cryptocurrency; move up to senior management; begin a second career; etc.
The fact is that software engineering at a high level (such as would warrant employment at a FAANG in the first place) pays very well in relative terms, and with appropriate self-control and a moderate lifestyle would enable someone to “retire” at a relatively early age. But paradoxically, that same type of person is unlikely to do so.
Are companies like Google and Facebook heaven on earth in terms of workplaces?
No. In fact Google’s a really poor workplace by comparison with most others I’ve had in my career. Having a private office with a door you can close is a real boon to doing thoughtful, creative work, and having personal space so that you can feel psychologically safe is important too.
You don’t get any of that at Google, unless you’re a director or VP and your job function requires closed-door meetings. I have a very nice, state-of-the-art standing desk, with a state-of-the-art monitor, and the only way for me to avoid hearing my tech lead’s conversations is to put headphones on. (You can get very nice, state-of-the-art headphones, too.)
On the other hand, I also have regular access to great food, and an excellent gym, and all the La Croix water I can drink. I get to work on the most incredible technological platform on earth. And the money’s good. But heaven on earth? Nah. That’s one of the reasons the money’s good.
What is the starting salary of a software engineer at Google?
A new grad software engineer (L3) at Google makes a salary around $193,000 including stock compensation and bonus. The industry is getting a lot more competitive and top companies such as Google have to make offers with really generous stock packages. The below diagram shows a breakdown for the salary. View all the crowdsourced reports as well as other levels on Levels.fyi.
Hope that helps!
What is the best Google employee perk, and why?
Having recent left Google for a new startup I have to agree that the most-missed perk is the food. It’s not so much that it’s free — you can get lunch for about $10 per day so the cost is not a huge deal. There is simply nowhere you can go, even in a Silicon Valley city like Mountain View, that has healthy low-fat, varied choices that include features like edible fruits and vegetables. The food is even color-coded (red/yellow/green) based on how healthy it is (it always bothered me that the peanut-butter cups are red….).
Outside of Google you end up having muffins for breakfast and pizza for lunch. It tastes good but it’s not the same to your body.
But beyond just the food, the long term health impact of the set of perks at Google is huge. There is nothing better than being able to come in early, work out at the (free) gym by your office, shower (with towels provided as noted by others), then have eggs (or egg whites if you prefer) and toast (or one of a dozen other breakfasts). Source
How I got in to Amazon, Microsoft, Google. All from studying these resources by Alex nguyen @medium
Follow Alex Nguyen on his quest to 30,000 followers on LinkedIn
Alex Nguyen | LinkedIn
Everyone has a study plan and list of resources they like to use. Different plans work for different people and there is no one size fits all.
This by no means is the only list of resources to join a larger technology company. But it is the list of resources I used myself to prepare for all my technology interviews.
Quick Background
I’m a current engineer at Microsoft who previously worked at Amazon for 1 year each respectively. I don’t have a master’s degree and I graduated from NYU, not an Ivy League. I’ll soon be joining Google and the following resources is how I got there.
Yes, the purchasable resources are affiliate links that help support this blog. Regardless, these are the resources I’ve used both purchasable and free.
Coding Resources
Cracking the Coding Interview (CTCI)
This is the simplest book to get anyone started in studying for coding interviews.
If you’re an absolute beginner, I recommend you to start here. The questions have very details explanations that are easy to understand with basic knowledge of algorithms and data structures.
Elements of Programming Interviews (Python, Java, C++)
If you’re a little more experienced, every question in this book is at the interviewing level of all large technology companies.
If you’ve mastered the questions in this book, then you are more than ready for the average technology interview. The book is not as beginner friendly as CTCI but it does include a study plan depending on how much you need to prepare for your interviews. This is my personal favorite book I carried everywhere in university.
NeetCode blind 75 — YouTube
Blind has a list of 75 questions that is generally enough to solve most coding interviews. It’s a very curated and focused list for the most essential algorithms to leverage your time.
The playlist above is one of the clearest explanations I’ve ever seen and highly recommend if you need an explanation on any of the problems.
CSES Problem Set — Tasks
These problems are hard. Really hard for anyone who hasn’t practiced algorithms and is not beginner friendly. But if you are able to complete the sorting and searching section, you will be more capable than the average LeetCode user and be more than ready for your coding interview.
Consider this if you’re comfortable with LeetCode medium questions and find the questions in CTCI too easy.
Algorithm Learning
Introduction to Algorithms (4th Edition)
This is the most common and best textbook anyone could use to learn algorithms. It’s also the textbook my university used personally to learn the core and essential algorithms to most coding problems.
The 4th edition was recently released and is still relevant to MIT students. If you need structure and a traditional classroom setting to study, follow MIT’s algorithm course here.
William Fiset — Graph Theory
Graph theory does come up in interviews (and was a question I had at both Bloomberg and Google). Stay prepared and follow William Fiset’s graph theory explanation.
The diagrams are comprehensive and the step-by-step explanations are the best I’ve ever seen on the topic.
CSES.fi Handbook
This handbook is for people who are strongly proficient with most Leetcode algorithms. It’s a free resource that strongly complements the CSES.fi curriculum.
Competitive Programming 4th Ed.
For the most experienced algorithm enthusiasts, this book will cover every niche data structure and algorithm that could possibly be asked in any coding interview. This level of preparation is not generally needed for FAANG type companies but can show up if you’re considering hedge fund type companies.
System Design
The System Design Interview (Vol. 1, Vol. 2, Online Course + Community)
In my opinion, you will be more than ready for any system design interview using these resources. The diagrams are clear and the explanations are as simple as possible in each book to help you learn system design concepts quickly.
I recommend the online course personally because yes the content from both books is great to own, it’s the online community discord you get access to that makes the yearly subscription worth it. The discord includes mock interview buddies, salary discussion, and over view on each system design topics to study with other users on.
System Design Primer
The system design primer is the best free resource on all things system design. Dig deep into the Git repository and you will learn everything you need to know on system design. It’s all curated in a single repository and the clearly structured to give you a guided curriculum.
Educative’s System Design Interview
This quick overview on system design is great to review if you’re in a rush. The read typically takes users 45 minutes but you’ll be left knowing more system design than the average engineer.
Give it a read. If concepts are unclear or confusing, that might be a sign you’re not ready for interviews.
Object Oriented Design
Design Patterns: : Elements of Reusable Object-Oriented Software
Regardless if you’re learning design patterns for the object-oriented programming interview, you will need to know design patterns as a software engineer at these large companies.
The book is the origin of the world’s most common design patterns today and showing proficiency in these for your object oriented interview is a requirement for certain large technology companies like Amazon.
Head First Design Patterns
The above resource is dense and written in language that’s hard to understand. While the original source material in design patterns is great, it doesn’t help much if it’s difficult to understand.
Consider Head First Design patterns to study a simplified explanation of those common design patterns. It might not be as in-depth as the original source material, but your understanding in design patterns will be more than enough to crack any object-oriented interview.
Closing Thoughts
Honestly, I did not go through all of these resources from cover to cover. If you do, I’m sure you wouldn’t need to study for another interview again. But likely we don’t have the time to do that so make sure that once you understand the core concepts in the any of the above categories that you invest your time moving on to the next.
Again, these are the resources I used and is not at all inclusive of anyone else’s study plan.
My Google L4 interview experience by Alex Nguyen
3 Years ago I applied to Google and was rejected immediately after the phone screen. Fast forward 2022 and was given another chance to re-interview. Here’s how the entire experience went.
Quick Background
I am currently a junior level software engineer at Microsoft (L60) with previous experience at Amazon (SDE I). My tenure is 1 year at Microsoft and 1 year at Amazon.
The first time I applied to Google was fall of my senior year of college at NYU. I failed the phone screen horribly and never thought I would join a company as competitive as Google. But I did not want to count myself out before even interviewing.
Recruiter Screen
I slowly built my LinkedIn to make sure recruiters would notice me whenever I wrote a LinkedIn post. With 15,000 followers at the time, it wasn’t too difficult to have one of them reach out with the chance to interview. A message came in my LinkedIn inbox and I responded promptly to schedule the initial recruiter call.
The chat was focused more on my previous experiences engineering and some of the projects I worked on. It was important to talk about what languages I was using and how much of my day was spent coding (70% of my day at Microsoft).
The recruiter was interested in having me follow through with a full-loop and asked when I would like to go through the process. It was important to me to ask what engineering level I was applying for. He shared it was L3/L4 role where the interviews would calibrate me depending on my performance. Knowing that, I mentioned I’d like to interview 1 month later and asked what the process looked like as explained to me.
- Technical Phone Screen
- 6 Hour Virtual On-site
a. 4 Technical Coding Interviews or 3 Technical Coding Interviews + 1 system design
b. Behavioral “Googliness” interview
Phone Screen
Following the initial recruiter phone screen, I received an email from Google. It explained that I would be exempt from the Google Technical Phone Screen.
Why? I am personally not sure but it likely had to do with prior experience at large technology companies. I was personally surprised because to this day my first Google Phone Screen is still one of the toughest coding interviews I have ever been given.
It looked like that was as relevant as my current work experience and I didn’t have much to complain about moving quicker through the process and directly on-site.
Technical Onsite
Every coding question I had was a coding question that was either on LeetCode or could be solved with the patterns you find solving coding questions. Here’s what my experience for each of them looked like
Coding Interview #1
The interviewer looked like someone who was my age and likely joined Google directly after university. Maybe I wasn’t jealous. Maybe I was.
The question I was given was a string parsing Hash-Map question. Easily doable if you worked through a few medium questions regarding hash-maps and string parsing. But if you’re not careful, you may have fallen into a common trap.
Let me point it out for you. Abstract away the logic for tedious parsing logic by writing something like “parsingFunction()”. Otherwise 30 minutes may pass without you solving the question. I wrote a short “ToDo” mentioning I’d come back to it if the interviewer cared.
Spoiler: The interviewer didn’t care.
They lastly asked me to optimize with a heap and what the running time was. Unlike others who assert the running time, I solved for it and the interview concluded there.
Coding Interview #2
The interviewer who was more senior than the previous interviewer. I heard the coding question and thought the on-site was over.
The thing about some coding questions is whether you see the pattern for the algorithm or not. The recognizing the pattern for the algorithm can be much more difficult than actually writing the code for it. This was one of those interviews.
After hearing the questions I was thinking of ways to brute force the question or if there was a pattern I could see using smaller test cases. I wasn’t able to recognize it and eventually the interviewer told me what the pattern was.
I tried not to come off embarrassed but followed up with the algorithm to implement that pattern and the interviewer gave me the “go ahead” to code. I finished coding the pattern and answer the follow up by the interviewer on how to make my code modular to handle another requirement. This did not require implementation.
Afterwards was a discussion on time and space complexity and the interview was over.
Coding Interview #3
The interviewer was a mid-level engineer who was not as keen on chatting as much as the interviewers.
Some coding interviews are just one interview where you have to get the question correct or not. This one started off easy and iterated to be tougher.
My quick advice to anyone is to never come off arrogant for any coding question. You may know the question is easy and the interviewer likely does as well. Often times it’ll get harder and all that ego will go out the window. Go through the motions and communicate you always do for any other coding problem.
The problem given was directly on LeetCode and I felt more comfortable knowing I had solved this awhile ago before. If you’re familiar with “sliding window” then you more than likely would be able to solve it. But here’s where the challenge was.
After the warm-up question, the follow up had another requirement on top of the previous question. That follow up was more array manipulation. Finally the last iteration was shared.
I implemented the algorithm where Math.max was being called more than necessary. To me it didn’t affect the output of the algorithm and looked like it didn’t matter. But it mattered to the interviewer. I took that feedback and carefully implemented it the way the interviewer asked me to (whether it actually affected the algorithm or not).
Time and space complexity was solved and the interview was over.
Coding Interview #4
This was another interviewer who had joined Google after university and had the same work experience I did.
This prompt was not given to me and I expected I had to write down the details to the question myself. After asking some clarifying questions on what was and wasn’t in scope, I shared my algorithm.
The question was an object-oriented question to implement a graph. If you had taken any university course on graph theory, you would be more than prepared.
The interesting discussion was whether I had to implement the graph with BFS or DFS and explain the pro’s and con’s of each. Afterwards, I decided with BFS (because BFS is easier for me to implement) and the requirement followed up with taking K-most steps iterative.
I’m not sure if that’s the follow-up because I implemented it in BFS or if that was always the follow-up but I quickly adjusted the algorithm and solved for space and time complexity as always.
The Googliness interview
Googliness is just Google’s behavioral interview. Most questions were along the lines of
- Tell me about yourself
- What’s a project you worked on?
- When was a time you implemented a change?
- When was a time you dealt with a coworker who wasn’t pulling their weight?
To prepare for these, I’d recommend learning about the STAR format and outlining your work experiences if you can recall them before interviewing.
This seemed to go well but then I was given a question I didn’t expect. A product question and my thought process on how to work with teammates to answer the question.
My key point of advice: Nothing matters if the user doesn’t want it.
Emphasize how important user research is to build a product that a user will use otherwise everyone’s time could be better invested in other initiatives. Avoid jumping straight into designing the product and coordinating talks with product managers and UX designers.
Offer
2 weeks later, an informal offer was shared with me in my email.
Most of the interview didn’t not pertain to my previous experience directly. A systematic way of approaching, communicating, and implementing coding problems is enough without experience from Amazon/Microsoft.
Follow Alex Nguyen on his quest to 30,000 followers on LinkedIn
Alex Nguyen | LinkedIn
Yes, it is. That’s a very good sign.
That means you interviewed well. Someone else interviewed better for the first role, but the recruiter sees that there other roles for which you might be a better fit.
The eight interviews is a sign that someone in the process wanted you specifically for some role.
I think there may be two different things going on.
First, are you sure whether it’s a FAANG recruiter, or someone from an external sourcing firm which is retained by a FAANG company? I had this experience where someone reached out on LinkedIn and said they were recruiting for a Google role and passed along a job description. As I started asking them questions, it became clear that they just wanted me to fill out an application so that they can pass it to someone else. Now, as it happens, I am a former Google employee, so it quickly became clear that this person was not from Google at all, but just retained to source candidates. The role they wanted me to apply for was not in fact suitable, despite their claim that they reached out to me because I seemed like a good match.
If you are dealing with a case like this, probably what happens is that they source very broadly, basically spamming people, on the chance that some of the people they identify will in fact be a good fit. So they would solicit a resume, pass it to someone who is actually competent to judge, and that person would reject. And the sourcing firm will often ghost you at this point.
If you are dealing with an actual internal recruiter, I think it can be a similar situation. A recruiter often doesn’t really know if you are a fit or not, and it will often be some technical person who decides. That person may spend 30 seconds on your resume and say “no”. And positions get filled too, which would cause everyone in the pipeline to become irrelevant.
In such cases there is no advantage for the recruiter to further interact with you. Now, every place I worked with, I am pretty sure, had a policy that if a recruiter interacted with the candidate at all, they were supposed to formally reject them (via email or phone). But I imagine there’s very little incentive for a recruiter to do it, so they often don’t. And as a candidate, you don’t really have any way to complain about it to the company, unless you have a friend or colleague on the inside. If you do, I suggest you ask them, and it may do some good, if not to you (you are rejected either way), at least to the next applicant.
As a software engineer or programmer, what’s the dumbest line of code you’ve seen in a codebase?
It’s not actually a line of code, so to speak, but lines of code.
I work in Salesforce, and for those who are not familiar with its cloud architecture, a component from QA could be moved to production only if the overall test coverage of the production is 75% or more. Meaning, if the total number of lines of code across all components, including the newly introduced ones, is 10000, enough test classes must be written with appropriate test scenarios so as to cover at least 7500 lines of the lump. This rule is enforced by Salesforce itself, so there’s no going around it. Asserts, on the other hand, could be done without.
If the movement of your components causes a shift in balance in production and tips its overall coverage to below 75%, you are supposed to work on the new components and raise their coverage before deployment. A nightmare of sorts, because there is a good chance your code is all clean and the issue occurs only because of a history of dirty code that had already gone in over years to drag the overall coverage to its teetering edges.
Someone in my previous company found out a sneaky way to smuggle in some code of his (or hers) without having to worry about this problem.
So this is simple math, right? If you have got 5000 lines of code, 3750 must be covered. But what if I have managed to cover only 2500 (50%) and my deadline is dangerously close?
Simple. I add 5000 lines of unnecessary code that I can surely cover by just one function call, so that the overall line number now is 10000 and covered lines are 7500, making my coverage percentage a sweet 75.
For this purpose they introduced a few full classes with a lone method in each of them. The method starts with,
Integer i = 0;
and continues with a repetition of the following line thousands of times.
i++;
And they had the audacity to copy and paste this repetitive ‘code’ throughout a bulky method and across classes in such a reckless manner that you could see a misplaced tab in first line replicated exactly in every 100th line or so.
Now all that is left for you to do is call this method in a test class, and you can cover scores of lines without breaking a sweat. All the code that actually matters may lie untested in automated coverage check, glaring red if one should care to take a look at, but you have effectively hoodwinked Salesforce deployment mechanism.
And the aftermath is even crazier. Seeing the way hoards of components could be moved in without having to embark on the tedious process of writing test classes, this technique acquired a status equivalent to ‘Salesforce best practices’ in our practice. In almost all the main orgs, if you search for it, you can find a class with streams of ‘i++;’ flowing along the screen for as far as you have the patience to scroll down.
Well, these cloaked dastards remained undetected for years before some of the untested scenarios started reeking. More sensible developers fished out the ‘i++;’ classes, raised the alarm and got down to clean up the mess. Just removing those classes drove the overall production coverage to abysmal low, preventing any form of interaction with production. What can I say, that kept many of us busy for at least a month.
I wouldn’t call the ‘developers’ that put this code in dumb. I would rather go for ‘wicked’. The higher heads and testers who didn’t care to look while this passed under their noses do qualify as dumb.
And the code… Man, that’s the dumbest thing I’ve ever seen.
For Google, other than data structure and algorithms, what else should I prepare for in an interview?
Ask your recruiter.
If you are in the pipeline and you have interviews scheduled, then your recruiter will know exactly what loop will be set up for you and what kind of questions you may have. Recruiters try to get their candidates all the information they need to approach the interviews at the top of their potential, so ask the everything you need to know.
The actual answer depends on the candidate level and profile, the composition of the interviews is pretty much bespoke.
Would Elon Musk pass the Google, Amazon, or Facebook technical interview for the software engineer position?
I think it is likely he will pass the interview if the job description includes the following text:
The successful candidate will have built a brand new car and launched it into interplanetary orbit, using a rocket that they also built.
But will he even want the job?
https://www.youtube.com/channel/UCjxhDXgx6yseFr3HnKWasxg
How difficult is it to find highly talented software developers?
Dev: Alright, let the competition begin!
Startup A: We will give you 50% of the revenue!
Startup B: To hell with it, we will give you 100%!
Startup A: Eh… we will give you 150%!
TL;DR: Nearly impossible. If you are a Google-sized company, of course. Totally impossible in other cases.
I run an outsourcing company. Our statistics so far:
- 500 CVs viewed per month
- 50 interview invitations sent per month
- 10 interviews conducted per month
- 1 job offer made (and usually refused) per month
And here we are looking for a mid-level developers in Russia.
Initially we wanted to hire some top-notch engineers and were ready to pay “any sum of money that would fit on the check”. We sent many invitations. Best people laughed at us and didn’t bother. Those who agreed – knew nothing. After that we had to shift our expectations greatly.
Still, we manage to find good developers from time to time. None of them can be considered super-expert, but as a team they cooperate extremely effectively, get the job done and all of them have that engineering spirit and innate curiosity that causes them to improve.
This is as good as an average company can get.
What is something worth knowing that people working at Google know and others don’t?
It takes constant human effort to keep sites like Google and Gmail online. Right now a Google engineer is fixing something that no one will ever know was broken. Some server somewhere is running out of memory, a fiber link has gone down, or a new release has a problem and needs to be rolled back. There are careful procedures, early warnings, and multiple layers of redundancy to ensure that problems never become visible to end users, but.
Sometimes problems do become visible but not in a way that an individual user can attribute to the site. A request might not get a prompt response, or any at all, but the user will probably blame the internet or their computer, not the site. Google itself is very rarely glitchy, but services like image search do sometimes have user visible problems.
And then of course, very rarely, a giant outage brings down something giant like YouTube or Google Cloud. But if it weren’t for an army of very smart, very diligent people, outages would happen much more often.
What do 10x software developers understand that other programmers don’t?
It’s what they don’t understand. 10x software engineers don’t really understand their job description.
They tend to think all these other things are their responsibility. And they don’t necessarily know why they’re doing all these other things. They just sense that it’s the right thing to do. If they spot something is wrong, they will just fix it. Sometimes it even seems like they’re not in control of what they do. It’s like a conscientiousness overdose.
10x engineers are often all over the code base. It is like they had no idea they were just part of one eng team.
Why don’t big tech companies like Google, Microsoft, and Facebook care about work experience and previous projects when interviewing software engineering candidates and rely completely on programming problems?
Thanks for the A2A.
I don’t think the premise behind the question is entirely true. These companies rely completely on programming problems with junior candidates that are not expected to have significant experience . Senior candidates do, in fact, get assessed based on their experience, although it might not always feel like it.
Let me illustrate this with an interview process I went through when interviewing for one of the aforementioned companies (AFAIK it’s typical for all the above). After the phone screen, there was a phone site interview with 5 consecutive interviews – 2 whiteboard coding + 2 whiteboard architecture problems + 1 behaviour interview. On the surface, it looks like experience doesn’t play a part, but, SURPRISE, experience and past projects play part in 3 interviews out of 5. A large part of the behavioural interview was actually discussing past projects and various decisions. As for the architecture problems – it’s true that the problem discussed is a new one, but those are essentially open ended questions, and the candidates experience (or lack thereof) clearly shines through. Unlike the coding exercises, these questions are almost impossible to solve without tackling something similar in the past.
Now, here a few reasons to why the emphasis is still on solving new problems and not diving into the candidates home territory, in no particular order:
- Companies do not want to pass over strong candidates that just happen to be working on some boring stuff.
- Most times companies do not want to clone a system that the candidate has worked on, so the ability to learn from experience, and apply it to new problems is much more valuable.
- When the interviewer asks different candidates to design the same system, they can easily compare different candidates against one another. The interviewer is also guaranteed to have a deep understating of the problem they want the candidate to solve.
- People can exaggerate (if not outright lie) their role in working on a particular project. This might be hard to catch-on in one hour, so it’s to avoid in the first place.
- (This one is a minor concern, but still) Large companies hire by committee, where interviewers are gathered from the whole company. The fact that they shouldn’t discuss previous projects, removes the need to coordinate on questions, by preventing a situation where two interviewers accidentally end up talking about the same system, and essentially doing the interview twice.
I hope that adds some clarity.
As a teenager, what can I do to become an engineer/entrepreneur like Elon Musk? What skills can I start learning to succeed as an engineer/entrepreneur?
Originally Answered: What can I, currently 17 years old, do to become an engineer/entrepreneur like Elon Musk?
This is a quick recap of my earlier response to a similar question on Quora:
I would recommend that you take a close look at the larger scheme of things in your life, by spending some time and effort to design your life blueprint, using Elon Musk as your inspiration and/or visual model.
By the way, here’s my quick snapshot of his beliefs and values:
1) Focus on something that has high value to someone else;
2) Go back to first principles, so as to understand things more deeply and widely, especially their implications;
3) Be very rigourous in your own self analysis; constantly question yourself, especially on the practicality of the idea(s) you have;
4) Be extremely tenacious in your pursuits;
5) Put in 100 hours or more every week, as sweat equity of intense efforts and focused execution count like hell;
6) Constantly think about how you could be doing better, faster, cheaper and smarter;
7) Relentlessly and ruthlessly think about how to make a better world;
Again, here’s my quick snapshot of his unique traits and characteristics:
1) Be a voracious reader.
2) Be intrinsically driven.
3) (F)ollow (o)ne (c)ourse (u)ntil (s)uccess. That’s Focus!
4) Develop a steadfast problem solving attitude.
5) Employ a physics-mind or first principles in problem solving.
6) Work doubly hard, and a lot, and diligently.
7) Welcome negative feedback.
Nonetheless, here is a simple template:
1) First and foremost, know exactly what you want, in terms of compelling, inspiring and overarching long-range goals and objectives:
a) what do I want to be?
b) what do I want to do?
c) what do I want to have?
d) what do I want to improve?
e) what do I want to change?
in tandem with the following major life dimensions in your life:
i) academic pursuit;
ii) mental development;
iii) career aspirations;
iv) physical health;
v) financial wealth;
vi) family relationships;
vii) social networking;
viii) recreational ventures (including hobbies, interests, sports, vacations, etc.);
ix) spiritual development (including contributions to society, volunteering, etc.);
2) Translate all your long-range goals and objectives in (1) into specific, prioritised and executable tasks that you need to accomplish daily, weekly, monthly, quarterly and even annually;
3) With the end in mind as formulated in (1) and (2), work out your start-point, endpoint and the developmental path of transition points in between;
4) Pinpoint specific tasks that you need to accomplish at each transition point till the endpoint;
5) Establish metrics to measure your progress, or milestone accomplishments;
6) Assign and allocate personal accountability, as some tasks may need to be shared, e.g. with team members, if any;
7) Identify and marshal resources that are required to get all the work done;
[I like to call them the 7 M’s: Money; Methods; Men; Machines; Materials; Metrics; and Mojo!]
8) Schedule a timetable for completion of each predefined task;
9) Highlight potential problems or challenges that may crop up along the Highway of Life, as you traverse on it;
10) Brainstorm a slew of possible strategies to deal with (9);
This is your contingency plan.
11) Institute some form of system, like a visual Pert Chart, to track, control and monitor your forward trajectory, as laid out in your systematic game plan, in conjunction with all the critical elements of (4) to (10);
12) Follow-up massively and follow-through consistently your systematic game plan;
13) Put in your sweat equity of intense effort and focused execution;
14) Stay focused on your strategic objectives, but remain flexible in your tactical execution;
Godspeed to you, young man!
Why may a software engineer struggle in a Google/Facebook onsite interview despite solving most of the LeetCode questions?
For a whole bunch of reasons.
You aren’t so stressed and nervous when you are practicing LeetCode, because your career doesn’t depend on how well you do while solving LeetCode.
When solving LeetCode, you aren’t expected to talk to the interviewer to get clarifications on the problem statement or input format. You aren’t expected to get hints and guidance from the interviewer, and to be able to pick them up. You aren’t expected to be able to communicate with other human beings in general, and to be able to talk about technical details of your solution in particular. You aren’t expected to be able to prove and explain your idea in clear, structured way. You aren’t expected to know how to test your solution, how to scale it, or how to adjust it to some unexpected additional constraints or changes. You may not be able to simply get constraints on input size and use them to figure out what is the complexity of expected solution. You have limited amount of time, so if you slowly got through most of the LeetCode, you may still struggle to get stuff done in 45 minutes. And many more… For all these things, you don’t need them to solve LeetCode, so you usually don’t practice them by solving LeetCode; you may not even know that you need to improve something there.
To sum it up: two main reasons are:
- Higher stakes.
- Lack of skills that are required at typical Google/Facebook interview, but not covered by solving LeetCode problems on your own.
You should also keep in mind that LeetCode isn’t the list of problems being asked at Google or Facebook interviews. If anything, it is more of a list of problems that you aren’t going to be asked, because companies ban leaked questions 🙂 You may get a question that is surprisingly different from what you did at LeetCode.
And sometimes you simply have a bad day.
I failed all technical interviews at Facebook, Google, Microsoft, Amazon, and Apple. Should I give up the big companies, keep improving my algorithm skills, and try some small startups?
Originally Answered: I failed all technical interviews at Facebook, Google, Microsoft, Amazon and Apple. Should I give up the big companies and try some small startups?
Wanted to go Anonymous for obvious reasons.
Reality is stranger than Fiction.
In 2010: After graduation, I was interviewed by one of the companies mentioned above for an entry level Software Engineering Role. During the interview, the person tells me: ‘You can never be a Software Engineer’. Seriously? Of-course I didn’t get hired.
In 2013: I interviewed again with the same company but for a different department and got hired.
Fast Forward to 2016 Dec: I received 2 promotions since 2013 and now I am above the grade level of the guy who interviewed me. I remember the date, Dec 14 2016, I went to his desk and asked him to go out for a coffee. Initially he didn’t recognize me but later he did and we went out for a coffee. Needless to say, he was apologetic for his behavior.
For me, it felt REALLY GOOD. Its a story I’ll tell my Grandkids! 🙂
I have 3 years of experience as a software developer. Should I expect algorithms at an interview at FAANG + Microsoft?
Big tech interviews at FAANG companies are intended to determine – as much as possible – whether you’ve got the knowledge and attributes to be a successful employee. A big part of that for software developers is familiarity with a good set of data structures and algorithms. Interview loops vary, but a good working knowledge of common algorithms will almost always come in handy for both interviews and the job.
Algorithm-related to questions I was asked in my first five years, or that I ask people with less than 5 years: sorting, searching, applying hashes correctly, mapping, medians and averages, trees, linked lists, traveling salesman (I was asked this a couple times, never asked it), and many more.
I never recommend an exhaustive months-long review before an interview, but it’s always a good idea to make sure you’re current on your basics: hash tables and sets, string operations, working with arrays and vectors and lists, binary trees, and linked lists.
For more information on how interviews work and what to expect for big tech interviews, you may want to watch some of my videos in this playlist: Big Tech InterviewsVideos about interviewing at the big tech companies like Microsoft, Google/Alphabet, Amazon, and Facebook.
How true is it that learning Python programming language first will make it harder to learn other programming languages later down the line?
Compared to other modern languages, python has two features that make it attractive, and then also make learning a second language difficult if you started with python. The first is that, despite some minor steps to allow annotation, python is loosely and dynamically typed. The second is that python provides a lot of syntactic sugar; this is shorthand, like a map function, where you can apply a function to each element in a data structure.
Do these features make it harder to switch to another language that is strongly and statically typed? For some people, yes, and for others, no.
Some programmers are naturally curious what’s happening under the hood. How are data being represented and manipulated? Why does an operation produce one type of result in one situation, and another type of result in another situation? If you are the kind of person who asks these questions, you are more likely to have an easier time transitioning. If you are a person who finds these questions uninteresting or even distasteful, transitioning to another language can be very painful.
As a software engineer, how do you make your resume stand out from the crowd?
I have excellent skills and experience on my resume, which makes it stand out.
Seriously, there is no magical spell that will make a crappy resume attractive to recruiters. Most people give up believing in magic after they are 5 or 6 years old. A software engineer who believes in magic is not a good candidate for hire.
What are some secrets about working for big tech companies that you didn’t know before joining those companies?
All those complaints you have about their products? The people working there complain about the same exact things. Microsoft employees complain about how slow Outlook is. Google employees complain about everything changing all the time. Salesforce employees complain about how hard our products are to use.
So why don’t we do something about it? There are a few possible answers:
- We are actively doing something about it right now and it will be fixed soon.
- The problem is technically difficult to fix. For example, it’s currently beyond the state of the art to change the wake word (“Alexa”/”OK Google”) to a user-selected word. A variation of this is the problem that’s more expensive to fix than the amount of annoyance saved.
- The team responsible for that functionality has problems. Maybe they have a bad manager or have been reorged a lot, and as a result they haven’t been doing a good job. Even once the problem is solved, it can take a long time to catch up.
- The problem is related to making money. For example, Microsoft used to have a million different versions of Office, each including different programs and license restrictions. It was super confusing. But the bean counters knew how much extra money the company made from these bundles, compared to a simpler scheme, and it was a lot. So the confusion stayed.
- The problem is cultural. For example, Google historically made its reputation by offering new features constantly. Everything about the culture was geared towards change and innovation. When they started making enterprise products, that cultural became baggage.
But none of that keeps the employees from complaining.
I can’t understand the solution of LeetCode. Can I recite and write from my memory them to achieve the effect of learning?
That’s perhaps the first stage of learning, recitation.
Using the four-stage model of learning that goes
- Unconscious Incompetence
- Conscious Incompetence
- Conscious Competence
- Unconscious Competence
that’s maybe a 2 to 2.5 there. You know you haven’t really understood why you are doing things that way and without detailed step-by-step, you don’t yet know how you would design those solutions.
You need to step back a bit, by reviewing some working solutions and then using those as examples of fundamentals. That might mean observing that there is a for() loop, for example – why? What is it there for? How does it work? What would happen if you changed it? If you wanted to use a for loop to write out “hello!” 8 times, how would you code that?
As you build up the knowledge of these fundamental steps, you’ll be able to see why they were strung together the way they were.
Next, practice solving smaller challenges. Use each of these tiny steps to create a solution – one where you understand why you chose the pieces you chose, what part of the problem it solves and how.
As a software engineering hiring manager, would you be concerned if the candidate who has applied for a position has changed 3 jobs in 4 years?
Early 2020 has been a very rough period for many companies who laid off tons of good people, many of which have bounced to a company who was not a good fit and eventually went to a third one. Forced remote work was also difficult for many folks. So in the current context, having changed 3 jobs in the last 4 years is really a non-event.
Now more generally, would my hiring recommendation be influenced by a candidate having changed jobs several times in a short period of time?
The assumption here is that if a candidate has switched jobs 3 times in 4 years, there must be something wrong.
I think this is a very dangerous assumption. There are lots of things that cause people to change jobs, sometimes choice, sometimes circumstances, and they don’t necessarily indicate anything wrong in the candidate. However, what could be wrong in a candidate can be assessed in the interview, such as:
- is the candidate respectful? Is the candidate able to disagree consrtuctively?
- does the candidate collaborate?
- Does the candidate naturally support others?
- Has the candidate experience navigating difficult human situations?
- etc, etc.
There are a lot of signals we can detect in the interview and we can act upon them. Everything that comes outside of the interview / outside of reference check is just bias and should be ignored.
The hiring decision should be evidence-based.
What does it feel like to have an IQ of 140?
My IQ was around 145 the last time I checked (I’m 19).
I feel lots of gratitude for my ability to deeply understand and comprehend ideas and concepts, but it has definitely had its “downsides” throughout my life. I tend to think very deeply about things that I find interesting and this overwhelming desire to understand the world has led me to some dark places. When I was around 9 or 10, I discovered the feeling of existential panic. I had watched an astronomy documentary with my father (who is a geoscience professor) and was completely overwhelmed with the fact that I was living on an unprotected orb, orbiting around a star at speeds far faster than I could even comprehend. I don’t think anyone in my family expected me to really grasp what the documentary was saying so they were a bit alarmed when I spent that whole night and most of the next week panicking and hyperventilating in my bedroom.
I lost my mom to suicide when I was 11 which sent me into a deep depression for several years. I found myself thinking a lot about death and the meaning of human existence in my earlier teenage years. I was really unmotivated to do school work all throughout high school because I found no meaning in it. I didn’t understand why I was alive, or what being alive meant, or if there even was any true meaning to life. I constantly struggled to see how any of it truly mattered in the long run. What was the point of going to the grocery store or hanging out with my friends or getting a drivers license? I was an overdeveloped primate forced to live in and contribute to a social group that I didn’t ask to be in. I was living in a strange universe that made no sense and I was being expected to sit at a desk for 8 hours every day? Surrounded by people who didn’t care about anything except clothing and football games? No way man, count me out. I spent a lot of nights just sitting in my bedroom wondering if anything I did really mattered. Death is inevitable and the whole universe will one day end, what’s the point. I frequently wondered if non-existence was inherently better than existence because of all of the suffering that goes hand in hand with being a conscious being. I didn’t understand how anyone could enjoy playing along in this complex game if they knew they were all going to die eventually.
Heavy stuff, yeah.
When I was 18 I suddenly experienced what some people label as an “ego death” or a “spiritual awakening” in which it suddenly occurred to me that the inevitably of death doesn’t mean that life itself is inherently meaningless. I realized that all of my actions affect the universe and I have the ability to set off chain reactions that will continue to alter the world long after I’m gone. I also realized that even if life is inherently meaningless, then that is all the more reason to enjoy being alive and to experience the beauty and wonder of the world while I’m still around. After that day I began meditating daily to achieve a deeper awareness of myself and try to find inner peace. I began living for the experience of being alive and nothing else. All of this has brought me great peace and has allowed me to enjoy learning again. For so long learning was terrifying to me because it meant that I was going understand new information that could potentially terrify me. Information that I could not unlearn. I have become a very emotionally sensitive person after the death of my mother, so I simply could not handle the weight of learning about existential concepts for a while. Now that I’ve been able to find a state of peace within myself and radically accept the fact that I will die one day (and that I do not know what occurs after death) I have begun to enjoy learning again! I read a lot of nonfiction and fiction alike. I enjoy traveling and seeing the world from as many different perspectives as possible. Talking to new people and attempting to see my world through their eyes is very enjoyable for me. Picking up new skills is generally very easy for me and I spend a lot of my free time pondering philosophical issues, just because it’s fun for me. I’m not a very social person, I like having a few close friends, but I mostly enjoy being alone.
So all in all, I think having an IQ of 140+ is a very turbulent experience that can be very beautiful! When you are able to truly understand deep concepts, it can seriously freak you out, especially when you’re searching for meaning and answers to philosophical problems. If I hadn’t embraced a way of life that revolves around radically acceptance, I don’t think I would have the guts to look as deeply into some things as I do. However, since I do have that safety cushion, I’m able to shape my perception of the world with the knowledge that I learn. This allows me to see incredible beauty in our world and not take things too personally. When I have a rough day, all I need to do is sit on my roof for half an hour and look at the stars. It reminds me that I am a very small animal in a very big place that I know very little about. It really puts all of my silly human problems in perspective.
If no-code is the future, is a CS major even worth it?
If you can explain to me how “no-code is the future”, maybe there’s a useful response to this.
As far as I can tell, “no-code” means that somebody already coded a generic solution and the “no-code” part is just adapting the generic solution for a specific problem.
Somebody had to code the generic solution.
As to the second part, “is a CS major even worth it?” I’ve had a 30+ year career in software engineering, and I didn’t major in CS. That hasn’t kept me from learning CS concepts, it hasn’t kept me from delivering good software, and it hasn’t stopped me from getting software jobs.
Is a CS major even worth it? Only the student knows the answer to that.
How can we solve the issue of English speakers advantage in software programming and computer related fields over other languages speakers, considering the fact that programming languages are mostly English based?
IT’S NOT ABOUT THE PROGRAMMING LANGUAGE:
People have written no-English versions of many programming languages – but they aren’t used as much as you’d think because it’s just not that useful.
Consider the C language – there are no such English words as “int”, “bool”, ”enum”, “struct”, “typedef”, “extern”, or “const”. The words “auto”, “float” and “char” are English words – but with completely different meanings to how they are used in C.
This is the complete list of C “reserved words” – things you’d have to essentially memorize if you’re a non-English speaker…
auto, else, long, switch, break, enum, register, typedef, case, extern, return, union, char, float, short, unsigned, const, for, signed, void, continue, goto, sizeof, volatile, default, if, static, while, do, int, struct, double
…but very few of those words are used in their usual English meanings…and you have to just know what things like “union” mean – even if you’re a native english speaker.
But if you really think there is an advantage to this being your native language then:
#define changer switch
#define compteur register
#define raccord union
…and so on – and now all of your reserved words are in French.
I don’t think it’s going to help much.
IT”S ABOUT LIBRARIES AND DOCUMENTATION:
The problem isn’t something like the C language – we could easily provide translations for the 30 or so reserved words in 50 languages and have a #pragma or a command to the compiler to tell it which language to use.
No problem – easy stuff.
However, libraries are a much bigger problem.
Consider OpenGL – it has 250 named function, and hundreds of #defined tokens.
glBindVertexArray would be glLierTableauDeSommets or something. Making versions of OpenGL for 50 languages would be a hell of a lot more painful.
Then, someone has to write documentation for all of that in all of those languages.
But a program written and compiled against French OpenGL wouldn’t link to a library written in English – which would be a total nightmare.
Worse still, I’ve worked on teams where there were a dozen US programmers, two dozen Russians and a half dozen Ukrainians – spread over two continents – all using their own languages ON THE SAME PIECE OF SOFTWARE.
Without some kind of control – we’d have a random mix of variable and function names in the three languages.
So the rule was WE PROGRAM IN ENGLISH.
But that didn’t stop people from writing comments and documentation in Russian or Ukranian.
SO WHAT IS THE SOLUTION?
I don’t think there actually is a good solution for this…picking one human language for programmers to converse in seems to be the best solution – and the one we have.
So which language should that be?
Well according to:List of languages by total number of speakers – Wikipediahttps://en.wikipedia.org/wiki/List_of_languages_by_total_number_of_speakers
There are 1.3 billion English speakers, 1.1 billion Mandarin speakers, 600 million Hindi speakers, 450 Spanish speakers…and no other language gets over half of that.
So if you have to pick a single language to standardize on – it’s going to be English.
Those who argue that Mandarin should be the choice need to understand that typing Mandarin on any reasonable kind of keyboard was essentially impossible until 1976 (!!) by which time using English-based programming languages was standard. Too late!
SO – ENGLISH IT IS…KINDA.
Even though we seem to have settled on English the problems are not yet over.
British English or US English – or some other dialect?
As a graphics engineer, it took me the best part of a decade to break the habit of spelling “colour” rather than “color” – and although the programming languages out there don’t use that particular word – the OpenGL and Direct3D libraries do – and they use the US English spelling rather than the one that people from England use in “English”.
ARE PROGRAMMERS UNIQUE IN THIS?
No – we have people like airline pilots, ships’ captains.
ICAO (International Civil Aviation Organization), require all pilots to have attained ICAO “Level 4” English ability. In effect, this means that all pilots that fly international routes must speak, read, write, and understand English fluently.
However, that’s not what happened for ships. In 1983 a group of linguists and shipping experts created “Seaspeak”. Most words are still in English – but the grammar is entirely synthetic. In 1988, the International Maritime Organization (IMO) made Seaspeak the official language of the seas.
As a software engineer would you join a well established & reputed tech company although work is less interesting or would you join a startup where the work is more exciting given the compensation for both the positions are comparable?
Here’s the thing. The compensation will never be comparable.
When you join a big tech, public company, all of your compensation is public. Also it’s relatively easy to get a fair estimate of what comp looks like a few years down the road.
When you join a private company, the comp is a bet on a successful exit.
In 2015, Zenefits was a super hot company. Zoom had been around for.4 years and was very confidential.
In a now infamous Quora question[1] a user asked wether they should take an offer at Zenefits or Uber. As a result, The Zenefits CEO rescinded their offer. But most people would have chosen an offer at Zenefits or Uber, whose IPO was the most anticipated back then, over one at Zoom.
And yet Zenefits failed spectacularly, Uber’s IPO was lackluster, while Zoom went beyond all expectations.
So this is mostly about to risk aversion. Going to a large co means a “golden resume” that will always get you interviews, so it has a lot of long term value.
Working in a large company has other benefits. Processes are usually much better and there’s a lot to learn. This is also the opportunity to work on some problems at a huge scale. No one has billions of users outside of Google, Meta, Apple or Microsoft.
But working in a small private company whose valuation explodes is the only way for a software engineer to become very wealthy. The thing is though that it’s impossible for an aspiring employee to tell which company is going to experience that growth versus fail.
Footnotes[1] What is the better way to start my career, Uber or Zenefits?
What are the pros and cons to consider when quitting a job?
Originally Answered: What are the pros and cons of quitting a job?
The pro’s and con’s really depend on the specific situation.
(1) When quitting for a new position…
Pros:
- Better pay & benefits
- More promotion opportunities
- New location
- New challenges (old job may have been boring)
- New job aligned to your interests.
Cons:
- New job/company was seriously misrepresented
- “New boss same as the old boss” (no company is perfect!)
- You might have wanted a new challenge, but you are now over your head.
Note: if you have a job and are not desperate, please do your homework and remember you are also interviewing them! You want a better job in most cases (unless that moving thing is going on).
(2) When quitting over a conflict…
Pros:
- Can sleep at night (providing it was a ethical issue and you were in the right)
- You showed them who is the boss!
- Plus, you wont be on the local news if they get sued, or the IRS does a audit.
- Again, if it was a toxic environment that you get to live as opposed to a stroke on the job! No job is worth it that is impacting your health, including mental health.
Cons:
- No unemployment in most states if you just up and quit.
- Job search with no income puts a lot of pressure at some point to take any job
- the good news though, is you can continue looking while earning a paycheck (and hopefully still growing skills & experience)
The reason so many people are quitting now…
Note there is a third category, when you quit due to a lifestyle change. In this case, we are looking a women quitting to be a full-time mother, or someone going back to school. A spouse getting promoted but with a move might also place the other mate in this position…
Pro:
- You get to live the life you want.
- You are preparing for a better career
Con:
- Loss of income
- Reduced social interaction (for the full-time mom)
Note here that most couples that decide to do the stay at home mom generally plan ahead so one income will cover their expenses.
Second, I also don’t consider serious health issues when you leave the work force in general to fall under the scope of this discussion.
Is practicing 500 programming questions on LeetCode, HackerEarth, etc, enough to prepare for a Google interview?
Originally Answered: Is practicing 500 programming questions on LeetCode, HackerEarth, etc enough to prepare for Google interview?
If you have 6 months to prepare for the interview I would definitely suggest the following things assuming that you have a formal CS degree and/or you have software development experience in some company:
Step 1 (Books/Courses for good understanding)
Go through a good data structure or algorithms book and revise all the topics like hash tables, arrays and strings, trees, graphs, tries, bit hacks, stacks, queues, sorting, recursion, and dynamic programming. Some good books according to me are:
The Algorithm Design Manual: Steven S Skiena: 9781848000698: Amazon.com: Books
Algorithms (4th Edition): Robert Sedgewick, Kevin Wayne: 8601400041420: Amazon.com: Books
There are other books as well and you can use any good book which you are comfortable with.
Some good courses to take on this topic if you need a more thorough understanding: (since you have 6 months time)
Algorithms, Part I – Princeton University | Coursera
Algorithms, Part II – Princeton University | Coursera
The Stanford Coursera algorithms courses are also very good and you can look at them if you have time. It’s a bit more theoretical though.
Step 2 (Programming practice for algorithms and data structures)
Once you are done with Step 1 you need a lot of practice. It need not be a set number of problems like 500 or 1000. The best way to practice problems is to mimic an interview setting and time yourself for half an hour and solve a problem without any distraction. The steps here are to read a problem, think of a brute force solution that works very quickly, and then think of an optimized version that works and then write clean working code and come up with test cases within half an hour. Most of the top companies ask you 1 or 2 medium problems or 1 hard problem in 45 mts to 1 hour. Once you are done solving the problem you can compare your solution with the actual solution and see if there is scope to improve your solution or learn from the actual solution.
If you do the math it takes half an hour to solve a problem and at least 15 mts to look and compare with the correct solution. So 500 problems take 500 * 45 mts = 375 hours. Even if you spend 5 solid hours a day for problem-solving it comes to 75 days (2.5 months). If you are in a full-time job it’s hard to spend so much time every single day. Realistically if you spend 2–3 hours a day we are talking about 5 months just for practicing 500 problems. In my opinion, you don’t need to solve so many problems to crack the interview. All you need is a few problems in each topic and understand the fundamentals really well. The different topics for algo and ds are:
arrays and strings, bit hacks, dynamic programming, graphs, hash tables, linked lists, math problems, priority queues, queues, recursion, sorting, stacks, trees, and tries. As a starter try to solve 4–5 problems in each topic after you finish step 1 and then if you have time solve 2–3 problems a day for fun in each topic and you should be good. Also, it is far better to solve 5 problems than to read 50 problems. In fact, trying to cover problems by reading problems is not going to be of any use.
Step 3 (this can be done in parallel with step 1) (Systems Design)
Practice problems in systems, design (distributed systems, concurrency, OO design). These questions are common in Google and other top companies. The best way to crack this section is to actually do complex systems projects at work or school projects. There are lots of resources online which are very good for preparation for this topic.
Edit: Since I have received some request to point some resources I am listing some of my favorite ones:
Data Manipulation at Scale: Systems and Algorithms – University of Washington | Coursera
HiredInTech’s Training Camp for Coding Interviews
Eventually Consistent – Revisited
Step 4 (behavioral and resume)
Please know your resume in and out and make sure you can explain all the projects mentioned in the resume. You should be able to dive as deep as needed (technically) for the projects mentioned. Also do enough research about the company you are interviewing, the product, engineering culture and have good questions to ask them
Step 5 (mock interviews)
Last but not least please make sure you have some good friends working in a good company or your classmate mock interview you. You also have several resources online for this service. Also, work on the feedback you get from the mock interview. You can also interview a few companies you are not interested to work as a practice interview before your goal companies.
I already know DSA and can solve 40%-50% LeetCode easy problems. Is it possible for me to be prepared for a Google coding interview in the next 2-3 months? If it’s possible, then how?
It is possible for some people; I don’t know whether it is possible for you.
You’re solving 50% of easy problems. Reality check: that’s…cute. Your target success rate, to have a good chance, should be near-100% on Easy, 75% on Medium, and 50% on Hard. On top of that, non-Leetcode rounds like system design should be solid, too.
You can see there’s a big gap between where you are and where you need to be.
The good news is that despite how large that gap is, without a doubt, there have been cases of people being able to learn fast enough to cover that gap in 90 days. These cases are not at all common, and I will warn you that the vast majority of people who are where you are now cannot get to where you need to be in 90 days. So, the odds are against you, but you might be better than the odds would say.
What is special about the situations of the people who can get there that fast? Off the top of my head, the key factors are:
- A strong previous background in CS and algorithms
- Being able to spend a significant amount of time daily to study
- High aptitude / talent / intelligence for learning these sorts of concepts
- Having an effective methodology for learning. The fact that you’re actively solving problems on Leetcode is a decent start here.
If the above factors describe you, you might be better off than the odds would suggest. It is at least possible that you could achieve your goal.
Good luck and happy job hunting!
I have heard I need to spend at least 1000 hours to prepare for the Google or Facebook interview. Is it true?
(Note: I’ve interviewed hundreds of developers in my time at Facebook, Microsoft and now as the co-founder and CEO of Educative. I’ve also failed several coding interviews because I wasn’t prepared. At Educative, we’ve helped thousands of developers level up their careers with hands-on courses on programming languages, system design, and interview prep.)
Is Interview Prep a Full-time Job?
Let’s break it down. A full-time job – 40 hours per week, 52 weeks per year – encompasses 2080 hours. If you take two weeks of vacation, you’re actually working 2,000 hours. The 1,000 hours recommendation is saying you need six months of full-time work to prepare for your interview at a top tech company. Really?
I think three months is a reasonable timeframe to fully prepare. And if you’ve interviewed more recently, studying the specific process of the company where you’re applying can cut that time down to 4-6 weeks of dedicated prep.
I’ve written more about the ideal interview prep roadmap for DEV Community, but I’ll give you the breakdown here.
The “Secret” to a Successful Interview Prep Plan
First of all, I want to be clear that there’s no silver bullet to interview prep. But during my time interviewing candidates at Facebook and Microsoft, I noticed there was one trait that all the best candidates shared: they understood why companies asked the questions they did.
The key to a successful interview prep program is to understand what each question is actually trying to accomplish. Understanding the intent behind every step of the interview process helps you prepare in the right way.
A lot of younger developers think they need to be experts in a few programming languages, or even just one language in order to crack the developer interview. Writing efficient code is a crucial skill, but what software companies are actually looking for (especially the big ones with custom libraries and technology stacks that you will be expected to learn anyway) is an understanding of the various components of engineering, as well as your creative problem-solving ability.
That breaks down into five key areas that “Big Tech” companies are focused on in the interview process:
1. Coding
Interviewers are testing the basics of your ability to code. What language should you be using? Start with the language you know best. Especially in larger companies, new syntaxes can be taught or libraries used if you establish you can execute well. I have interviewed people that used programming languages that I barely know myself. I know C++ inside and out, so even though Python is a more efficient language, I would always personally choose to interview using C++. The most important thing is just to brush up on the basics of your favorite programming language.
The questions in coding interviews focus on generic problem-solving, data structures (Mastering Data Structures: An interview refresher), and algorithms. So revisit concepts that you haven’t touched since undergrad to have a fresh, foundational understanding of topics like complexity analysis (Algorithms and Complexity Analysis: An interview refresher), arrays, queues, trees, tries, hash tables, sorting, and searching. Then practice solving problems using these concepts in the programming language you have chosen.
Coding Interview Preparation | Codinginterview has gathered hundreds of real coding questions asked by top tech companies to get you started.
2. OS and Concurrency Concepts
Whether you’re building a mobile app or web-scale systems, it’s important to understand threads, locks, synchronization, and multi-threading. These concepts are some of the most challenging and factor heavily into your “hiring level” at many organizations. The more expert you are at concurrency, the higher your level, and the better the pay.
Since you’ve already determined the language you’re using in (1), study up on process handling using that same language. Prepare for an interview – Concurrency
3. System Design
Like concurrency problems, system design is now key to the hiring process at most companies, and has an impact on your hiring level.
System Design Interviews (SDIs) are challenging for a couple reasons:
- There isn’t a clear-cut answer to an open-ended question where a candidate must work their way to an efficient, meaningful solution to a general problem with multiple parts.
- Most candidates don’t have a background designing large-scale systems in the first place, as reaching that level is several years into a career path and most systems are designed collaboratively anyway.
For this reason, it is important to spend time clarifying the product and system scope, a quick back-of-the-envelop estimation, defining APIs to address each feature in the system scope and defining the data model. Once this foundational work is done, you can take the data model and features to actually design the system.
If that seems like a daunting task, you can brush up on a few major APIs for free on Educative or dig deeper with our Scalability & System Design learning path, which includes the Grokking the System Design Interview course.
4. Object-Oriented Design
In Object-Oriented Design questions, interviewers are looking for your understanding of design patterns and your ability to transform the requirements into comprehensible classes. You spend most of your time explaining the various components, their interfaces and how different components interact with each other using the interfaces. Interviewers are looking for your ability to identify patterns and to apply effective, time-tested solutions rather than re-inventing the wheel. In a way, it is the partner of the system design interview.
Object-oriented programming deals with bundling certain properties with a specific object, and defining those objects according to its class. From there, you deal with encapsulation, abstraction, inheritance, and polymorphism. [Object-Oriented Basics – Grokking the Object Oriented Design Interview (educative.io)]
5. Cultural Fit
This is the one that doesn’t have a clear cut learning path, and because of that, it is often overlooked by developers. But for established companies like Google and Amazon, culture is one of the biggest factors. The skills you demonstrate in coding and design interviews prove that you know programming. But without the right attitude, are you open to learning? Are you passionate about the product and want to build things with the team? If not, companies can think you’re not worth hiring. No organization wants to create a toxic work environment.
Since every company has a few different distinguishing features in their culture, it’s important to read up on what their values and products are (Coding Interview Preparation | Codinginterview has information on many top tech companies, including Google and Facebook). Then enter the interview track ready to answer these basics:
- Interest in the product, and demonstrate understanding of the business. (Don’t mistake Facebook’s business model, which relies on big data, for AWS or Azure, which facilitate big data as a service. If you’re going into Google, know how user data and personalization is the core of Google’s monetization for its various products and services, while knowing what makes Android unique compared to iOS. Be an advocate.)
- Be prepared to talk about disagreements in the workplace. If you’ve been working for more than a few years, you’ve had disagreements. Even if you’re coming out of school, group projects apply. Companies want to know how you work on a team and navigate conflict.
- Talk about how the company helps you build and execute your own goals both as a technologist and in your career. What are you passionate about?
- Talk about significant engineering accomplishments – what have you built; what crazy/difficult bugs have you solved?
Conclusion
Strategic interview prep is essential if you want to present yourself as the best candidate for an engineering role.
It doesn’t have to take 1,000 hours, nor should it – but at big companies like Google and Facebook where the interview process is so intentional, it will absolutely benefit you to study that process and fully understand the why behind each step.
There are plenty of battle-tested resources linked in my answer that will guide you throughout the prep process, and I hope they can be helpful to you on your career journey.
Happy learning!
I have practiced over 300 algorithms questions on LintCode and LeetCode. I have been unemployed for almost 9 months and I got 8 interviews and all failed in the coding test. I still can’t get any offer. What should I do?
Originally Answered: I have practiced over 300 algorithms questions on LintCode and LeetCode but still can’t get any offer, what should I do?
I have interviewed and been interviewed a number of times, and I have found out that most of the time people (including myself) flunk an interview due to the following reasons:
- Failing to come up with a solution to a problem:
If you can’t come up with even one single solution to a problem, then it’s definitely a red flag since that reflects poorly on your problem solving skills. Also, don’t be afraid to provide a non-optimal solution initially. A non-optimal solution is better than no solution at all. - Coming up with solutions but can’t implement them:
That means you need to work more on your implementation skills. Write lots and lots of code, and make sure you use a whiteboard or pen and paper to mimic the interview experience as much as possible. In an interview you won’t have an IDE with autocomplete and syntax highlighting to help you. Also make sure that you’re very comfortable in your programming language of choice. - Solving the problem but not optimally:
That could mean that you’re missing some fundamental knowledge of data structures and algorithms, so make sure that you know your basics well. - Solving the problem but after a long time, or after receiving too many hints:
Again, you need more problem solving practice. - Solving the problem but with many bugs:
You need to properly test your code after writing it. Don’t wait for the interviewer to point out the bugs for you. You wouldn’t want to hire someone who doesn’t test their code, right? - Failing to ask the interviewer enough questions before diving into the code:
Diving right into the code without asking the interviewer enough questions is definitely a red flag, even if you came up with a good solution. It tells the interviewer that either you’re arrogant, or that you’re reckless. It’s also not in your favor, because you may end up solving the wrong problem. Discussing the problem and asking questions to the interviewer is important because it ensures that both of you are on the same page. The interviewer’s answers to your questions may also provide with some very useful hints that may greatly simplify the problem. - Being arrogant:
If you’re perceived as arrogant, no one will want to hire you no matter how good you are. - Lying on the resume:
Falsely claiming knowledge of something, or lying about employment history is a huge red flag. It shows dishonesty, and no one wants to work with someone who is dishonest.
I hope this helps, and good luck with your future interviews.
How often do tech companies ask LeetCode Hard questions during interviews?
Unless we’re talking about Google, which has problems that are unique to them in comparison to the rest, you can be sure that big tech companies ask LeetCode-style questions quite often. Seeing LeetCode Hard problems specifically, however, is not that common in these interviews, and it’s more likely that you’ll be facing LeetCode Medium questions and one or two Hard questions at best. This is because having a time limit to solve them as well as an interviewer right beside you already adds enough pressure to make these questions feel harder than they normally would be; increasing their difficulty would simply be detrimental to the interviewing process.
I suggest that you avoid using the difficulty of LeetCode questions that you can solve as a way of telling if you’re prepared for your interviews as well because it can be pretty misleading. One reason this is the case is that LeetCode’s environment is different from an interviewing environment; LeetCode cares more about running time and the optimal solution to a problem, while an interviewer cares more about your approach to the question (an intuitive solution can always be optimized further with a discussion between you and the interviewer).
Another reason you should avoid worrying too much about LeetCode-style questions is that FAANG companies are starting to refrain from asking them, as they’re noticing that many candidates come to their interviews already knowing the answer to some of their questions; currently, if your interviewer notices that you already know the answer to the question you’re given, they won’t take it into account and instead will move on to another question, as already knowing how to solve the problem tells them nothing about the way you approach challenging situations in the first place.
Also, you should consider that LeetCode only lets you practice what you already know in coding; if you don’t have a good knowledge of data structures & algorithms beforehand, LeetCode will be a difficult resource to use efficiently, and it also won’t teach you anything about important non-technical skills like communication skills, which is a crucial aspect that interviewers also evaluate. Therefore, I also suggest that you avoid using LeetCode as your only resource to prepare for your technical interviews, as it doesn’t cover everything that you need to learn on its own.
For example, you may want to enroll in a program like Tech Interview Pro as you use LeetCode. TIP is a program that was created by an ex-Google software engineer and was designed to be a “how to get into big tech” course, with over 20 hours of instructional video content on data structures & algorithms and system design.
Another good resource that you could use, this time to cover the behavioral aspect of interviews, is Interviewing.io. With it, you can engage in mock interviews with other software engineers that have worked with Facebook and Google before and also receive feedback on your performance.
You could also read a book like Cracking the Coding Interview, which offers plenty of programming questions that are very similar to what you can expect from FAANG companies, as well as valuable insight into the interviewing process.
Best of luck with your interviews!
Are technical internships like Google, Amazon, and Facebook more selective than getting into Harvard?
Harvard is seen in popular culture as being very selective, and so any funnel which has a conversion rate lower than 5% is going to describe itself as “more selective than Harvard”. “More selective than Harvard” has 70m hits on Google. When Walmart opened a DC store, it hired about 2.5% of the people that sent applications, and ran a story that it was “twice as selective as Harvard”. Tech internships, somewhat unsurprisingly, are harder to get as jobs at Walmart.
Generally speaking, the more LeetCode problems you solve, the better your odds of getting an offer will be. Be careful, however, as using the number of problems you solve on LeetCode as a reference for how ready you are for your technical interviews is misleading, especially if it’s for Google and Facebook. Even if you solve every problem on LeetCode (please don’t try this), there’s still a chance you won’t get an offer, and there are several reasons why.
First of all, coding is not the only thing taken into consideration by interviewers from big tech companies. One of the main things they look for in a candidate is the presence of strong soft skills like teamwork, leadership, and communication. If you’re raising red flags in that department—if the interviewer doesn’t think you have the leadership skills to lead a team down the road, for example—odds are that you’re going to get overlooked. They also expect you’ll be able to clearly explain your thought process before solving a given coding problem, which is something a surprising number of developers have trouble with.
The second problem with using LeetCode alone is that it can only help you practice data structures & algorithms and system design, but not exactly teach you about them. This might not be an issue if you’re solving questions from the Easy section of LeetCode, but once you get to the Medium and Hard problem sets, you’ll need more theoretical knowledge to properly handle these problems.
So, ideally, you’ll want to prepare using resources that help you learn more about DS&A and systems design before you start practicing on LeetCode, and you’ll also want to work on your behavioral skills to ensure you do well there, too. Here are some tools that can help:
- Interviewing.io: A site where you can engage in mock interviews with other software engineers—some of whom have worked at Google and Facebook—and receive immediate, objective feedback on your performance.
- Tech Interview Pro: An interview prep program designed by a former Google software engineer that includes 150+ instructional video lessons on data structures & algorithms, systems design, and the interview process as a whole. TIP members also get access to a private Facebook group of 1,500+ course graduates who’ve used what they learned in the course to land jobs at Google, Facebook, and other big tech companies.
- Educative’s Scalability & System Design for Developers Course: An introductory systems design course that will teach you how to think about architecture trade-offs and design systems at scale for enterprise-level software.
So, using LeetCode on its own would prepare you well for questions about data structures & algorithms, but may leave you unprepared for questions related to systems design and the behavioral aspect of your interviews. But by complementing LeetCode with other resources, you’ll put yourself in a much better position to receive an offer from Google, Facebook, or anyone else. Best of luck.
Dmitry Aliev is correct that this
was introduced into the language before references.
I’ll take this question as an excuse to add a bit more color to this
.
C++ evolved from C via an early dialect called “C with Classes”, which was initially implemented with Cpre, a fancy “preprocessor” targeting C that didn’t fully parse the “C with Classes” language. What it did was add an implicit this
pointer parameter to member functions. E.g.:
- struct S {
- int f();
- };
was translated to something like:
- int f__1S(S *this);
(the funny name f__1S
is just an example of a possible “mangling” of the name of S::f
, which allows traditional linkers to deal with the richer naming environment of C++).
What might comes as a surprise to the modern C++ programmer is that in that model this
is an ordinary parameter variable and therefore it can be assigned to! Indeed, in the early implementations that was possible:
- struct S {
- int n;
- S(S *other) {
- this = other; // Possible in C with Classes.
- this->n = 42; // Same as: other->n = 42;
- }
- };
Interestingly, an idiom arose around this ability: Constructors could manage class-specific memory allocation by “assigning to this” before doing anything else in the constructor. E.g.:
- struct S {
- S() {
- this = my_allocator(sizeof(S));
- …
- }
- ~S() {
- my_deallocator(this);
- this = 0; // Disabled normal destructor post-processing.
- }
- …
- };
That technique (brittle as it was, particularly when dealing with derived classes) became so widespread that when C with Classes was re-implemented with a “real” compiler (Cfront), assignment to this
remained valid in constructors and destructors even though this
had otherwise evolved into an immutable expression. The C++ front end I maintain still has modes that accept that anachronism. See also section 17 of the old Cfront manual found here, for some fun reminiscing.
When standardization of C++ began, the core language work was handled by three working groups: Core I dealt with declarative stuff, Core II dealt with expression stuff, and Core III dealt with “new stuff” (templates and exception handling, mostly). In this context, Core II had to (among many other tasks) formalize the rules for overload resolution and the binding of this
. Over time, they realized that that name binding should in fact be mostly like reference binding. Hence, in standard C++ the binding of something like:
- struct S {
- int n;
- int f() const {
- return this->n;
- }
- } s = { 42 };
- int r = s.f();
is specified to be approximately like:
- struct S { int n; } s = { 42 };
- int f__1S(S const &__this) {
- return (&__this)->n;
- }
- int r = f__1S(s);
In other words, the expression this
is now effectively a kind of alias for &__this
, where __this is just a name I made up for an unnamable implicit reference parameter.
C++11 further tweaked this by introducing syntax to control the kind of reference that this
is bound from. E.g.,
- struct S {
- int f() const &;
- int g() &&;
- };
can be thought of as introducing hidden parameters as follows:
- int f__1S(S const &__this);
- int g__1S(S &&__this);
That model was relatively well-understood by the mid-to-late 1990s… but then unfortunately we forgot about it when we introduced lambda expression. Indeed, in C++11 we allowed lambda expressions to “capture” this
:
- struct S {
- int n;
- int f() {
- auto lm = [this]{ return this->n; };
- return lm();
- }
- };
After that language feature was released, we started getting many reports of buggy programs that “captured” this
thinking they captured the class value, when instead they really wanted to capture __this
(or *this
). So we scrambled to try to rectify that in C++17, but because lambdas had gotten tremendously popular we had to make a compromise. Specifically:
- we introduced the ability to capture
*this
- we allowed
[=, this]
since now[this]
is really a “by reference” capture of*this
- even though
[this]
was now a “by reference” capture, we left in the ability to write[&, this]
, despite it being redundant (compatibility with earlier standards)
Our tale is not done, however. Once you write much generic C++ code you’ll probably find out that it’s really frustrating that the __this
parameter cannot be made generic because it’s implicitly declared. So we (the C++ standardization committee) decided to allow that parameter to be made explicit in C++23. For example, you can write (example from the linked paper):
- struct less_than {
- template <typename T, typename U>
- bool operator()(this less_than self,
- T const& lhs, U const& rhs) {
- return lhs < rhs;
- }
- };
In that example, the “object parameter” (i.e., the previously hidden reference parameter __this
) is now an explicit parameter and it is no longer a reference!
Here is another example (also from the paper):
- struct X {
- template <typename Self>
- void foo(this Self&&, int);
- };
- struct D: X {};
- void ex(X& x, D& d) {
- x.foo(1); // Self=X&
- move(x).foo(2); // Self=X
- d.foo(3); // Self=D&
- }
Here:
- the type of the object parameter is a deducible template-dependent type
- the deduction actually allows a derived type to be found
This feature is tremendously powerful, and may well be the most significant addition by C++23 to the core language. If you’re reasonably well-versed in modern C++, I highly recommend reading that paper (P0847) — it’s fairly accessible.
When an employee is hired, there is a step in the process where they are given a stack of documents to sign that (anecdotally) I’ll venture maybe 1 in 1,000 actually read. One of the least understood (or read) is the notice that the company controls, collects and analyzes all communications, internet activity and data stored on company-owned or -managed devices and systems.
This includes network traffic that flows across their servers. It’s safe to assume that mid-to-large employers are fully aware of the amount of on-the-clock time employees spend shopping, tweeting or watching YouTube, and know which employees are spending inordinate amounts of ‘company time’ shopping on Amazon rather than tackling assignments.
This also include Bring Your Own Device policies— where employees are allowed to use their personal smartphone, tablet or laptop for business purposes. Companies don’t always ‘exploit’ the policy for nefarious surveillance purposes, but employers are within their rights to collect information like location data from your BYOD smartphone both on and off the clock.
An example of where this can hurt employees is when they start to look for another job.
If you email/Slack/message your supervisor and ask for a personal day off to attend to a family matter, but your device logs show you are accessing job-search sites and your location data suggests your aren’t at home or even within the radius of a competitor’s office, they know. This tends to make your boss cranky, and can adversely impact your employment to the point of losing your job.
I disagree with this kind of intrusive surveillance, and the presumption of guilt employees face when they take steps to protect themselves by using encrypted tools like Signal, proxy servers or switching devices to Airplane Mode intrudes on the employee’s legitimate rights to privacy: you may not want your employer to know that you’re seeing a psychiatrist on your lunch hour, and they really have no reasonable expectation for you to disclose this (or not take steps to conceal it.)
- Workplace Privacy and Employee Monitoring
- PDF: https://www.privacyrights.org/printpdf/67553
- This is Your Wakeup Call on Employee Privacy
Facebook recruiting breaking poaching agreements really lead to measurable higher salaries at Google?
I think so. I remember there was a noticeable number of people going to Facebook, and some discussion of it among the employees. And then there was an explicit event where Google rearranged its compensation strategy. Everyone got a huge raise just at that moment, and from that point on the salaries and stock grants became close to the top of the market, as they need to be for a company that hires top talent.
I have no internships. I just graduated with a degree in CS. How can I get a job at FAANG?
If you can’t get FAANG to pay attention to you, you probably need to get another job first. Perhaps one of the companies that are considered to be pretty good would be interested.
It is actually quite hard to get an entry-level role at a top tech company, because where you went to college (and internships, which you don’t have) plays a disproportionate role. It’s not surprising, because what else can they go on? Interviewing is expensive, and there are hundreds of applicants per opening, so they want to pre-filter candidates somehow.
Once you have a few years of experience, things look a little better, especially if you climb up the prestige pole. For instance, Microsoft (or Twitter where I work today) isn’t FAANG, but you can be sure that recruiters would take applicants from there seriously, and you would have a good chance to get an interview. But the main factor is what you manage to do in your time at work. If you do well, get promoted, demonstrate clear impact (that you can articulate externally), build your professional network, that would improve your chances to both get your foot in the door, and also to pass the interviews.
There are also other things you can do, but I think they depend on luck too much. Slowly improving your portfolio is the way to go, I think.
What’s the best future web programming language to work in a big company like Google, Facebook, and Microsoft?
All of these companies assume that if you know the front-end domain, you can learn whatever technology du jour to become a front-end developer, and besides, if you don’t know anything about front-end, you can still grow into a front-end developer if that’s the path you’re interested in.
That being said, TypeScript is increasingly becoming the standard way to write client-side web code. Both Microsoft and Google are very committed to TS, while Facebook uses JavaScript with Flow. Google also uses Dart for some of its front end.
Likewise, there are a number of technologies on which the larger companies have taken diverging choices. Google is very committed to gRPC, I mean, g stands for Google; while Facebook is behind graphQL. (graph being, originally. the “social graph” of Facebook). AFAIK, Microsoft uses both.
Neither Google nor Facebook have ever really embraced node.js. This would have seemed odd a few years ago but now the web ecosystem is generally turning away from tools and web servers written in node.js. I don’t know for sure what Microsoft uses for its web servers.
Facebook is unsurprisingly very committed to React and React Native. Google though uses a number of web frameworks, including non-open sourced ones, and among others Angular and Flutter. Microsoft, AFAIK, uses React and React Native and Angular.
But all these skills are transferable. If you understand React, it’s easy to learn Angular and conversely; TypeScript and Flow have similarities, etc.
One common denominator is HTML, CSS, web APIs and web standards, which are always relevant.
Is 40 too old to apply for an SDE role in FAANG?
Not at all, I applied for a role with Google the month before my 52nd birthday.
Nobody ever asked me during the application and interview process, “Can you keep up with these young kids and with new technologies?”
Doesn’t matter if you’re 22 or 52 when you join Google — during your first year you’re going to soak up knowledge like it came from a fire hose.
If that sounds interesting to you, then by all means, apply!
How can I figure out if my interviewer is impressed in an Amazon interview? My interviewers gave reactions after every answer such as wonderful, very good, I love it. Is this usual?
Your goal, in an interview, is not to impress your interviewer, but to demonstrate that you have the necessary skill set to be hired.
In a large tech company, the threshold to be considered “impressive” is pretty high… you have people that had superlative achievements in their field (or outside of tech), and in their day to day they’re just treated like normal people. I never interviewed for Amazon, but I interviewed (and got hired) at both Facebook and Google, and both of my interviewer brackets included folks who had their own Wikipedia entry (and since then, all of my Facebook interviewers had amazing careers and most got their own Wikipedia page). So that’s the caliber of folks that your interviewers work with on a daily basis.
So your interviewer is not going to be impressed by your interview performance. That said, I’ve observed that many tech employees treat others as if they could be the next Ada Lovelace or the next Steve Jobs no matter their current achievements. This is not forced, but it’s an attitude that comes naturally because we’ve observed so many people achieve greatness. Interviewers would love nothing more than to give the highest recommendation for the candidate that they are seeing right now, it’s very fulfilling (conversely, having to reject a candidate is always a bit frustrating). So I think it’s fair that your interviewer is hoping you can become a superstar, but that hope is the same as for every other candidate and not directly linked to how well you are doing right now.
Google’s interview process leans towards making sure that an unsuitable candidate is not hired, they are ok if a few suitable candidates are missed in the process.
There is also a factor of chance involved in the process. Here is a story to prove that:
I have personally asked at least 5 engineers at Google if they would be willing to interview again assuming they would be offered 1.5 times their current compensation. Obviously they loose the job if they don’t clear the interview. I am yet to meet somebody willing to take this bargain , I wont take it either.
Btw google also offers anybody who leaves google to comeback and join at the same level without an interview if they comeback within 2 years. My guess is that they also realize the chance involved.
Not clearing an interview at google is an indicator of only one thing, that you did not clear a google interview. Don’t draw conclusions about your ability based on this.
What laptop do FAANG software developers seem to prefer? Why?
At Google there’s a selection of laptops you can choose from: a couple of Macs, a couple of Chromebooks, a couple of Linux laptops and a couple of windows laptops. Usually there’s a smaller, lighter version, for people who favor portability, and a larger version if you prefer a larger screen.
I’ve seen developers use all. I’d guess that Macs are most common (but under 50%} and Windows machines are least common.
I use a Chromebook (well, two Chromebooks). You turn it on, you log in and it looks exactly the same as your other Chromebook. This saves me carrying a laptop between work and home. If you work from another office, you don’t need to carry your laptop, you just grab one off the shelf, log in, and it looks the same as the computer you left at home.
(I tried using a Mac, I couldn’t get used to it, I didn’t know how to do anything, the keyboard shortcuts drove me crazy and so I gave it back and got a Chromebook).
Why is employee activism seen more in Google but not in other companies like Facebook and Amazon?
Google and Meta (formerly Facebook) have a long-standing culture where employees believe that they’re hot stuff and that the company has to keep them happy because the company needs them as much as they need the company. Amazon doesn’t have that, probably because they fire people pretty often, making many of the remaining employees feel disposable.
Google and Meta have different concepts of culture fit—or at least they did historically. At Google, culture fit means “don’t be a person who’s hard to work with”. At Meta, culture fit means “be a person who believes that we are doing great things here and who will be excited to work hard on those great things”. As a result, it tends to be easy for Meta to keep convincing their existing employees that the company is doing the right thing. Google, on the other hand, ends up with a significant proportion of employees who are not easily convinced, and demand change.
Though it’s been so long since I’ve actually worked in the tech industry that I’m not sure if Meta still fits the description I gave above, and there are signs that Google has been trending away from the description I gave above.
The question was:
Why is employee activism seen more in Google but not in other companies like Facebook and Amazon?
When people who have PhDs want work in FAANG, do many of them gravitate more towards Google than any of the other FAANG companies?
Just to add a small note to Dimitriy’s great answer, computer science PhDs tend to be analytical and hyperrational. Working for Google is probably the single best “pass” to choosing whatever the hell you want for the rest of your career, or at least for the next step or two. I think some CS PhDs work for Google not because it’s what they want, but because they don’t know what they want, and if you don’t know what you want and you can get a job there, it would be hard to do better than Google. Why not make $250,000 a year while figuring out your next step? The other companies in this so-called “top-tier” have issues; they are potentially great employers, but their issues make them anywhere from slightly to dramatically less attractive.
Why is it much harder to get into trading firms and hedge funds such as Jane Street and Two Sigma than FAANG/top tier companies?
The main factor why top prop trading firms and hedge funds are difficult to get into compared to tech companies is their size.
According to Wikipedia Two Sigma has about 1600 employees[1] and Jane Street has about 1900 employees .[2] Even the largest hedge fund, Bridgewater, only has 1500[3] and the third largest hedge fund, Renaissance Technology manages $130 billion with 310 employees.
Maybe these numbers on Wikipedia aren’t exact but I’d bet they’re well within the ballpark of being accurate.
Facebook has nearly 60,000 employees ,[4] Amazon has 160,000 ,[5] Apple has 154,000,[6] Netflix has around 12,000[7], and Google has 140,000[8]. Again, maybe these number aren’t precise but I don’t feel like doing more in depth research.
However, it’s pretty obvious to see that the big tech companies employ multiples of what those finance firms do and quite simply there are far more opportunities at those tech companies. More seats mean it’s going to be less competitive to be hired.
Second, those top hedge funds and prop trading firms pay well. Like really well.
And Jane Street’s 2020 graduate hires straight from college were paid a $200k annual base salary, plus a $100k sign-on bonus, plus a $100k-$150k guaranteed performance bonus. Junior bankers’ high salaries look a little paltry by comparison.[9]
So a new college grad makes $400-$450k. That’s a 22–23 year old making that. That same article found documents that said the average per employee in their London office was $1.3 million. Some make more and some make less, but that’s an eye wateringly high number when you consider all of the admin and support aren’t making close to that.
A friend’s younger brother worked at Jane Street about 10 years ago. He may still but I haven’t talked to her much since we moved. He was a rock star at Jane Street, and while I’m relying on my memory of a 10 year old conversation so I may not be totally accurate, he was in his late 20’s or early 30’s and made $4 million (and it may actually have been $8M) that year.
I know tech people are paid well but I doubt many, if any, make $400-$450k in year one and are making millions by their late 20’s is unheard of unless they founded or join a startup at the right time.
In addition, the interview processes at those firms is insanely difficult. I’ve never worked or interviewed at them but I’ve heard war stories. Just to get your foot in the door is nearly impossible then getting an offer to work there is basically impossible
My friend’s brother was half way through an absolutely top PhD program in Physics when he was recruited by them. I don’t consider myself a slouch and I’ve met a ton of highly intelligent people, but this guy was like his brain was plugged into a computer and the internet. And he was a dynamic personality.
They hire the absolute best of the best and because they’re small and privately held they don’t actually ever need to hire or grow because the public markets can’t punish their stock price because they don’t have one. If some of those top investment firms can’t find the right fit they may simply not need to make a hire right then and can wait. They’re not big banks like Goldman that need to hire X number of analysts and associates because they need to replace the people who left.
So the main reasons that it’s tougher to get into a top hedge fund or prop trading firm than big tech is because they’re much smaller, they pay more, they are even more diligent in their hiring practices, and they hire very intelligent people.
Footnotes
[2] Jane Street Capital – Wikipedia
[3] Bridgewater Associates – Wikipedia
[4] Number of Facebook Employees 2022/2023: Compensation, Tenure & Perks – Financesonline.com
[5] Amazon tops 1M U.S. employees
[7] number of nextflix employees
[9] Jane Street paid staff $1.3m as profits soared
What would happen to Google if they lost all their source code?
If that were to happen, we’ll have bigger problems to deal with. The Google monorepo exists on tens of thousands of machines. That would mean: every data center, every workstation used by Google would suddenly be out of commission – not just turned off, but so that storage isn’t even available. This is only possible in a complete doomsday scenario.
Do FAANG developers have a hard time finding another job with higher salary given the fact FAANG salaries are top of the line?
It’s generally possible to find better compensated jobs for people with experience in big tech cos. This experience is very desirable for companies in fast growth mode – not just the technical expertise but also knowledge of processes of world-class engineering organizations. Smaller but fast-growing companies can offer better packages but with an element of risk – if the company ends up failing, the employee will only get their salary.
To Conclude:
The tech industry is booming, and there are a lot of great opportunities for those with the skills and experience to land a job at one of the FAANG companies. Google, Facebook, Amazon, Apple, Netflix, and Microsoft are all leaders in the tech industry, and they offer competitive salaries and benefits. The interview process for these companies can be intense, but if you’re prepared and knowledgeable about the company’s culture and values, you’ll have a good chance of landing the job. Perks at these companies can include free food and transportation, stock options, and generous vacation time. If you’re looking for a challenging and rewarding career in the tech industry, consider applying for a job at one of the FAANGM companies.
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- IAM Roles vs IAM Policies — Understanding Access Control in AWSby Atharva Sardesai (AWS on Medium) on April 28, 2025 at 5:02 am
Cybersecurity Basics Refresher Series: Part 2Continue reading on Medium »
- Increment Number Values In DynamoDB With The ADD Operatorby Uriel Bitton (AWS on Medium) on April 28, 2025 at 4:55 am
Easily increment number counters in your DynamoDB tables with this methodContinue reading on Towards AWS »
- Top 5 Amazon Bedrock Features You Need to Know Aboutby Josh Thorne (AWS on Medium) on April 28, 2025 at 4:54 am
My favourite Bedrock features and why you should use themContinue reading on Towards AWS »
- Shocking AWS Costs: Why ALB Isn’t Always Cheaper Than API Gateway [With Real Examples]by Yatin (AWS on Medium) on April 28, 2025 at 4:54 am
Discover why ALB isn’t always cheaper than API Gateway for large payloads, and how to avoid hidden AWS costs by understanding cost…Continue reading on Towards AWS »
- Why is iWatch not working after several hours of a swimming session?by Vyshnavieminent (Apple on Medium) on April 28, 2025 at 4:09 am
Apple Watches (often casually called iWatch) are designed to be water-resistant, not completely waterproof. Prolonged exposure to water —…Continue reading on Medium »
- Saham ERAA: Berkah Berkat Iphone 16 Seriesby Hendy Harnio (Apple on Medium) on April 28, 2025 at 3:53 am
ERAA untung di akhir 2024, dengan meraup kenaikan penjualan sekitar 8.54% YoY menjadi Rp65.27 triliun dan laba bersih sebesar Rp1.03…Continue reading on Medium »
- How the Apple Watch is Keeping You Healthy and Saving Livesby Azeeza (Apple on Medium) on April 28, 2025 at 2:47 am
Apple Watch keeps you safe, tracks your health, and offers peace of mind in emergencies.Continue reading on Mac O’Clock »
- 9 Essential Changes Apple Must Bring to iPadOS 19 for True Laptop Replacementby Sareena (Apple on Medium) on April 28, 2025 at 2:47 am
Find out why your iPad still isn’t a MacBook replacement — and how that could change soon.Continue reading on Mac O’Clock »
- Michigan nuclear plant set to restart, first for U.S.by /u/Comfortable_Tutor_43 (/r/Technology) on April 28, 2025 at 1:00 am
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- Goodbye, Skype. I’ll never forget youby /u/serene_sketch (/r/Technology) on April 28, 2025 at 12:40 am
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- 4chan is back online, says it's been ‘starved of money'by /u/EliteAccess23 (/r/Technology) on April 28, 2025 at 12:39 am
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- Teens Are Using ChatGPT to Invest in the Stock Marketby /u/AlwaysBlaze_ (/r/Technology) on April 28, 2025 at 12:25 am
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- “You wouldn’t steal a car” anti-piracy campaign may have used pirated fonts | Digging into archived site points to use of questionable text styling.by /u/ControlCAD (/r/Technology) on April 28, 2025 at 12:07 am
submitted by /u/ControlCAD [link] [comments]
- How to Make Your dog with apple in mouth $APPLE earn passive income for youby dog with apple in mouth (Apple on Medium) on April 27, 2025 at 10:28 pm
Harness the Power of Staking dog with apple in mouth $APPLE to Increase Your ProfitsContinue reading on Medium »
- 09037521639by شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس (Apple on Medium) on April 27, 2025 at 10:24 pm
شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس #شماره خاله اصفهان شماره خاله کرج #شماره خاله شیراز #شماره خاله قم# شماره خاله گرگان…Continue reading on Medium »
- 09037521639by شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس (Apple on Medium) on April 27, 2025 at 10:24 pm
شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس #شماره خاله اصفهان شماره خاله کرج #شماره خاله شیراز #شماره خاله قم# شماره خاله گرگان…Continue reading on Medium »
- 09037521639by شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس (Apple on Medium) on April 27, 2025 at 10:23 pm
شماره خاله #شماره خاله تهران #شماره خاله تهرانپارس #شماره خاله اصفهان شماره خاله کرج #شماره خاله شیراز #شماره خاله قم# شماره خاله گرگان…Continue reading on Medium »
- Consumers make their voices heard as Microsoft's huge venture flatlines in popularityby /u/KJ6BWB (Microsoft) on April 27, 2025 at 9:55 pm
submitted by /u/KJ6BWB [link] [comments]
- iOS 19: The Biggest Redesign Since iOS 7?by MATHANAM.S (Apple on Medium) on April 27, 2025 at 9:41 pm
Booting up my first Apple computer, a 2009 MacBook Pro running OS X 10.5 Leopard, was like getting behind the wheel of a Porsche for the…Continue reading on Medium »
- Balcony solar took off in Germany. Why not the US? From breaker-masking to voltage mismatches, America’s grid isn’t ready for balcony solar — yet.by /u/HenryCorp (/r/Technology) on April 27, 2025 at 9:36 pm
submitted by /u/HenryCorp [link] [comments]
- Apple IsEvil?by Cornell E Davinci (Apple on Medium) on April 27, 2025 at 9:31 pm
The iphone… We all may not be religious but religion is used symbolically and used to control. Notice how apple’s logo is a bitten apple……Continue reading on Medium »
- Alumni Access To Company Store Changed?!?by /u/NorbDad (Microsoft) on April 27, 2025 at 9:18 pm
I just jumped in to take a look at Xbox prices and noticed that my current access to the company store is severely limited. I don't see anything posted on the Alumni site, any other MS Alumni seeing the same thing? submitted by /u/NorbDad [link] [comments]
- GXP Experience 365 teamby /u/IvySpring2020 (Microsoft) on April 27, 2025 at 8:32 pm
Hi everyone! Super excited about my upcoming internship as a Product Designer at Microsoft! At the moment, the only clue I have is that I'll be joining the GXP Experience 365 team (sounds fancy, right?). If anyone here knows anything about this org or has insights, stories, or tips, please share! I'd love to hear your thoughts and any juicy details! Many many thanks~ submitted by /u/IvySpring2020 [link] [comments]
- Google and Adobe appear to be abusing copyright to silence a whistleblower's videoby /u/zaiguy (/r/Technology) on April 27, 2025 at 7:17 pm
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- Trump DOJ goon threatens WikipediaThe interim US attorney for DC claims Wikipedia is ‘allowing foreign operatives’ to rewrite its website.by /u/Tr0jan___ (/r/Technology) on April 27, 2025 at 6:49 pm
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- Hegseth’s Personal Phone Use Created Vulnerabilities. The phone number used in the Signal chat could also be found in a variety of places, including on social media and a fantasy sports site.by /u/Knightbear49 (/r/Technology) on April 27, 2025 at 6:46 pm
submitted by /u/Knightbear49 [link] [comments]
- Lawyer for MyPillow Founder Filed AI-Generated Brief with ‘Nearly 30’ Bogus Citationsby /u/chrisdh79 (/r/Technology) on April 27, 2025 at 6:29 pm
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- Google Deepmind staff plan to join union against military AIby /u/MetaKnowing (/r/Technology) on April 27, 2025 at 4:04 pm
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- USB 2.0 is 25 years old today — the interface standard that changed the world | USB 2.0 was the game-changer we needed to revolutionize data transfer between devices.by /u/chrisdh79 (/r/Technology) on April 27, 2025 at 2:23 pm
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- Grid-Scale Battery Storage Is Quietly Revolutionizing the Energy Systemby /u/DukeOfGeek (/r/Technology) on April 27, 2025 at 2:05 pm
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- Meta’s ‘Digital Companions’ Will Talk Sex With Users—Even Childrenby /u/acct_removed (/r/Technology) on April 27, 2025 at 2:01 pm
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- Tech industry tried reducing AI's pervasive bias. Now Trump wants to end its 'woke AI' effortsby /u/shachen (/r/Technology) on April 27, 2025 at 1:18 pm
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- Scientists develop artificial leaf that uses sunlight to produce valuable chemicalsby /u/fchung (/r/Technology) on April 27, 2025 at 12:11 pm
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- DOGE is building a master database for immigration enforcement, sources sayby /u/Doener23 (/r/Technology) on April 27, 2025 at 12:09 pm
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- India to begin construction of gravitational wave projectby /u/eternviking (/r/Technology) on April 27, 2025 at 12:08 pm
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- UK bans gaming controller exports to Russia to hinder military useby /u/AdSpecialist6598 (/r/Technology) on April 27, 2025 at 11:55 am
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- Deepfake porn is destroying real lives in South Koreaby /u/moeka_8962 (/r/Technology) on April 27, 2025 at 8:09 am
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- YouTube says goodbye to decade-old video player UI, but users hate the new designby /u/moeka_8962 (/r/Technology) on April 27, 2025 at 3:16 am
submitted by /u/moeka_8962 [link] [comments]
- Dating apps face a reckoning as users log off: ‘There’s no actual human connection’ | In Australia, dating apps have been hit with lawsuits and new regulation, while their profits are declining worldwideby /u/Hrmbee (/r/Technology) on April 27, 2025 at 1:02 am
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- Italy, Sweden, Belgium, Portugal, Spain, Poland, Bulgaria, and Canada Urge Travelers to Use Burners Instead of Smartphones When Visiting US for an Easy Tripby /u/loki2002 (/r/Technology) on April 26, 2025 at 11:51 pm
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- Trump DOJ Threatens Wikipedia’s Nonprofit Status Over Alleged ‘Propaganda’ | The attorney claims Wikipedia is being manipulated by "foreign actors."by /u/chrisdh79 (/r/Technology) on April 26, 2025 at 10:52 pm
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- I have to laugh..by /u/HeyOldDudes (Microsoft) on April 26, 2025 at 8:42 pm
Has anyone noticed lately how useless Microsoft support techs have been in their replies . as if they did not even read the question or problem posted by the OP. The other day i was having a problem with Win10 disconnecting the USB slots upon boot into the login splash screen. so while i was searching for an answer i found someone who had a a similar problem. the OFFICIAL Microsoft representative advice was... and i quote "Right click on the task manager and.... " Now, how in heck am i suppose to "Right click" when my USB mouse and keyboard will not work?? Keep In mind these people are getting paid for their time doing this... but it's like they aren't even reading the question. Could it be all A.I. replies?? Anyway end sfc /rantnow P.S. it's still randomly doing it.. there are no driver conflicts, no power setting that would disable the USB. I find myself using Linux Mint more and more lately for internet browsing , movie streaming. submitted by /u/HeyOldDudes [link] [comments]
- Got a referral at Microsoft for a position I was previously rejected from. Will it still be considered?by /u/Rare-Sky-6212 (Microsoft) on April 26, 2025 at 8:11 pm
Hi everyone, I applied for a role at Microsoft a while ago and got rejected. Recently, someone from inside the company offered to refer me for the same position. Does anyone know if my application will still be considered in this case? Should I reapply or reach out to the recruiter? Thanks a lot! submitted by /u/Rare-Sky-6212 [link] [comments]
- Never trust Microsoft with anything importantby /u/old_guy_AnCap (Microsoft) on April 26, 2025 at 5:22 pm
Microsoft seems to have a tendency to block accounts for random reasons claiming "suspicious activity". When they do there is only automated ways to recover those accounts with no human support. My girlfriend's Hotmail account that she had for over a decade got blocked and she has spent months trying to get back into it but the system keeps refusing. There is no way to contact a real person to get this fixed and she has lost access to numerous other things attached to that account. In trying to resolve this I have found what appear to be hundreds, if not thousands of users who have experienced the same thing. As this could cost some people lots of money due to loss of access to important accounts this might be a good thing for a class action suit if an attorney wished to take it on. Users beware. submitted by /u/old_guy_AnCap [link] [comments]
- Kanye West joins streaming service Twitch — gets banned after seven minutesby /u/IAmPookieHearMeRoar (/r/Technology) on April 26, 2025 at 11:31 am
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- Employee- Perspectiveby /u/reaper___007 (Microsoft) on April 26, 2025 at 8:04 am
How important is other employee feedbacks or perspective? Does the manager read it before connects? submitted by /u/reaper___007 [link] [comments]
- Can you call phone numbers with Microsoft Teams, now that Skype is no longer available?by /u/chaplin2 (Microsoft) on April 26, 2025 at 5:22 am
I have a hard time figuring out how to do this in Teams. Skype for all its faults works and is straightforward: you get a dial pad and call. You charge it easily by buying a plan right there in the app. I got a message that Skype will be closing in May and I should transfer to using teams. Microsoft Teams is so complicated that is hard to see how to make a simple phone call. I don’t see a Call tab in the iOS app. So I thought I should first add a contact, and from there select call, but there is no contacts tab either. The new name seems to be People but that tab has only one option: import your phone contacts (to see if your phone contacts are on teams). The next step is to create a new chat and enter the phone number there, or in address bar, to create a contact, but that only sends an invitation and requires an acceptance from the other side before being added as a contact. I don’t see any way to create a new contact or a People in Teams. I don’t see any subscription option for international phone calls in the app. It is unclear these are doable at all. I searched and it seems even more complicated: There was a desktop app for my operating system that is no longer maintained. Instead, posts suggest using web app. Then there is progressive web app. Apparently, there is a separate contacts app, but I can’t find it. There are actually so many confusing web pages and apps. Even when I enter password in Teams, another Microsoft app is opened (authenticator). Do I first need to purchase a plan to see the call tabs? But there is no subscription tab. Meanwhile, there are useless tabs: Community, Sport, Volunteer, .. Whose idea was this garbage?! This thing seems to be for enterprise and companies. There is an ecosystem of apps constantly changing. For individuals, it seems to be kind of a social media app, where you have to add your friends. But I already have those in zillions of apps. Does anyone know if this is doable? If it’s not doable, why does Microsoft suggest transferring from Skype to teams? submitted by /u/chaplin2 [link] [comments]
- Tpm entry level salaryby /u/Suspicious_Text1807 (Microsoft) on April 26, 2025 at 3:36 am
Technical program manager entry level salary ? submitted by /u/Suspicious_Text1807 [link] [comments]
- Samsung Discount MSFT Employeesby /u/Ok-Nature2192 (Microsoft) on April 26, 2025 at 2:12 am
I’m trying to buy a new Samsung phone (s25+/ultra) and I want to know what the discount is for a MSFT employee. I can’t find any information online and I want to know if it’s worth waiting to buy it until I start my job. submitted by /u/Ok-Nature2192 [link] [comments]
- Do you use Microsoft Defender?by /u/MarioDF (Microsoft) on April 25, 2025 at 10:56 pm
Microsoft Defender is the app that comes with the 365 subscription. Not to be confused with Windows defender, the antivirus included within windows security. submitted by /u/MarioDF [link] [comments]
- Quality controlby /u/ChemicalRabbit4536 (Microsoft) on April 25, 2025 at 12:51 pm
In my life I have owned 6 controllers now I know what u might be thinking blimey what a temper but I can assure this is not the case, 1 was 360(4 years) when I had it , another was Xbox One( 6 years), in the last 2 year of owning series I’ve replaced 4 controllers yes I did indeed get warranty so moneys not my issue what is my issue is that I know I take good care of my controllers so why is gods name hav I had to replace 4 (technically 5 took one back same day cos it was broken before it lt even left the store), if there’s a quality assurance officer they should most definitely lose their jobs. 1 wouldn’t take a charge even tho my controllers go in a drawer so definitely no water damage, 1 was stick drift and 2 of them the RB button’s inside hook submitted by /u/ChemicalRabbit4536 [link] [comments]
- Declined an offer at Microsoftby /u/Wrong_Damage4344 (Microsoft) on April 25, 2025 at 8:53 am
I declined an offer at microsoft, due to the compensation being low i.e. I got a higher compensation elsewhere. Now, I am hunting for a job again. Note: I declined the offer after negotiating the compensation and having the call with the potential team manager. Additionally, my background check was also complete and the offer letter was signed. How many months should I wait before re applying? Seems like I keep getting those automated rejections on my applications. submitted by /u/Wrong_Damage4344 [link] [comments]
- Should I be concerned?by /u/ManagementBound (Microsoft) on April 25, 2025 at 2:50 am
Interviewed for a CSAM role, April 4th, all interviews went extremely well - but haven’t heard back, currently has been officially two weeks - referred internally, and the hiring manager told my referral that I did do amazing during my interviews - the problem is I followed up with the recruiter who hasn’t responded twice - wait is killing me man- Anyone else is in the same boat or has interviewed for this role? Let me know! submitted by /u/ManagementBound [link] [comments]
- Data Center Technician Manager interviewby /u/Kratus7 (Microsoft) on April 23, 2025 at 8:12 pm
Hi all! I currently work as a Technical Account Manager / Cloud Architect at AWS with Data Center experience, and I just noticed an opening for a Data Center Technician Manager role. My questions are: Is this a good role? I can't understand if this is pure manager role or a mix. How doable is to move internally later on to, for example, a Solutions Architect role if I see that would be a better fit? I remember some years ago having a conversation with a recruiter for a DC Technician role at Microsoft and the salary was not very high comparing to AWS, no stocks whatsoever, does the same applies to this manager role? My biggest concern is if I'm taking a step back in my career by moving to this role. Edit: Also, what is the career progression for this role? Edit 2: My main motivator is because I want to move for a management role. submitted by /u/Kratus7 [link] [comments]
- Dear Microsoft . . .by /u/mind-meld224 (Microsoft) on April 23, 2025 at 4:47 pm
You give us features we didn't know we needed, that will save us life's most valuable resource -- time -- but you then you break basic features, and we spend scads of life's most valuable resource trying to fix what you've broken. Stop it! Addendum: I'm frustrated today with the New Outlook, changes to Teams, Copilot Studay, Power Apps, and Windows 11... and it's only noon. Addendum 2: It wouldn't be so bad if this happened in just one product, but when it happens in all of the user products in a constant deluge of changes, it's impossible to keep up. Not to mention the changes in Azure et al every day. submitted by /u/mind-meld224 [link] [comments]
- Recommended for another positionby /u/Impossible_Set_1239 (Microsoft) on April 23, 2025 at 4:35 pm
As the title says I went through the process for interviewing for a DCT, after the final interviews I asked for a follow up and the recruiter reached out and let me know that they went with another candidate for that position but the interview team said that I did an amazing job and they recommended me for another DCT position that was just posted yesterday as they thought I would be a better fit for that specific team. The recruiter said they want to interview quickly for this and as the team recommended me he will be reaching out to me shortly for a time to interview again. Has this happened to anyone else did you end up getting the position they recommended? submitted by /u/Impossible_Set_1239 [link] [comments]
- Sr Product Designer Salary @ Microsoft India?by /u/PianistOk509 (Microsoft) on April 23, 2025 at 4:34 pm
Hi, I'm in the final stage of interviewing for the role of a Senior Product Designer, based in India. The job description mentions having 8/10+ years of experience. What should be the expected salary range for this role during negotiation? Any inputs appreciated! submitted by /u/PianistOk509 [link] [comments]
- If you ignore this Windows error, maybe it'll go away — or so says Microsoftby /u/Huge-Platypus9075 (Microsoft) on April 23, 2025 at 1:46 pm
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- Lego Clippyby /u/Klocek1990 (Microsoft) on April 23, 2025 at 10:32 am
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- Microsoft targets ‘low performers’ in a sensational new memoby /u/76willcommenceagain (Microsoft) on April 22, 2025 at 4:49 pm
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- Microsoft website is so slow which makes me want to avoid itby /u/Special-Winner-8591 (Microsoft) on April 22, 2025 at 4:13 pm
For many years, I dread going to microsoft.com to do anything - everything is so slow. Whether it is accessing account, Xbox or anything else - things are very slow. Will one day in future it will be responsive as many other websites? submitted by /u/Special-Winner-8591 [link] [comments]
- How safe are manager signals with no comment?by /u/SnooRecipes1809 (Microsoft) on April 22, 2025 at 2:20 pm
I am an employee whose manager has more inhibited productivity rather than encouraged it, with the added bonus of an obvious dislike for me no matter what work I do to counteract it. I want to be honest about how this management style doesn’t work for me on our signals, but employees online do caution that even outlier scores can lead to an investigation and inflame an already poor relationship. Is this true? They advised not to write comments or specific examples, as this is a fingerprint of which employee talked shit. But I cannot bring myself to give them good scores and cuck myself, as this would imply the way they treated me was good management. I want to be objective, but I want to know if I’m shooting my own foot doing this. (And I’m not doing this to talk shit, I do have coherent explanations for my opinion I could defend. But I want to know if or how a manager retaliates.) submitted by /u/SnooRecipes1809 [link] [comments]
- Microsoft’s “1‑bit” AI model runs on a CPU only, while matching larger systemsby /u/BippityBoppityWhoops (Microsoft) on April 21, 2025 at 6:00 pm
submitted by /u/BippityBoppityWhoops [link] [comments]
- Bill Gates Says His Kids And Grandkids Will Live In A 'Very Changed World' As AI Puts An End To Shortage Of Teachers And Doctorsby /u/ControlCAD (Microsoft) on April 21, 2025 at 9:48 am
submitted by /u/ControlCAD [link] [comments]
- Microsoft: Official Support Threadby /u/MSModerator (Microsoft) on March 3, 2025 at 12:25 pm
This thread was created in order to facilitate easy-to-access support for our Reddit subscribers. We will make a best effort to support you. We may also need to redirect you to a specialized team when it would best serve your particular situation. Also, we may need to collect certain personal information from you when you use this service, but don't worry -- you won't provide it on Reddit. Instead, we will private message you as we take data privacy seriously. Here are some of the types of issues we can help with in this thread: Microsoft Support: Needing assistance with specific Microsoft products (Windows, Office, etc..) Microsoft Accounts: Lockouts, suspensions, inability to gain access Microsoft Devices: Issues with your Microsoft device (Surface, Xbox) Microsoft Retail: Needing to find support on a product or purchase, assistance with activating online product keys or media, assistance with issues raised from liaising with colleagues in the Microsoft Store. This list is not all inclusive, so if you're unsure, simply ask. When requesting help from us, you may be requested to provide Microsoft with the following information (you'll be asked via private message from the MSModerator account): Your full name (First, Last) Your interactions with support thus far, including any existing service request numbers An email address that we can use to contact you Thank you for being a valued Microsoft customer. For previous Support Threads, please use the Support Thread flair. submitted by /u/MSModerator [link] [comments]
How to prepare for FAANG – MAANGM jobs interviews
FAANG – MAANGM Job interviews Q&A
Tips to succeed at FAANGM companies
Recipes to succeed in corporate, how to navigate the job world.
I’m going to read between the lines and assume that you are working at a grade below senior at a company which is not a FAANG. I’m also assuming that you feel that you are ready and that you’ve already done the obvious, read the books, practiced questions etc.
Your senior eng interview has 3 facets, coding, system design and behavioral.
Your levers to do better at each are:
- To get better at coding interviews, interview more candidates. Seeing what others do well and less well is very helpful. This really applies to all sorts of interviews but IMO is most helpful for coding interviews.
- To get better at system design interviews, read more design docs at your existing company, attend more design reviews, and force yourself to participate. Comment, ask questions. It doesn’t matter if you’re off the mark. See what doesn’t make sense to you and challenge it.
- To get better at behavioral interviews, read your perf packets and the feedback from your coworkers. Read the docs that you wrote on your career plans (If you don’t have any, ask yourself why and start one). Reflect, regularly, on what has been hardest in your career, what you have done very well, where you struggled, what you would do differently.
I’d like to answer first in general — about attrition rates in the tech sector — and then about Amazon specifically.
Industry-Wide Retention
Retention in the US high-tech industry is very challenging. I believe there are two main reasons for that.
First, there is an acute shortage of qualified workers, which means companies are desperate to get employees anywhere they can, including — sometimes mainly — by poaching them from other companies. This is why so many companies moved into the Seattle East Side in the ’90s or South Lake Union in the last five years, for example: to poach from Microsoft and Amazon, respectively.
I remember the crazy late-90’s in the Israel high-tech industry. People would come in, work for 6–12 months, then jump ship for a fancier title and a bump in pay. It was insane; it was disgusting (I mean that literally: I would sometimes feel physically sick thinking about how stupid it all was.)
The second reason — which I’m not as certain about — is that the high-tech industry is so incredibly dynamic. Things change constantly: new companies spring up and grow like crazy (Uber anyone?); “old” companies that were considered the cream of the crop a couple of years ago are suddenly untouchable (Yahoo!). New technologies explode onto the scene and old ones stagnate.
Not only does that create a lot of churn as companies keep growing and shrinking; it also creates incredible pressure on tech workers to stay on top of their game. We’re always looking for the next big technology, the next big field, then next big product… The sad part is that a lot of it is just hype, but the psychological pressure is real enough, and it makes people move around always looking for the next great opportunity.
Amazon
The reason I want to talk about Amazon — which generally suffers from the same problems I’ve described above — is that there’s a perception in the public that Amazon is somehow worse than the rest of the industry; that it has awful attrition, because it’s a terrible place to work. I’ve tackled that in a couple of other answers (e.g. this one and this one), but it’s a very persistent myth.
Much of the fault is in reports like this one from PayScale, which then get regurgitated in hundreds of stories like this one (from BuzzFeed). The basic story seems very simple: the average tenure of an Amazon employee is about a year, which is — undoubtedly — really low, even in tech-industry terms.
That’s a great example of (supposedly) Benjamin Disraeli’s famous quote, “lies, damned lies and statistics”. There are at least two reasons why this number is completely meaningless:
- Short tenure does not mean high attrition: in the last 6–7 years the number of employees at Amazon has grown exponentially, and I mean this literally:
- Source: Amazon: number of employees 2017 | Statista
This means that at any time, pretty much, about 20–40% of all Amazon employees have joined less than a year ago. It’s no really surprising that they have a short tenure, is it?
Measuring retention is not trivial, but this methodology is just plain dumb (or maybe intentionally misleading). - Amazon is not (only) a tech company: sure, if you compare Amazon to Google and Facebook it comes out bad. But unlike those companies, the majority of Amazon employees are not tech workers. They’re warehouse workers, drivers, customer-service people, etc. Many of them are temp workers, and many others are not considering the job as a career.
There is a good discussion to be had about how Amazon treats these workers and whether it can do better, but it makes no sense to compare it with Microsoft or Apple; Walmart and Target would be much better comparisons.
What are some ways we can use machine learning and artificial intelligence for algorithmic trading in the stock market?
How do we know that the Top 3 Voice Recognition Devices like Siri Alexa and Ok Google are not spying on us?
Machine Learning Engineer Interview Questions and Answers
Top 60 AWS Solution Architect Associate Exam TipsA Twitter List by enoumen
Jobs, Career, Salary, Total Compensation, Interview Tips at FAANGM: Facebook, Apple, Amazon, Netflix, Google, Microsoft


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Jobs Career Salary Total Compensation Interview Tips at FAANGM: Facebook Apple, Amazon Netflix Google Microsoft
This blog is about Clever Questions, Answers, Resources, Links, Discussions, Tips about jobs and careers at FAANGM companies: Facebook, Apple, Amazon, AWS, Netflix, Google, Microsoft, Linkedin.
How to prepare for FAANGM jobs interviews
You must be able to write code. It is as simple as that. Prepare for the interview by practicing coding exercises in different categories. You’ll solve one or more coding problems focused on CS fundamentals like algorithms, data structures, recursions, and binary trees.
Coding Interview Tips
These tips from FAANGM engineers can help you do your best.
Make sure you understand the question. Read it back to your interviewer. Be sure to ask any clarifying questions.
An interview is a two-way conversation; feel free to be the one to ask questions, too.
Don’t rush. Take some time to consider your approach. For example, on a tree question, you’ll need to choose between an iterative or a recursive approach. It’s OK to first use a working, unoptimized solution that you can iterate on later.
Talk through your thinking and processes out loud. This can feel unnatural; be sure to practice it before the interview.
Test your code by running through your problem with a few test and edge cases. Again, talk through your logic out loud when you walk through your test cases.
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Think of how your solution could be better, and try to improve it. When you’ve finished, your interviewer will ask you to analyze the complexity of the code in Big O notation.
Walk through your code line by line and assign a complexity to each line.
Remember how to analyze how “good” your solution is: how long does it take for your solution to complete? Watch this video to get familiar with Big O Notation.
https://www.youtube.com/watch?v=v4cd1O4zkGw
How to Approach Problems During Your Interview
Before you code
• Ask clarifying questions. Talk through the problem and ask follow-up questions to make sure you understand the exact problem you’re trying to solve before you jump into building
the solution.
• Let the interviewer know if you’ve seen the problem previously. That will help us understand your context.
• Present multiple potential solutions, if possible. Talk through which solution you’re choosing and why.
While you code
• Don’t forget to talk! While your tech screen will focus heavily on coding, the engineer you’re interviewing with will also be evaluating your thought process. Explaining your decisions and actions as you go will help the interviewer understand your choices.
• Be flexible. Some problems have elegant solutions, and some must be brute forced.
If you get stuck, just describe your best approach and ask the interviewer if you should go that route. It’s much better to have non-optimal but working code than just an idea with nothing written down.
• Iterate rather than immediately trying to jump to the clever solution. If you can’t explain your concept clearly in five minutes, it’s probably too complex.
• Consider (and be prepared to talk about):
• Different algorithms and algorithmic techniques, such as sorting, divide-and-conquer, recursion, etc.
• Data structures, particularly those used most often (array, stack/queue, hashset/hashmap/hashtable/dictionary, tree/binary tree, heap, graph, etc.)
• O memory constraints on the complexity of the algorithm you’re writing and its running time as expressed by big-O notation.
• Generally, avoid solutions with lots of edge cases or huge if/else if/else blocks, in most cases. Deciding between iteration and recursion can be an important step
- After you code
• Expect questions. The interviewer may tweak the problem a bit to test your knowledge and see if you can come up with another answer and/or further optimize your solution.
• Take the interviewer’s hints to improve your code. If the interviewer makes a suggestion or asks a question, listen fully so you can incorporate any hints they may provide.
• Ask yourself if you would approve your solution as part of your codebase. Explain your answer to your interviewer. Make sure your solution is correct and efficient, that you’ve taken into account edge cases, and that it clearly reflects the ideas you’re trying to express in your code.
FAANGM Screening/Phone Interview Examples:
Arrays
Reverse to Make Equal: Given two arrays A and B of length N, determine if there is a way to make A equal to B by reversing any subarrays from array B any number of times. Solution here
Contiguous Subarrays: You are given an array arr of N integers. For each index i, you are required to determine the number of contiguous subarrays that fulfills the following conditions:
The value at index i must be the maximum element in the contiguous subarrays, and
These contiguous subarrays must either start from or end on index i. Solution here
Add 2 long integer (Example: “1001202033933333093737373737” + “934019393939122727099000000”) Solution here
# Python3 program to find sum of
# two large numbers. # Function for finding sum of
# larger numbers
def findSum(str1, str2):
# Before proceeding further,
# make sure length of str2 is larger.
if (len(str1) > len(str2)):
t = str1;
str1 = str2;
str2 = t; # Take an empty string for
# storing result
str = ""; # Calculate length of both string
n1 = len(str1);
n2 = len(str2); # Reverse both of strings
str1 = str1[::-1];
str2 = str2[::-1]; carry = 0;
for i in range(n1):
# Do school mathematics, compute
# sum of current digits and carry
sum = ((ord(str1[i]) - 48) +
((ord(str2[i]) - 48) + carry));
str += chr(sum % 10 + 48); # Calculate carry for next step
carry = int(sum / 10); # Add remaining digits of larger number
for i in range(n1, n2):
sum = ((ord(str2[i]) - 48) + carry);
str += chr(sum % 10 + 48);
carry = (int)(sum / 10); # Add remaining carry
if (carry):
str += chr(carry + 48); # reverse resultant string
str = str[::-1]; return str; # Driver code
str1 = "12";
str2 = "198111";
print(findSum(str1, str2)); # This code is contributed by mits
Optimized version below
# python 3 program to find sum of two large numbers. # Function for finding sum of larger numbers
def findSum(str1, str2): # Before proceeding further, make sure length
# of str2 is larger.
if len(str1)> len(str2):
temp = str1
str1 = str2
str2 = temp # Take an empty string for storing result
str3 = "" # Calculate length of both string
n1 = len(str1)
n2 = len(str2)
diff = n2 - n1 # Initially take carry zero
carry = 0 # Traverse from end of both strings
for i in range(n1-1,-1,-1):
# Do school mathematics, compute sum of
# current digits and carry
sum = ((ord(str1[i])-ord('0')) +
int((ord(str2[i+diff])-ord('0'))) + carry)
str3 = str3+str(sum%10 )
carry = sum//10 # Add remaining digits of str2[]
for i in range(n2-n1-1,-1,-1):
sum = ((ord(str2[i])-ord('0'))+carry)
str3 = str3+str(sum%10 )
carry = sum//10 # Add remaining carry
if (carry):
str3+str(carry+'0') # reverse resultant string
str3 = str3[::-1] return str3 # Driver code
if __name__ == "__main__":
str1 = "12"
str2 = "198111"
print(findSum(str1, str2)) # This code is contributed by ChitraNayal
Strings
Rotational Cipher: One simple way to encrypt a string is to “rotate” every alphanumeric character by a certain amount.
Rotating a character means replacing it with another character that is a certain number of steps away in normal alphabetic or numerical order. For example, if the string “Zebra-493?” is rotated 3 places, the resulting string is “Cheud-726?”. Every alphabetic character is replaced with the character 3 letters higher (wrapping around from Z to A), and every numeric character replaced with the character 3 digits higher (wrapping around from 9 to 0). Note that the non-alphanumeric characters remain unchanged. Given a string and a rotation factor, return an encrypted string. Solution here
Matching Pairs: Given two strings s and t of length N, find the maximum number of possible matching pairs in strings s and t after swapping exactly two characters within s. A swap is switching s[i] and s[j], where s[i] and s[j] denotes the character that is present at the ith and jth index of s, respectively. The matching pairs of the two strings are defined as the number of indices for which s[i] and t[i] are equal. Note: This means you must swap two characters at different indices. Solution here
Minimum Length Substrings: You are given two strings s and t. You can select any substring of string s and rearrange the characters of the selected substring.
Determine the minimum length of the substring of s such that string t is a substring of the selected substring. Solution here
Recursion
Encrypted Words: You’ve devised a simple encryption method for alphabetic strings that shuffles the characters in such a way that the resulting string is hard to quickly read, but is easy to convert back into the original string.
When you encrypt a string S, you start with an initially-empty resulting string R and append characters to it as follows:
Append the middle character of S (if S has even length, then we define the middle character as the left-most of the two central characters)
Append the encrypted version of the substring of S that’s to the left of the middle character (if non-empty)
Append the encrypted version of the substring of S that’s to the right of the middle character (if non-empty)
For example, to encrypt the string “abc”, we first take “b”, and then append the encrypted version of “a” (which is just “a”) and the encrypted version of “c” (which is just “c”) to get “bac”.
If we encrypt “abcxcba” we’ll get “xbacbca”. That is, we take “x” and then append the encrypted version “abc” and then append the encrypted version of “cba”.
Greedy Algorithms
Slow Sums: Suppose we have a list of N numbers, and repeat the following operation until we’re left with only a single number: Choose any two numbers and replace them with their sum. Moreover, we associate a penalty with each operation equal to the value of the new number, and call the penalty for the entire list as the sum of the penalties of each operation.For example, given the list [1, 2, 3, 4, 5], we could choose 2 and 3 for the first operation, which would transform the list into [1, 5, 4, 5] and incur a penalty of 5. The goal in this problem is to find the worst possible penalty for a given input.
Linked Lists
Reverse Operations: You are given a singly-linked list that contains N integers. A subpart of the list is a contiguous set of even elements, bordered either by either end of the list or an odd element. For example, if the list is [1, 2, 8, 9, 12, 16], the subparts of the list are [2, 8] and [12, 16].Then, for each subpart, the order of the elements is reversed. In the example, this would result in the new list, [1, 8, 2, 9, 16, 12].The goal of this question is: given a resulting list, determine the original order of the elements. Solution Here.
Hash Tables
Pair Sums: Given a list of n integers arr[0..(n-1)], determine the number of different pairs of elements within it which sum to k. If an integer appears in the list multiple times, each copy is considered to be different; that is, two pairs are considered different if one pair includes at least one array index which the other doesn’t, even if they include the same values. Solution here.
Note: These exercises assume you have knowledge in coding but not necessarily knowledge of binary trees, sorting algorithms, or related concepts.
• Topic 1 | Arrays & Strings
• A Very Big Sum
• Designer PDF Viewer
• Left Rotation
A very big Sum in Java
import java.io.*;
import java.util.*;
import java.text.*;
import java.math.*;
import java.util.regex.*;
public class Solution {
/**
* Your solution in here. Just need to add the number in a variable type long so you
* don't face overflow.
*/
static long aVeryBigSum(int n, long[] ar) {
long sum = 0;
for (int i = 0; i < n; i++) {
sum += ar[i];
}
return sum;
}
/**
* HackerRank provides this code.
*/
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
int n = in.nextInt();
long[] ar = new long[n];
for(int ar_i = 0; ar_i < n; ar_i++){
ar[ar_i] = in.nextLong();
}
long result = aVeryBigSum(n, ar);
System.out.println(result);
}
}
Left Rotation in Java
import java.io.*;
import java.util.*;
import java.text.*;
import java.math.*;
import java.util.regex.*;
public class Solution {
static int[] leftRotation(int[] a, int d) {
// They say in requirements that these inputs should not be considered.
// However, noting that we should prevent against those.
if (d == 0 || a.length == 0) {
return a;
}
int rotation = d % a.length;
if (rotation == 0) return a;
// Please note that there is an implementation, circular arrays that could be considered here,
// but that one has an edge case (Test#1)
// As, we don't need to optimize for memory, let's keep it simple.
int [] b = new int[a.length];
for (int i = 0; i < a.length; i++) {
b[i] = a[indexHelper(i + rotation, a.length)];
}
return b;
}
/**
* Takes care of the case where the rotation index. You have to take into account
* how it is rotated towards the left. To compute index of B, we rotate towards the right.
* If we were to do a[i] in the loop, then these method would need to be slightly chnaged
* to compute index of b.
*/
private static int indexHelper(int index, int length) {
if (index >= length) {
return index - length;
} else {
return index;
}
}
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
int n = in.nextInt();
int d = in.nextInt();
int[] a = new int[n];
for(int a_i = 0; a_i < n; a_i++){
a[a_i] = in.nextInt();
}
int[] result = leftRotation(a, d);
for (int i = 0; i < result.length; i++) {
System.out.print(result[i] + (i != result.length - 1 ? " " : ""));
}
System.out.println("");
in.close();
}
}
Sparse Array in Java
import java.io.*;
import java.util.*;
public class Solution {
public static void main(String[] args) {
Scanner scanner = new Scanner(System.in);
final int totalN = Integer.parseInt(scanner.nextLine());
final Map<String, Integer> mapWords = buildCollectionOfStrings(scanner, totalN);
final int numberQueries = Integer.parseInt(scanner.nextLine());
printOcurrenceOfQueries(scanner, numberQueries, mapWords);
}
/**
* This method construcs a map with the collection of Strings and occurrence.
*/
private static Map<String, Integer> buildCollectionOfStrings(Scanner scanner, int n) {
final Map<String, Integer> map = new HashMap<String, Integer>();
for (int i = 0; i < n; i++) {
final String line = scanner.nextLine();
if (map.containsKey(line)) {
map.put(line, map.get(line) + 1);
} else {
map.put(line, 1);
}
}
return map;
}
private static void printOcurrenceOfQueries(Scanner scanner, int numberQueries, Map<String, Integer> mapWords) {
for (int i = 0; i < numberQueries; i++) {
// for each query, we look for how many times it occurs and we print on screen the value.
final String line = scanner.nextLine();
if (mapWords.containsKey(line)) {
System.out.println(mapWords.get(line));
} else {
System.out.println(0);
}
}
}
}
• Topic 2 | Lists
Insert a Node at a Position Given in a List
Cycle Detection
Topic 3 | Stacks & Queues
Balanced Brackets
Queue Using Two Stacks
Topic 4 | Hash & Maps
Ice Cream Parlor
Colorful Number
Topic 5 | Sorting Algorithms
Insertion Sort part 2
Quicksort part 2
• Topic 6 | Trees
Binary Tree Insertion
Height of a Binary Tree
Qheap1
Topic 7 | Graphs (BFS & DFS)
Breath First Search
Snakes and Ladders
Solution here
• Topic 8 | Recursion
Fibonacci Numbers
Solutions: All solutions are available in this public repository:
FAANGM Interview Tips
What they usually look for:
The interviewer will be thinking about how your skills and experience might help their teams.
Help them understand the value you could bring by focusing on these traits and abilities.
• Communication: Are you asking for requirements and clarity when necessary, or are you
just diving into the code? Your initial tech screen should be a conversation, so don’t forget
to ask questions.
• Problem solving: They are evaluating how you comprehend and explain complex ideas. Are you providing the reasoning behind a particular solution? Developing and comparing multiple solutions? Using appropriate data structures? Speaking about space and time complexity? Optimizing your solution?
• Coding. Can you convert solutions to executable code? Is the code organized and does it
capture the right logical structure?
• Verification. Are you considering a reasonable number of test cases or coming up with a
good argument for why your code is correct? If your solution has bugs, are you able to walk
through your own logic to find them and explain what the code is doing?
– Please review Amazon Leadership Principles, to help you understand Amazon’s culture and assess if it’s the right environment for you (For Amazon)
– Review the STAR interview technique (All)
FAANGM Compensation
Legend – Base / Stocks (Total over 4 years) / Sign On
– 105/180/22.5 (2016, L3)
– 105/280/58 (2016, L3)
– 105/330/22.5 (2016, L3)
– 110/180/25 (2016, L3)
– 110/270/30 (2016, L3)
– 110/250/20 (2016, L3)
– 110/160/70 (2016, L3)
– 112/180/50 (2016, L3)
– 115/180/50 (2016, L3)
– 140/430/50 (2016, L3)
– 110/90/0 (2017, L3)
– 145/415/100 (2017, L3)
– 120/220/25 (2018, L3)
– 145/270/30 (2017, L4)
– 150/400/30 (2018, L4)
– 155/315/50 (2017, L4)
– 155/650/50 (2017, L4)
– 170/350/50 (2017, L4)
– 170/400/75 (2017, L4)
*Google’s target annual bonus is 15%. Vesting is monthly and has no cliff.
– 105/120/120 (2016, E3)
– 105/150/75 (2016, E3)
– 105/100/50 (2016, E3)
– 105/240/105 (2016, E3)
– 107/150/75 (2016, E3)
– 110/150/75 (2016, E3)
– 110/235/75 (2016, E3)
– 115/150/75 (2016, E3)
– 110/150/110 (2017, E3)
– 115/160/100 (2017, E3)
– 160/300/70 (2017, E4)
– 145/220/0 (2017, E4)
– 160/300/100 (2017, E4)
– 160/300/100 (2017, E4)
– 150/250/25 (2017, E4)
– 150/250/60 (2017, E4)
– 175/250/0 (2017, E5)
– 160/250/100 (2018, E4)
– 170/450/65 (2015, E5)
– 180/600/50 (2016, E5)
– 180/625/50 (2016, E5)
– 170/500/100 (2017, E5)
– 175/450/50 (2017, E5)
– 175/480/75 (2017, E5)
– 190/600/70 (2017, E5)
– 185/600/100 (2017, E5)
– 185/1000/100 (2017, E5)
– 190/500/120 (2017, E5)
– 200/550/50 (2018, E5)
– 210/1000/100 (2017, E6)
*Facebook’s target annual bonus is 10% for E3 and E4. 15% for E5 and 20% for E6. Vesting is quarterly and has no cliff.
LinkedIn (Microsoft)
– 125/150/25 (2016, SE)
– 120/150/10 (2016, SE)
– 170/300/30 (2016, Senior SE)
– 140/250/50 (2017, Senior SE)
Apple
– 110/60/40 (2016, ICT2)
– 140/99/8 (2016, ICT3)
– 140/100/20 (2016, ICT3)
– 155/130/65 (2017, ICT3)
– 120/100/21 (2017, ICT3)
– 135/105/20 (2017, ICT3)
– 160/105/30 (2017, ICT4)
Amazon
– 95/52/47 (2016, SDE I)
– 95/53/47 (2016, SDE I)
– 95/53/47 (2016, SDE I)
– 100/70/59 (2016, SDE I)
– 103/65/52 (2016, SDE I)
– 103/65/40 (2016, SDE I)
– 103/65/52 (2016, SDE I)
– 110/200/50 (2016, SDE I)
– 135/70/45 (2016, SDE I)
– 106/60/65 (2017, SDE I)
– 130/88/62 (2016, SDE II)
– 127/94/55 (2017, SDE II)
– 152/115/72 (2017, SDE II)
– 160/160/125 (2017, SDE II)
– 178/175/100 (2017, SDE II)
– 145/120/100 (2018, SDE II)
– 160/320/185 (2018, SDE III)
*Amazon stocks have a 5/15/40/40 vesting schedule and sign on is split almost evenly over the first two years*
Microsoft
– 100/25/25 (2016, SDE)
– 106/120/20 (2016, SDE)
– 106/60/20 (2016, SDE)
– 106/60/10 (2016, SDE)
– 106/60/15 (2016, SDE)
– 106/60/15 (2016, SDE)
– 106/120/15 (2016, SDE)
– 107/90/35 (2016, SDE)
– 107/120/30 (2017, SDE)
– 110/50/20 (2016, SDE)
– 119/25/15 (2017, SDE)
– 130/200/20 (2016, SWE1)
– 120/150/18.5 (2016, SWE1)
– 145/125/15 (2017, SWE1)
– 160/600/50 (2017, SWE II)
Uber
– 110/180/0 (2016, L3)
– 110/150/0 (2016, L3)
– 140/590/0 (2017, L4)
Lyft
– 135/260/60 (2017, L3)
– 170/720/20 (2017, L4)
– 152/327/0 (2017, L4)
– 175/480/0 (2017, L4)
Dropbox
– 167/464/10 (2017, IC2)
– 160/250/10 (2017, IC2)
– 160/300/50 (2017, IC2)
Top-paying Cloud certifications for FAANGM:
- Google Certified Professional Cloud Architect — $175,761/year
- AWS Certified Solutions Architect – Associate — $149,446/year
- Azure/Microsoft Cloud Solution Architect – $141,748/yr
- Google Cloud Associate Engineer – $145,769/yr
- AWS Certified Cloud Practitioner — $131,465/year
- Microsoft Certified: Azure Fundamentals — $126,653/year
- Microsoft Certified: Azure Administrator Associate — $125,993/year
According to the 2020 Global Knowledge report, the top-paying cloud certifications for the year are (drumroll, please):
FAANGM FAQ (Frequently Asked Questions and Answers)
Does any of the FANG offer internship to self taught programmers?
I am not a lawyer, but I believe there is some sort of legal restrictions on what an internship can be (in California, at least). In my previous company, we had discussed cases on whether or not someone who was out of school can be an intern, and we got an unequivocal verdict that you have to be in school, or about to start school (usually college or graduate school, but high school can work too), in order to be considered for an internship.
I suspect the reason for this is to protect a potential intern from exploitation by companies who would offer temporary jobs to people while labeling them as learning opportunities in order to pay less.
Personally, I feel for people like you, in an ideal world you should be allowed to have the same opportunities as the formally schooled people, and occasionally there are. For example, some companies offer residency programs which are a bit similar to internships. In many cases, though, these are designed to help underrepresented groups. Some examples include:
Facebook’s The Artificial Intelligence (AI) Residency Program
Google’s Eng Residency
Microsoft AI Residency Program
How can I get an intership as a product manager at faang or any other tech company?
What questions to expect in cloud support engineer deployment roles at AWS?
Recipes to succeed in corporate, how to navigate the job world.
Ever wonder how the FAANGM big tech make their money?
This is a common bug in the thinking of people, doing the wrong thing harder in the hope that it works this time. Asking tough questions is like hitting a key harder when the broken search function in LinkedIn fails. No matter how hard you hit the key, it won’t work.
Given the low quality of the LinkedIn platform from a technical perspective it seems hard to imagine that they hire the best or even the mediocre. But it may be that because their interviews are too tough to hire good programmers.
Just because so few people can get a question right, does not mean it is a good question, merely that it is tough. I am also a professional software developer and know a bunch of algorithms, but also am wholly ignorant of many others. Thus it is easy to ask me (or anyone else) questions they can’t answer. I am (for instance) an expert on sort/merging, and partial text matching, really useful for big data, wholly useless for UX.
So if you ask about an obscure algorithm or brain teaser that is too hard you don’t measure their ability, but their luck in happening to know that algo or having seen the answer to a puzzle. More importantly how likely are they to need it ?
This is a tricky problem for interviewers, if you know that a certain class of algorithms are necessary for a job, then if you’re a competent s/w dev manager then odds are that you’ve already put them in and they just have to integrate or debug them. Ah, so I’ve now given away one of my interview techniques. We both know that debugging is more of our development effort than writing code. Quicksort (for instance) is conceptually quite easy being taught to 16 year old Brits or undergraduate Americans, but it turns out that some implementations can go quadratic in space and/or time complexity and that comparison of floating point numbers is a sometimes thing and of course some idiot may have put = where he should have put == or >= when > is appropriate.
Resolving that is a better test, not complete of course, but better.
For instance I know more about integrating C++ with Excel than 99.9% of programmers. I can ask you why there are a whole bunch of INT 3’s laying around a disassembly of Excel, yes I have disassembled Excel, and yes my team was at one point asked to debug the damned thing for Microsoft. I can ask about LSTRs, and why SafeArrays are in fact really dangerous. I can even ask you how to template them. That’s not easy, trust me on this.
Are you impressed by my knowledge of this ?
I sincerely hope not.
Do you think it would help me build a competent search engine, something that the coders at LinkedIn are simply unable to do ?
No.
I also know a whole bunch of numerical methods for solving PDEs. Do you know what a PDE even is ? This can be really hard as well. Do you care if you can’t do this ? Again not relevant to fixing the formless hell of LI code. fire up the developer mode of your browser and see what it thinks of Linkedin’s HTML, I’ve never seen a debugger actually vomit in my face before.
A good interview is a measure not just of ability but of the precise set of skills you bring to the team. A good interviewer is not looking for the best, but the best fit.
Sadly some interviewers see it as an ego thing that they can ask hard questions. So can I, but it’s not my job. My job is identfying those that can deliver most, hard questions that you can’t answer are far less illuminating that questions you struggle with because I get to see the quality of your thinking in terms of complexity, insight, working with incomplete and misleading information and determination not to give up because it is going badly.
Do you as a candidate ask questions well ? If I say something wrong, do you a) notice, b) have the soft skills to put it to me politely, c) have the courage to do so ?
Courage is an under-rated attribute that superior programmers have and failed projects have too little of.
Yes, some people have too much courage, which is a deeper point, where for many things there is an optimum amount and the right mix for your team at this time. I once had to make real time un-reversible changes to a really important database whilst something very very bad happened on TV news screens above my head. Too much or too little bravery would have had consequences. Most coding ain’t that dramatic, but the superior programmer has judgement, when to try the cool new language/framework feature in production code, when to optimise for speed, or for space and when for never ever crashes even when memory is corrupted by external effects. When does portability matter or not ? Some code will only be used once and we both know some of it will literally never be executed in live, do we obsess about it’s quality in terms of performance and maintainability .
The right answer is it depends, and that is a lot more important to hiring the best than curious problems in number theory or O(N Log(N)) for very specific code paths that rarely execute.
Also programming is a marathon, not a sprint, or perhaps more like a long distance obstacle course, stretches of plodding along with occasional walls. Writing a better search engine than LinkedIn “programmers” manage is a wall, I know this because my (then) 15 year old son took several weeks, at 15, he was only 2 or 3 times better than the best at LinkedIn, but he’s 18 now and as a professional grade programmer, him working for LinkedIn would be like putting the head of the Vulcan Science Academy in among a room of Gwyneth Paltrow clones.
And that ultimately may be the problem.
Good people have more options and if you have a bad recruitment process then they often will reject your offer. We spend more of our lives with the people we work with than sleep with and if at interview management is seen as pompous or arrogant then they won’t get the best people.
There’s now a Careers advice space on Quora, you might find it interesting.
8- Resources:
– Cracking the Coding Interview: 189 Programming Questions and Solutions
Top sites for practice problems:
• Facebook Sample Interview Problems and Solutions
• InterviewBit
• LeetCode
• HackerRank
Video prep guides for tech interviews:
• Cracking the Facebook Coding Interview: The Approach (The password is FB_IPS)
• Cracking the Facebook Coding Interview: Problem Walk-through (The password is FB_IPS)
Additional resources*:
• I Interviewed at Five Top Companies in Silicon Valley in Five Days, and Luckily Got
Five Job Offers
What are the best alternatives to G-Suite now Google Workspace?


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What are the best alternatives to G-Suite now Google Workspace?
There are several alternatives to G Suite (now known as Google Workspace) that businesses and individuals use for email, document creation, and collaboration. Some popular alternatives include:
- Microsoft 365: This suite includes Office applications like Word, Excel, and PowerPoint, as well as email and calendar through Outlook, and other collaboration tools like Teams.
- Zoho Workplace: This suite includes email, document creation and editing, and collaboration tools, and also includes a range of other business applications like CRM and HR software.
- Slack: This is a popular communication and collaboration tool that is often used as an alternative to email for teams.
- Asana: This is a project management tool that helps teams organize and track their work, and can be used as an alternative to Google Docs for document collaboration.
- Notion: This is a productivity and organization tool that allows users to create and share notes, tasks, wikis, and databases.
It’s important to consider the specific needs of your business or organization when selecting a productivity suite. It’s also a good idea to try out several different options before making a decision, so that you can find the one that best fits your workflow and communication needs.
- Office 365 suite is an alternative, with similar features.For about $79 per year (or $6.99 per month), Office 365 Personal will allow a customer to install and use Microsoft Office on one Windows or Mac PC, plus one tablet. It also includes all of the other benefits of Office 365, including 20 GB of additional OneDrive cloud storage and 60 minutes per month of Skype calls. Office 365 Suite Features and plans. To get a professional email with Office 365, you need to get your domain name from a domain provider like DjamgaWeb or Godaddy.
- LibreOpenOffice:
LibreOffice is a free and open source office suite, a project of The Document Foundation. LibreOffice suite comprises programs for word processing, the creation and editing of spreadsheets, slideshows, diagrams and drawings, working with databases, and composing mathematical formulae. It is available in 110 languages. - Apache Open Office:
is an open-source office productivity software suite. It is one of the successor projects of OpenOffice.org and the designated successor of IBM Lotus Symphony.[5] It is a close cousin of LibreOffice and NeoOffice.
It contains a word processor (Writer), a spreadsheet (Calc), a presentation application (Impress), a drawing application (Draw), a formula editor (Math), and a database management application (Base).
I currently use both G suite and Office 365 and from my personal experience G suite is far superior in design, simplicity and usability.
Office 365 interface is heavy and confusing and opens several tabs on the browser.
G suite interface is Gmail like, smooth.
The question is why G suite?
- Gives you a professional custom email (you@yourcompany.com (mailto:you@yourcompany.com))
- Allows you to access documents in the cloud with over 30GB of storage
- Helps you work faster from anywhere and from any device
The Pros:
- All useful apps to manage your small business in one place from same provider with 24/7 support.
- Slick and extremely fast apps like gmail, google groups
- You can set them up yourself with no knowledge of IT.
- Cost efficient
- Easy to use as most people already use gmail and other google products.
- 24/7 Support: (https://gsuite.google.com/support/) If you call or email Google anytime , they will help you set it up very quickly and get you ready.
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The Cons:
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- G suite groups don’t allow you to add more than 25 people at the time.
What is Google Workspace?
Google Workspace is a cloud-based productivity suite that helps teams communicate, collaborate and get things done from anywhere and on any device. It's simple to set up, use and manage, so your business can focus on what really matters.
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Look professional and communicate as you@yourcompany.com. Gmail's simple features help you build your brand while getting more done.
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Check emails, share files, edit documents, hold video meetings and more, whether you're at work, at home or on the move. You can pick up where you left off from a computer, tablet or phone.
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List of Freely available programming books - What is the single most influential book every Programmers should read
- Bjarne Stroustrup - The C++ Programming Language
- Brian W. Kernighan, Rob Pike - The Practice of Programming
- Donald Knuth - The Art of Computer Programming
- Ellen Ullman - Close to the Machine
- Ellis Horowitz - Fundamentals of Computer Algorithms
- Eric Raymond - The Art of Unix Programming
- Gerald M. Weinberg - The Psychology of Computer Programming
- James Gosling - The Java Programming Language
- Joel Spolsky - The Best Software Writing I
- Keith Curtis - After the Software Wars
- Richard M. Stallman - Free Software, Free Society
- Richard P. Gabriel - Patterns of Software
- Richard P. Gabriel - Innovation Happens Elsewhere
- Code Complete (2nd edition) by Steve McConnell
- The Pragmatic Programmer
- Structure and Interpretation of Computer Programs
- The C Programming Language by Kernighan and Ritchie
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
- Design Patterns by the Gang of Four
- Refactoring: Improving the Design of Existing Code
- The Mythical Man Month
- The Art of Computer Programming by Donald Knuth
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
- Gödel, Escher, Bach by Douglas Hofstadter
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- Effective C++
- More Effective C++
- CODE by Charles Petzold
- Programming Pearls by Jon Bentley
- Working Effectively with Legacy Code by Michael C. Feathers
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel
- Surely You're Joking, Mr. Feynman!
- Effective Java 2nd edition
- Patterns of Enterprise Application Architecture by Martin Fowler
- The Little Schemer
- The Seasoned Schemer
- Why's (Poignant) Guide to Ruby
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
- The Art of Unix Programming
- Test-Driven Development: By Example by Kent Beck
- Practices of an Agile Developer
- Don't Make Me Think
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
- Domain Driven Designs by Eric Evans
- The Design of Everyday Things by Donald Norman
- Modern C++ Design by Andrei Alexandrescu
- Best Software Writing I by Joel Spolsky
- The Practice of Programming by Kernighan and Pike
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
- Software Estimation: Demystifying the Black Art by Steve McConnel
- The Passionate Programmer (My Job Went To India) by Chad Fowler
- Hackers: Heroes of the Computer Revolution
- Algorithms + Data Structures = Programs
- Writing Solid Code
- JavaScript - The Good Parts
- Getting Real by 37 Signals
- Foundations of Programming by Karl Seguin
- Computer Graphics: Principles and Practice in C (2nd Edition)
- Thinking in Java by Bruce Eckel
- The Elements of Computing Systems
- Refactoring to Patterns by Joshua Kerievsky
- Modern Operating Systems by Andrew S. Tanenbaum
- The Annotated Turing
- Things That Make Us Smart by Donald Norman
- The Timeless Way of Building by Christopher Alexander
- The Deadline: A Novel About Project Management by Tom DeMarco
- The C++ Programming Language (3rd edition) by Stroustrup
- Patterns of Enterprise Application Architecture
- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
- Object Thinking by Dr. David West
- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
- The Timeless Way of Building by Christopher Alexander
- Design Patterns in C# by Steve Metsker
- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
- Effective Java by Joshua Bloch
- Computability by N. J. Cutland
- Masterminds of Programming
- The Tao Te Ching
- The Productive Programmer
- The Art of Deception by Kevin Mitnick
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
- Masters of Doom
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
- How To Solve It by George Polya
- The Alchemist by Paulo Coelho
- Smalltalk-80: The Language and its Implementation
- Writing Secure Code (2nd Edition) by Michael Howard
- Introduction to Functional Programming by Philip Wadler and Richard Bird
- No Bugs! by David Thielen
- Rework by Jason Freid and DHH
- JUnit in Action
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Top 1000 Canada Quiz and trivia: CANADA CITIZENSHIP TEST- HISTORY - GEOGRAPHY - GOVERNMENT- CULTURE - PEOPLE - LANGUAGES - TRAVEL - WILDLIFE - HOCKEY - TOURISM - SCENERIES - ARTS - DATA VISUALIZATION

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Health Health, a science-based community to discuss human health
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