Download the AI & Machine Learning For Dummies PRO App: iOS - Android Our AI and Machine Learning For Dummies PRO App can help you Ace the following AI and Machine Learning certifications:
The AI revolution continues to blaze through 2024. June was a month of monumental strides, marked by breakthroughs in quantum AI, autonomous medical drones, and natural language processing. But the AI landscape is a dynamic one, and July has already proven to be no exception.
This month, we’re diving deep into the latest AI developments, from groundbreaking research to real-world applications. We’ll explore how AI is reshaping industries, addressing global challenges, and redefining what’s possible. Join us as we uncover the stories behind the headlines and analyze the implications of these innovations for society.
Whether you’re an AI expert or just curious about the future, this blog is your go-to source for the most up-to-date insights. Stay tuned for daily updates as we navigate the exciting world of artificial intelligence together.
A Daily Chronicle of AI Innovations on August 30th 2024
Apple and Nvidia may invest in OpenAI
Amazon’s new Alexa voice assistant will use Claude AI
OpenAI and Anthropic will share their models with the US government
Google is working on AI that can hear signs of sickness
OpenAI and Anthropic partner with US gov
China’s new Qwen2 beats GPT-4o
AI startup reaches 100M token context
China’s new Qwen2 beats GPT-4o
Alibaba just unveiled Qwen2-VL, a new vision-language AI model that outperforms GPT-4o in several benchmarks — particularly excelling in document comprehension and multilingual text-image understanding.
Qwen2-VL can understand images of various resolutions and ratios, as well as videos over 20 minutes long.
The model excels particularly at complex tasks such as college-level problem-solving, mathematical reasoning, and document analysis.
It also supports multilingual text understanding in images, including most European languages, Japanese, Korean, Arabic, and Vietnamese.
You can try Qwen2-VL on Hugging Face, with more information on the official announcement blog.
There’s yet another new contender in the state-of-the-art AI model arena, and it comes from China’s Alibaba. Qwen2-VL’s ability to understand diverse visual inputs and multilingual requests could lead to more sophisticated, globally accessible AI applications.
Apple and Nvidia are reportedly in talks to participate in a significant funding round for OpenAI, with Apple planning to integrate ChatGPT into iOS and Nvidia being a key supplier of the chips that power OpenAI’s AI services.
Apple, which had earlier considered appointing Phil Schiller to OpenAI’s board before abandoning the plan, is looking to deepen its involvement with OpenAI as it prepares to enhance Siri with ChatGPT capabilities later this year.
Nvidia, whose hardware is essential for OpenAI’s operations, is also considering investing in this funding round, joining Microsoft, which has been a major investor in OpenAI since 2019 and made another substantial investment in 2023.
OpenAI and Anthropic just signed a groundbreaking agreement with the U.S. Artificial Intelligence Safety Institute to allow government access and testing of their AI models before public release.
The U.S. AI Safety Institute will have access to major new models from both companies prior to and after their public release.
This collaboration is a step toward AI regulation and safety efforts, with the U.S. government evaluating AI models’ capabilities and associated risks.
The institute will provide feedback to OpenAI and Anthropic on potential safety improvements that should be made.
These agreements come as AI companies face increasing regulatory scrutiny, with California legislators recently passing a broad AI regulation bill earlier today.
The two most popular AI companies in the world are granting the U.S. government access to unreleased models before release. This could reshape how AI is developed, tested, and deployed worldwide, with major implications around innovation, safety, and international competition in the AI space, for better or worse.
Amazon’s new Alexa voice assistant will use Claude AI
Amazon’s new voice assistant, “Remarkable Alexa,” will launch in October and be powered by Anthropic’s Claude AI, offering a subscription-based service.
The existing Alexa model struggled with accuracy, leading Amazon to invest in Anthropic’s AI technology after facing internal technical and bureaucratic issues.
Remarkable Alexa is set to feature daily AI-generated news summaries, a child-focused chatbot, and conversational shopping tools, with a demo planned for Amazon’s September event.
Magic just developed LTM-2-mini, a model capable of processing 100 million tokens of context — equivalent to about 10 million lines of code or 750 novels — and partnered with Google Cloud to build advanced AI supercomputers.
LTM-2-mini can process and understand 100 million tokens of context given during inference, surpassing current models by 50x.
The model’s innovative algorithm processes long sequences of data 1000x more efficiently than the current top-performing AI models.
Magic is also partnering with Google Cloud to build supercomputers powered by Nvidia’s newest and most advanced GPUs.
The company has raised more than $450 million in total funding, including a recent $320 million investment round.
This breakthrough in context length allows AI agents to process and reason over dense and complicated codebases, vast databases, and years of conversation history in a single inference. It’s a significant step toward creating AI assistants with near-perfect recall and memory.
Google is working on AI that can hear signs of sickness
Google is developing artificial intelligence technology that can detect early signs of illness by analyzing sound signals like coughs and sniffles.
The AI model is trained with 300 million audio samples and can identify diseases such as tuberculosis by recognizing specific audio patterns of labored breathing.
Google has partnered with Salcit Technologies, an AI startup in India, to integrate this technology into smartphones to assist high-risk populations in areas with limited healthcare access.
Anthropic’s Prompt Engineering Interactive Tutorial: a digital platform designed to teach users how to effectively craft prompts for AI applications, enhancing user interaction and efficiency.
Documents reveal state-linked Chinese entities are using cloud services from AWS or its rivals to access advanced US chips and AI models they cannot acquire otherwise.
California lawmakersapproved a bill proposing sweeping AI regulations, including safety testing requirements and potential legal consequences for harmful AI systems.
A Daily Chronicle of AI Innovations on August 29th 2024
AI creates DOOM video game in real-time
OpenAI raises at $100B valuation
AI spots cancer earlier than ever
Nvidia just showed how hard it is to be the AI king
Google researchers run Doom on a self-generating AI model
Midjourney says it’s ‘getting into hardware’
OpenAI aims for $100B+ valuation in new funding round
Major websites reject Apple AI data scraping
AI creates DOOM video game in real-time
Google researchers just developed GameNGen, an AI system that can simulate the classic game DOOM in real-time, running at over 20 frames per second and producing visuals nearly indistinguishable from the original game.
GameNGen produces playable gameplay at 20 frames per second on a single chip, with each frame predicted by a diffusion model.
The AI was trained on 900M frames of gameplay data, resulting in 3-second clips almost indistinguishable from the actual game by playtesters.
Running on a single TPU, GameNGen handles Doom’s 3D environments and fast-paced action without traditional game engine components.
In tests, human raters could barely distinguish between short clips of the AI simulation and the actual game.
GameNGen is the first AI model that can generate a complex and playable video game in real-time without any underlying real game engine. We’re at the fascinating time where soon, AI will be able to create entire games on the fly, personalized to each player.
OpenAI is reportedly in talks to raise a new funding round at a valuation exceeding $100 billion, led by Thrive Capital, with Microsoft also expected to participate.
The potential valuation of over $100 billion would be significantly higher than OpenAI’s previous $86 billion valuation.
Thrive Capital is expected to invest around $1 billion in this round.
OpenAI’s annualized revenue reportedly surpassed $3.4 billion earlier this year.
The company is still, however, projected to lose nearly $5 billion by the end of the year and has already spent $8.5 billion on AI training and staffing.
Building AI is expensive, and raising billions of dollars at a $100B+ valuation would silence OpenAI’s critics who insist that the company is on its downfall. The increased valuation also suggests that the company has potential hidden breakthroughs behind the scenes, such as Project Strawberry and Orion.
Researchers recently developed an AI tool called AINU that can differentiate cancer cells from normal cells and detect early stages of viral infection, by analyzing high-resolution images of cell nuclei.
AINU uses a convolutional neural network to analyze images captured by STORM microscopy, which offers nanoscale resolution.
The AI can detect structural changes in cells as small as 20 nanometers, 5,000 times smaller than a human hair’s width.
AINU also detected viral infections (herpes simplex virus type-1) just one hour after infection by observing subtle changes in DNA packing.
The tool can accurately identify stem cells too, which could accelerate stem cell research without relying on animal testing.
Yesterday, researchers revealed an AI tool to help with early dementia detection, and now AI is detecting cancer cells at a nanoscale level. Clinical applications may be years away, but AI healthcare breakthroughs like AINU are only accelerating — and will dramatically revolutionize scientific research in the coming years.
Nvidia just showed how hard it is to be the AI king
Nvidia achieved strong second-quarter results by more than doubling its revenue compared to the same period last year, but industry experts anticipated these outcomes due to ongoing investments in AI by tech companies.
Despite reporting $30.04 billion in revenue, which surpassed analyst expectations, Nvidia’s stock fell 6.9% after hours due to investor concerns and sky-high expectations.
Issues like shipment delays for Nvidia’s upcoming Blackwell GPUs and slightly lower-than-expected revenue projections for the next quarter also contributed to investor unease, as noted by multiple analysts.
Midjourney, known for its AI image-generation tool, announced it is entering the hardware market and invited job seekers to join its new division.
The announcement was made on Midjourney’s official X account, revealing that founder David Holz and new hire Ahmad Abbas, a former Apple hardware manager, will lead the hardware efforts.
Midjourney hinted at multiple ongoing projects and the possibility of new form factors, though no specific timeline or further details have been provided yet.
OpenAI aims for $100B+ valuation in new funding round
OpenAI is reportedly negotiating with venture capital firms to raise a large sum of money, potentially valuing the company at over $100 billion.
Thrive Capital plans to invest $1 billion in this funding round, and Microsoft is also expected to contribute additional funds, as reported by The Wall Street Journal.
If successful, this would be the most substantial new capital for OpenAI since Microsoft’s $10 billion investment in January 2023, with OpenAI’s valuation potentially exceeding $103 billion based on recent negotiations.
Many of the largest websites, such as Facebook, Instagram, and The New York Times, have opted out of Apple’s AI training by using the Applebot-Extended tag to exclude their content.
Apple allows publishers to easily opt out of content scraping for Apple Intelligence training through a publicly-accessible robots.txt file, ensuring their data is not used for AI purposes.
Apple’s use of Applebot for AI training is designed to be ethical, with mechanisms to filter out personal data and a system for web publishers to prevent their data from being utilized.
A Daily Chronicle of AI Innovations on August 28th 2024
OpenAI prepares ‘Project Strawberry’
Google launches trio of new models
😯Google AI-Powered Interview Warmup
Create an AI prompt optimizer GPT
AI tools help early dementia detection
📈 Nvidia earnings to test AI boom
Google Meet will now take notes for you
OpenAI prepares ‘Project Strawberry’
OpenAI researchers are preparing to launch a new AI model, code-named Strawberry (previously Q*), that demonstrates superior reasoning capabilities in solving complex problems, according to a new report via The Information.
Project Strawberry could be integrated into ChatGPT as soon as this fall, marking a significant leap in AI intelligence.
Given extra “thinking” time, Strawberry can tackle subjective topics and solve complex puzzles like the New York Times Connections.
OpenAI is using Strawberry to generate high-quality training data for another secretive upcoming LLM, reportedly code-named Orion.
The new AI model could enhance OpenAI’s development of AI agents, potentially automating multi-step tasks more effectively.
If Strawberry lives up to the leaks, it could mark a significant leap in AI reasoning capabilities, potentially advancing OpenAI towards Stage 2 of its five-level roadmap to AGI. With ChatGPT reported to gain these capabilities this fall, we’re likely on the verge of seeing the next major wave of AI disruption.
Google Meet’s new AI-powered feature, “take notes for me,” has started rolling out today, summarizing meetings for Google Workspace customers with specific add-ons and initially announced at the 2023 Cloud Next conference.
This feature automatically generates a Google Doc with meeting notes, attaches it to the calendar event, and sends it to the meeting organizer and participants who activated the tool, although it currently supports only spoken English.
Google predicts the feature will be available to all Google Workspace customers by September 10th, 2024, but there are concerns about its accuracy, given the performance of similar transcription tools in the past.
Google just released three new experimental Gemini 1.5 models, including a compact 8B parameter version, an improved Pro model, and an enhanced Flash model — all available for developers on Google AI Studio.
Gemini 1.5 Flash-8B is a smaller, faster model that can handle text, images, and other data types efficiently for super quick responses while processing a lot of information.
The updated Gemini 1.5 Pro model is now better at writing code and understanding complex instructions.
An improved Gemini 1.5 Flash model offers overall enhancements, performing better on Google’s internal tests across various tasks.
The upgraded Gemini 1.5 Pro model now ranks as #2, and the new Gemini 1.5 Flash ranks as #6 on the Chatbot Arena leaderboard.
While OpenAI is leaving everyone waiting, Google has been shipping out constant upgrades and new features to its AI offerings. These new enhancements give Gemini 1.5 Flash big improvements overall and Gemini 1.5 Pro new upgrades in math, coding, and responding to longer prompts.
Google actually runs this tasty thing called “Interview Warmup.” It’s an AI-powered training tool for your next big interview. It throws real questions based on your discipline: UX, data and analytics, cybersecurity, etc. Then, the magic kicks in, evaluating your audio answers and sending back recommendations on things like framing your qualifications to supporting your impact.
5 questions. Get some analysis. Build some confidence. Easy, right? 🌟
Oh. And for the tech-oriented: Also make sure you check this site out, too. Videos, former (real) interview questions, the works. Interview Prep – Google Tech Dev Guide
OpenAI’s Custom GPTs allow premium users to create AI assistants that can optimize prompts for other AI creative tools such as Midjourney for AI image generation or Gen-3 for AI video generation.
Log into your ChatGPT Plus account and click “Explore GPTs”, then click “Create”.
Name your GPT and add a brief description.
In the Instructions, paste: “User is using an AI video generator called [Tool Name]. You need to craft a perfect prompt for the topic they ask by following the prompting guide below. The prompt needs to follow the format provided in the guide.”
Test your GPT in the preview panel, then click “Create” to finalize and choose sharing options.
Hot tip: Add a complete prompting guide for your chosen AI tool (e.g. Runway’s Gen-3 prompting guide)
Scientists from the Universities of Edinburgh and Dundee are launching a massive AI-driven study of over 1.6 million brain scans to develop tools for early dementia prediction and diagnosis.
The project, called NEURii, will use AI and machine learning to analyze CT and MRI scans from Scottish patients over the past decade.
Researchers aim to create digital tools for radiologists to assess dementia risk during routine scans.
The study will match image data with linked health records to identify patterns associated with dementia risk.
With global dementia cases projected to reach 153 million by 2050, this research could significantly impact early intervention and treatment development.
This week alone, we’ve seen AI developing new cancer drugs, 3D printing lifelike human organs, and now creating tools for early dementia detection. As AI rapidly advances in healthcare, we’re accelerating into a new era of personalized medicine and preventative care.
There have been several negative reports ahead of Nvidia’s earnings, ranging from supply chain/design challenges to concerns about use cases and applications. However, one thing we learned from discussions with customers is that demand is still extremely constrained.
Key topics ahead of the results:
1. Will the Hopper architecture stay stronger for longer? 2. Is Blackwell really delayed? 3. What is the upside if the company can deliver on the systems orders?
Here are some thoughts on each:
1. Key players like Microsoft, Snowflake, and Tesla highlighted tight capacity for GPUs and more demand than available supply. Snowflake particularly called out H100 (un)availability. This makes us believe that the Hopper cycle may extend beyond ’23/24
2. There were several reports pointing to Blackwell delays, the new generation GPU. Analysts have now taken it out of estimates for this year (C24). However, our research indicates that the delays are mainly on the systems side, which were not supposed to be delivered until (C25). Meanwhile, Nvidia’s CEO noted that we can expect significant revenues from Blackwell this year … key will be to find out if this is still the case.
3. Systems – namely the GB200 NVL36/72 is where the delays are. But our intel suggests that the order book for these is through the roof due to the TCO (total cost of ownership) they offer. If Nvidia is in fact able to deliver these in ’25 revenue from systems alone can exceed >$100BN with total DC revenue >$200BN.
What Else is happening in AI on August 28th 2024!
Apple announced a September 9 event where it’s expected to debut the iPhone 16 with new generative AI features.
Elon Muskendorsed California’s Senate Bill 1047, which would require safety testing for large AI models, breaking with other tech leaders who oppose the regulation.
Amazonplans to launch a delayed AI-powered Alexa subscription in October, featuring “Smart Briefing” AI-generated news summaries.
Anthropicannounced the full release of its Artifacts feature for all Claude users, including mobile apps, after millions were created in its test phase.
A Daily Chronicle of AI Innovations on August 27th 2024
AI can 3D print lifelike human organs
Anthropic reveals Claude’s secret sauce
Amazon aims to launch delayed AI Alexa subscription in October
OpenAI, Adobe, Microsoft want all companies to label AI-generated content
ChatGPT teams up with ASU
Discovering new drugs with AI
How to use Midjourney ‘Erase‘
AI can 3D print lifelike human organs
Researchers at Washington State University recently developed an AI technique called Bayesian Optimization that dramatically improves the speed and efficiency of 3D printing lifelike human organs.
The AI balances geometric precision, density, and printing time to create organ models that look and feel authentic.
In tests, it printed 60 continually improving versions of kidney and prostate organ models.
This approach significantly reduces the time and materials needed to find optimal 3D printing settings for complex objects.
The technology also has potential applications beyond medicine — for example, in the computer science, automotive, and aviation industries.
With cheaper, lifelike 3D-printed human organs, medical students could better practice for surgery before operating on actual patients. Beyond medicine, this AI technique could help reduce manufacturing costs for a variety of things like smartphones, car parts, and even airplane components.
Scientists from China and the U.S. just developed ActFound, a new AI model that outperforms existing methods in predicting drug bioactivity, potentially accelerating and reducing costs in drug development.
ActFound combines meta-learning and pairwise learning to overcome common limitations in AI drug discovery, like small datasets and incompatible measurements.
The model was trained on 35,000+ assays (metal ore breakdowns) and 1.6 million experimentally measured bioactivities from a popular chemical database.
In tests, ActFound outperformed nine competing models and showed strong performance in predicting cancer drug bioactivity.
ActFound could significantly speed up drug development by accurately predicting compound properties with less data and lower costs than traditional methods. While still in early stages, AI breakthroughs like this are the lesser-talked about developments that could end up saving millions of lives.
OpenAI’s ChatGPT is headed to Arizona State University (ASU), where the university is integrating the AI assistant into over 200 projects across teaching, research, and operations.
ASU is using ChatGPT Edu, a version designed for universities with enhanced privacy and security features.
The university also launched an ‘AI Innovation Challenge’ for faculty and staff, receiving an overwhelming demand for using ChatGPT to maximize teaching, research, and ops.
Key projects include an AI writing companion for scholarly work, ‘Sam’ (a chatbot for med students to practice patient interactions), and AI-assisted research recruitment.
The partnership has inspired other institutions like Oxford and Wharton to pursue similar collaborations.
While some schools are attempting to resist AI, ASU is embracing ChatGPT to make learning more personalized and to prepare students for an increasingly AI-driven job market. As education continues to change in the age of AI, case studies like this will be instrumental in shaping the future of academia.
Source: https://openai.com/index/asu/
Anthropic reveals Claude’s secret sauce
Anthropic has published the system prompts for its latest AI models, including Claude 3 Opus, Claude 3.5 Sonnet, and Claude 3.5 Haiku, to demonstrate transparency and ethical practices.
The system prompts reveal specific behaviors and capabilities of the Claude models, such as the inability to open URLs or recognize faces, aiming to ensure ethical interactions.
Anthropic plans to continue updating and disclosing these system prompts to promote transparency, potentially pressuring other AI vendors to follow suit.
Amazon aims to launch delayed AI Alexa subscription in October
The new Alexa AI, set to launch around mid-October, will feature a “Smart Briefing” that provides daily, AI-generated news summaries based on user preferences.
A more personalized experience is expected, with Alexa AI learning user preferences through interactive and tailored responses, such as dietary requirements for recipe suggestions.
Alexa AI will also introduce a “Shopping Scout” feature to help users find deals and track prices, alongside a kid-friendly “Explore with Alexa 2.0” for safe, moderated conversations.
OpenAI, Adobe, Microsoft want all companies to label AI-generated content
OpenAI, Adobe, and Microsoft now back a California bill that mandates tech companies to add watermarks to AI-generated content, with the bill set for a final vote in August.
AB 3211 requires AI-generated photos, videos, and audio clips to have watermarks in their metadata and mandates large online platforms to label AI content clearly for average viewers.
Initially opposed by a trade group representing major software companies, the bill gained support from OpenAI, Adobe, and Microsoft after amendments addressed concerns about its practicality.
Inflection AI partnered with Data Transfer Initiative, enabling Pi users to export conversations and announced plans to cap free usage while focusing on enterprise AI.
Source: https://inflection.ai/the-future-of-pi
Phariareleased Pharia-1-LLM-7B, an open-source model optimized for German, French, and Spanish that excels in domain-specific applications.
IBMpreviewed Spyre, a new AI accelerator chip for IBM Z mainframes, designed to scale enterprise AI workloads with clustering capabilities.
Source: https://research.ibm.com/blog/spyre-for-z
Hugging FaceandGoogle Cloud just partnered up to release optimized Deep Learning Containers for building AI with open models on Google Cloud infrastructure.
SPONSOR US: Get your product in front of over 1 million+ AI enthusiasts
Our Daily AI Chronicle Blog, newsletter and podcast is read by thousands of Redditors, Quorans, Linkedin professionals, tech executives, investors, engineers, managers, and business owners around the world. Get in touch today.
A Daily Chronicle of AI Innovations on August 26th 2024
Amazon is telling its salespeople to trash talk Google, Microsoft, and OpenAI
Apple may be working on an AI ‘personality’ to replace Siri on its robots
Chinese companies showcased 27 humanoid robots alongside Tesla’s Optimus
AI learns to plan better without humans
How to use Ideogram for generating images
️ Grok-2 improves speed, accuracy, transparency
AI learns to plan better without humans
IBM Research and Cornell University recently created AutoToS, a system that teaches AI to solve complex planning problems at 100% accuracy — without needing a human to check its work.
AutoToS is like a smart tutor for AI, helping it learn how to break down and solve tricky problems step-by-step.
The system uses clever tests to check the AI’s work, pointing out mistakes and showing examples of how to do better without human interferance.
This approach seems to work equally as well for smaller and larger models.
AutoToS succeeded in teaching AI to solve complex puzzles, including classic problems like arranging blocks and solving Sokoban, a box-pushing game.
Right now, it’s difficult to trust AI agents to completely autonomously perform actions on your behalf, but AutoToS is solving complex tasks at a 100% accuracy. If this system works in the real world, it’s the next big step in creating more reliable AI assistants.
Apple may be working on an AI ‘personality’ to replace Siri on its robots
Apple is developing a new AI-based ‘personality’ for use in upcoming robotic devices, aiming to enhance interactions similar to how Siri functions on existing Apple products.
Bloomberg’s Mark Gurman reports that Apple’s futuristic AI assistant will be more humanlike and could operate on a tabletop product and other future robots, potentially costing under $1,000.
The project is in early development stages with no guarantees of release, while Apple continues to integrate generative AI features into its devices, like iPhones, iPads, and Macs, later this year.
Chinese companies showcased 27 humanoid robots alongside Tesla’s Optimus
At the Beijing World Robot Conference, Tesla’s Optimus humanoid was displayed motionless inside a clear box, facing tough competition from Chinese robots demonstrated by various companies.
The event saw 27 new humanoid robots debut, with significant financial investments in China’s robotics industry surpassing 100 billion yuan over the past decade.
Chinese startups like Agibot and Stardust Intelligence showcased robots capable of performing complex tasks, while experts believe Tesla’s and other U.S. companies’ robot technology leads by about one to two years.
xAI’s Grok-2 and Grok-2 mini just made major improvements — doubling the model’s speed in the mini version and showing increased accuracy in both models, just days after its beta launch.
Grok-2 mini is now twice as fast as it was previously, thanks to a rewritten inference stack using SGLang.
Both Grok-2 and its mini version have become slightly more accurate due to reduced quantization error, according to one xAI employee.
Additionally, both Grok-2 models are now part of the LMSYS Chatbot Arena leaderboard for increased transparency, with Grok-2’s larger model ranking #2 and surpassing Claude 3.5 Sonnet.
Grok-2 excels particularly in math, where it ranks #1 and performs at a state-of-the-art level in hard prompts, coding, and instruction-following.
From being founded only ~18 months ago, to creating an LLM ranked third in the world, it’s safe to say that xAI has the entire AI community mind blown. This not only makes Grok-2 a top contender in the AI race but also intensifies competition, potentially accelerating advancements across the industry.
At the 2024 World Robot Conference in Beijing, Chinese companies showcased 27 humanoid robots alongside Tesla’s Optimus, signalling China’s ambition to dominate the industry.
Chinese tech firms unveiled 27 humanoid robots at the expo, with Tesla’s Optimus being the only foreign competitor present.
AGIBOT, founded by a Huawei alumnus, presented robots powered by large language models (LLMs) for industrial use and customer service.
Other notable entries included Astribot’s S1 robot assistant capable of writing calligraphy and playing musical instruments, and Galbot’s wheeled robots for food delivery and retail tasks.
Despite the impressive showcase, experts note that technological hurdles and high costs still create challenges for Chinese manufacturers.
China may be slightly behind in the AI race against the U.S., but it’s clear the country is committed to dominating the humanoid robotics race. With a whopping 27 China-based humanoid robots demonstrating a wide-range of use cases at the event, commercially available humanoids may be coming sooner than most expect.
Ideogram 2.0, the latest state-of-the-art AI image generator, excels at creating images that include text — opening new possibilities for use cases like thumbnails, posters, newsletter graphics, memes, and more.
Head over to Ideogram’s website and Sign up. You’ll get free credits to try the image generator without a credit card.
Click “Describe what you want to see” and enter a detailed text prompt for your desired image.
Customize settings like aspect ratio, AI model (choose 2.0), and style (Realistic, Design, 3D, or Anime).
Click “Generate” to create four AI-generated images based on your prompt!
Pro tip: Experiment with different prompts and settings to discover its full potential and create unique visuals for your projects!
What Else is Happening in AI on August 26th 2024!
Scientists to use AI and 1.6 million brain scans for earlier and more accurate dementia diagnoses.
Anthropic supported California’s AI regulation bill after changes were made, saying its benefits likely outweigh its costs for advanced AI development.
A Daily Chronicle of AI Innovations on August 23rd 2024
Nvidia and Mistral make laptop-ready AI
Amazon’s AI assistant saves 4,500 years of development time
Slack AI could be tricked into leaking login details and more
Cruise’s robotaxis are coming on Uber
Google DeepMind workers urge the company to end ties with military organizations
Salesforce unveils AI agents for sales
Nvidia and Mistral make laptop-ready AI
Nvidia and Mistral just released Mistral-NeMo-Minitron 8B, a highly accurate small language model that can run efficiently on laptops and PCs.
The model uses optimization techniques like pruning (removing certain weights) and distillation (retraining the pruned model on a small dataset) to achieve high accuracy with a smaller footprint.
These optimizations resulted in up to 40x cost savings in terms of raw compute during training.
Laptops and PCs can run the model locally for faster and more secure interactions with AI.
Minitron 8B leads nine language-driven AI benchmarks for similarly sized models from language understanding to reasoning and coding.
AI models that are small enough to run locally on laptops and PCs means less reliance on cloud services, improved data privacy, and faster responses. As this tech evolves, we could soon see advanced AI in everything from smartphones and watches to home appliances.
Amazon’s AI assistant saves 4,500 years of development time
Amazon CEO Andy Jassy stated that their AI assistant, Amazon Q, has significantly reduced software upgrade times, saving the company thousands of work hours.
Jassy mentioned that implementing Amazon Q resulted in estimated savings equivalent to 4,500 developer-years and $260 million in annual efficiency gains.
The AI-generated code reviews were so accurate that 79% of them were shipped without any additional changes, demonstrating the tool’s effectiveness in streamlining tedious tasks.
Researchers just developed a new AI-based method called NES-VMC that can accurately calculate the excited states of atoms and molecules, a challenge in physics and chemistry that previously delayed improvements in solar tech.
NES-VMC (natural excited states variational Monte Carlo) accurately predicted quantum excited states on systems ranging from single atoms to benzene-sized molecules.
The method outperforms leading computational chemistry techniques, often achieving chemical accuracy.
Excited states are crucial for understanding light-matter interactions, key to improving solar cells, LEDs, lasers, and more.
NES-VMC overcomes long-standing challenges in physics and chemistry that have hindered progress in these fields.
This AI-driven breakthrough could lead to more efficient solar cells, brighter LEDs, and more powerful lasers. The ripple effects could be dramatic: lower electricity costs, improvements in phone and laptop battery life and displays, faster fiber-optic internet, and so much more.
Salesforce just introduced two fully autonomous, AI-powered sales agents, Einstein SDR Agent and Einstein Sales Coach Agent, designed to help sales teams accelerate growth through automation and personalization.
Einstein SDR Agent engages with inbound leads 24/7 to answer questions, handle objections, and book meetings.
Einstein Sales Coach Agent helps salespeople rehearse pitches and offers real-time suggestions during calls.
The agents both leverage Salesforce’s CRM data and external data uploaded via Data Cloud to generate accurate, contextually relevant responses.
The agents will be generally available in October, with more details expected to be released at Dreamforce conference in September.
By integrating AI agents into existing platforms, Salesforce is lowering the barrier for AI adoption in business processes. These agents offer 24/7 support and automate repetitive tasks like qualifying leads and booking meetings, freeing human sales teams to focus on high-value tasks and potentially close more deals.
Slack AI could be tricked into leaking login details and more
Security experts found that Slack’s AI assistant can be misled into disclosing sensitive information, like API keys, to unauthorized users through carefully crafted prompts.
Hackers can exploit this vulnerability by creating a public Slack channel, inputting a malicious command that causes the AI to leak private data via clickable URLs.
Salesforce fixed the issue for private channels but public ones remain exposed, allowing attackers to use social engineering tactics to get workspace members to upload malicious documents.
Google DeepMind workers urge the company to end ties with military organizations
In May 2024, approximately 200 Google DeepMind employees signed a letter urging the company to cease its contracts with military organizations due to concerns over the use of AI technology in warfare, according to Time magazine.
The letter highlights internal tensions between Google’s AI division and its cloud business, referencing Google’s defense contract with the Israeli military and the use of AI for mass surveillance and targeting in Gaza.
The letter calls for Google to investigate claims of its cloud services being used by militaries, cut off such access, and establish a new governance body to prevent future military use of DeepMind’s AI technology.
A Daily Chronicle of AI Innovations on August 22nd 2024
Neuralink’s second patient is already playing video games with brain implant
Apple’s first foldable MacBook might see big delays
OpenAI joins Silicon Valley companies lobbying against California’s AI bill
Ideogram 2.0 launches with major upgrades
xAI releases Grok 2 in early beta
Create your own AI Clone
Disney AI brings robots to life
Ideogram 2.0 launches with major upgrades
Ideogram just released version 2.0 of its advanced text-to-image model with major upgrades and new features, including five new image styles, an iOS app, a beta API, and over 1 billion public Ideogram images.
Ideogram 2.0 offers five image styles: General, Realistic, Design, 3D, and Anime.
The Realistic style convincingly resembles photographs with dramatically improved textures for human features like hands and hair, a pain point for previous image generation models.
The Design style also significantly improves text rendering, allowing users to create greeting cards, t-shirt designs and more.
Ideogram offers a free tier that allows users to generate around 40 images, or 10 prompts a day at no charge.
Ideogram 2.0 consistently renders high-quality images with near perfect human hands and text — which is an instant ‘AI giveaway’ in other AI image generators. This makes the model the new gold standard for use cases like memes, newsletter images, YouTube thumbnails, posters, and more.
xAI has begun rolling out early beta access for Grok 2, a powerful new AI model that leverages real-time data from X and uses Flux.1 to generate relatively unfiltered AI images.
Grok 2 is now available to a select group of premium X users in early beta mode.
The model can access and use real-time information from X, setting it apart from ChatGPT and other LLMs.
Grok 2 offers two modes: regular and “fun” mode, with the latter providing a more distinctive and entertaining personality.
When gathering and summarizing news, Grok 2 can reference specific tweets, a capability that cannot be found in ChatGPT or Claude.
Grok 2’s biggest advantage against other top-tier AI chatbots like ChatGPT is its ability to access real-time information from X and provide unfiltered responses. And with Grok 3 rumoured to be coming at the end of 2024, xAI has proven itself as a serious competitor in the LLM race — in a very short period of time.
ETH Zurich and Disney Research scientists have developed an AI system that can generate realistic, physics-based movements for virtual characters and robots from simple text or image inputs.
The system uses a two-stage approach: first, it learns a latent representation of motion from a large dataset, then trains a control policy using reinforcement learning.
It can handle a diverse range of motions, from simple walking to complex acrobatics, outperforming previous methods in accuracy and generalization.
The AI adapts to physical constraints, allowing it to transfer motions to real robots while maintaining balance and style.
Disney released a video showcasing one robot trained on the new two-stage AI technique dancing and getting pushed around while staying on its feet.
This AI system bridges the gap between animation and robotics, helping humanoids move more naturally and adapt better to new situations. With personal robots coming as soon as 2025 and the rapid pace of AI and robotics advancements, we might be coexisting with robots sooner than most people realize.
Neuralink’s second patient is already playing video games with brain implant
Elon Musk’s company Neuralink has implanted a brain chip in a second human patient named Alex, who is now using it to play video games and design 3D objects.
Alex’s recovery from the procedure has been smooth, and he has successfully used computer-aided design software to create a custom mount for his Neuralink charger.
The core technology of Neuralink involves a small, implantable chip with flexible electrode threads that capture and transmit brain activity to external devices like computers.
OpenAI joins Silicon Valley companies lobbying against California’s AI bill
OpenAI’s chief strategy officer Jason Kwon argues that AI regulations should be managed by the federal government, not individual states, to avoid hindering progress and causing businesses to relocate from California.
Kwon states that a consistent, nation-wide set of AI policies will promote innovation, allowing the U.S. to become a leader in global AI standards, and thus opposes California’s SB 1047 bill.
The proposed California AI safety bill, designed by Senator Scott Wiener, includes measures like pre-deployment safety testing and whistleblower protections, and awaits its final vote before potentially being signed by Governor Gavin Newsom.
California and Google drafted a $300 million, 5-year partnership to fund in-state newsrooms and AI initiatives, including a $40 million annual “AI Innovation Accelerator”.
A Daily Chronicle of AI Innovations on August 21st 2024
OpenAI signs landmark agreement with Condé Nast
Microsoft releases new Phi-3.5 models, beating Google, OpenAI and more
AWS CEO tells employees that most developers could stop coding soon as AI takes over
OpenAI adds free fine-tuning to GPT-4o
Claude sued for copyright infringement
Create AI images in real-time on WhatsApp
Microsoft’s new AI beats larger models
Microsoft just released Phi-3.5-MoE, an advanced AI model that rivals the reasoning capabilities of much larger models while maintaining a compact and efficient architecture.
Phi-3.5-MoE uses a new mixture-of-experts (MoE) approach, which selectively activates only the most relevant parts of the model for each task to save compute power.
The new model excels at understanding and following complex instructions and can handle up to ~125,000 words in a single prompt.
In head-to-head benchmarks, Phi-3.5-MoE outperformed popular models like Meta’s Llama 3 8B and Google’s Gemma 2 9B, but fell short against OpenAI’s GPT-4o mini.
Microsoft made the model available under an open-source MIT license on Hugging Face.
While the mainstream media focuses on the most advanced large language model, there’s also another race amongst tech giants for the smartest, fastest, and smallest AI. Breakthroughs like Phi-3.5-MoE are paving the way for advanced AI models to run directly and privately on our mobile devices.
OpenAI signs landmark agreement with Condé Nast
OpenAI announced a new media partnership with Condé Nast to enhance search features using their SearchGPT prototype, aiming to make finding information and reliable content sources faster and more intuitive.
The partnership has raised transparency issues, particularly among Condé Nast’s unionized workers, who are worried about the impact on journalism and the lack of clear details on the agreement.
This deal occurs as Wall Street expresses growing concern over a potential AI bubble, with investors questioning the monetization and viability of AI technologies in the current market.
Microsoft releases new Phi-3.5 models, beating Google, OpenAI and more
Microsoft introduced three new open-source AI models, named mini-instruct, MoE-instruct, and vision-instruct, which excel in logical reasoning and support multiple languages but face challenges in factual accuracy and safety.
The Phi series aims to deliver highly efficient AI models for commercial and scientific purposes using quality training data, though specifics of the Phi-3.5 training process remain undisclosed by Microsoft.
All the new Phi 3.5 models are accessible under the MIT license on Hugging Face and Microsoft’s Azure AI Studio, but they require specialized GPU hardware like NVIDIA A100, A6000, or H100 for optimal performance.
AWS CEO tells employees that most developers could stop coding soon as AI takes over
A leaked recording revealed that AWS CEO Matt Garman believes software developers may soon stop coding as artificial intelligence takes over many of their tasks.
Garman’s remarks, shared during an internal chat in June, were intended as a positive forecast rather than a dire warning for software engineers, emphasizing new opportunities and skills.
Garman highlighted that developers should focus more on understanding customer needs and innovation, rather than just writing code, as AI tools increasingly manage the technical aspects.
Meta deploys new web crawlers that bypass scraping blocks
Meta has introduced new web crawling bots designed to collect data for training its AI models and related products without being easily blocked by website owners.
These new bots, Meta-ExternalAgent and Meta-ExternalFetcher, have features that potentially bypass the traditional robots.txt file, making website owners’ efforts to block them less effective.
Meta’s bots, launched in July, have shown low block rates compared to older versions, with only 1.5% blocking Meta-ExternalAgent and less than 1% blocking Meta-ExternalFetcher, according to Originality.ai.
OpenAI just launched free fine-tuning (up to 1 million tokens per day through September 23) for GPT-4o, allowing developers to customize the model for higher performance and accuracy.
Developers can now, for the first time ever, fine-tune GPT-4o to improve the model’s structure, tone, and domain-specific instructions for their AI applications.
Fine-tuning is available on all paid usage tiers with training costs of $25 per million tokens, but it is completely free until September 23.
OpenAI suggests that developers should see strong results from fine-tuning with only a few dozen training examples.
Additionally, Google’s Gemini API is giving developers 1.5 billion tokens for free every day on its Gemini 1.5 Flash model and 1.6 million tokens on its Gemini 1.5 Pro model.
Just last week, a company that was granted early access to fine-tune GPT-4o, produced Genie and achieved state-of-the-art scores on both SWE-bench Verified (43.8%) and Full (30.1%) benchmarks. With free fine-tuning now available to all developers, get ready for a new wave of smarter, faster and more capable AI bots.
A group of authors filed a lawsuit against AI startup Anthropic, alleging the company committed “large-scale theft” by training its Claude chatbot on pirated copies of copyrighted books.
This is the first lawsuit from writers targeting Anthropic and Claude, but similar lawsuits have been filed against competitor OpenAI and ChatGPT.
The lawsuit accuses Anthropic of using a dataset called The Pile, which includes numerous pirated books.
Anthropic and others, including OpenAI, have argued that training AI models is protected under the “fair use” doctrine of U.S. laws, which permits the limited use of copyrighted materials.
This is not the first time an AI company has been sued over copyright infringement, but it resurfaces an important debate about AI training data. While similar cases have been largely dismissed in the past, courts have yet to definitively address the core issue of using unauthorized internet-scraped material for AI training.
International Data Corporation (IDC)forecasted that worldwide AI spending is expected to reach $632 billion by 2028, with generative AI accounting for 32% of that.
LTX Studio opened to the public and launched five new features, including character animation and dialogue, face motion capture, and generation and keyframe control.
A Daily Chronicle of AI Innovations on August 20th 2024
AGIBOT reveals new humanoid robot family
ChatGPT runs for mayor in Wyoming
Luma Labs launches Dream Machine 1.5
Tesla’s humanoid robot has a new competitor
Waymo now giving 100,000 weekly robotaxi rides
Fortune 500 companies are getting increasingly worried about AI
Anthropic gets sued on allegations of ‘large-scale theft’
Nvidia’s new AI predicts thunderstorms with kilometer-scale precision
Luma Labs launches Dream Machine 1.5
Luma Labs just released Dream Machine 1.5, a major upgrade to their current AI video generation model, with higher quality text-to-video, smarter prompt understanding, and better image-to-video capabilities.
Dream Machine 1.5 builds on the original model’s ability to generate high-quality, realistic 5-second video clips from text and image prompts.
The upgraded model showcases better natural language processing, interpreting and executing prompts at a higher accuracy.
It excels in creating smooth motion, cinematography, and dramatic shots, turning static concepts into dynamic stories, but lags in morphing, movement, and text.
Dream Machine 1.5 is available to try for free here.
With text-to-image AI generation nearly indistinguishable from reality, the next big frontier is text-to-video — and Dream Machine 1.5 is another big leap forward for realism. While AI video still has some catching up to do, expect fast-moving startups like Luma Labs to close that gap for AI video, fast.
Victor Miller, a mayoral candidate in Wyoming’s capital city, just vowed to let his customized ChatGPT GPT named Vic (Virtual Integrated Citizen) help run the local government if elected.
Miller created VIC using ChatGPT, feeding it city ordinances and related documents to make municipal decisions.
Miller filed for him and VIC to run for mayor, proposing that the ChatGPT GPT provides data-driven insights and solutions while Miller ensures legal execution.
OpenAI has shut down Miller’s account twice, citing policies against using its products for campaigning.
Wyoming’s Secretary of State raised concerns, but local officials allowed Miller’s candidacy with his human name on the ballot.
While Miller’s chances of winning seem slim, and his grasp of data privacy and LLMs seem slimmer, this marks the first time a political candidate has openly advocated for AI in governance. Whether Cheyenne, Wyoming is ready for an AI co-pilot in City Hall is debatable, but AI will certainly infiltrate politics in the coming years.
AGIBOT, a China-based robotics startup, just unveiled a family of five advanced humanoid robots, directly challenging Elon Musk and Tesla’s upcoming Optimus bot.
AGIBOT’s five new models are both wheeled and biped humanoid robots specifically designed for diverse tasks — from household chores to industrial operations.
The flagship model, Yuanzheng A2, stands 5’9″ (175cm), weighs 121 lbs (55kg), and can perform delicate tasks like needle threading.
The company aims to start shipping 300 units by the end of 2024, claiming better commercialization and cost-control abilities than Tesla.
Unitree, another high-performance robot manufacturer from China, also showcased its new G1 mass production-ready robot with better functionality and appearance.
The humanoid robotics and AI race between the US and China is intensifying. While it’s been months since Tesla unveiled its Optimus 2 prototype, four Chinese startups, including AGIBOT revealing five new humanoid robots, have showcased major technical progress in just a few days.
Unitree Robotics has launched the production version of its G1 humanoid robot, priced at $16,000, just three months after its initial announcement.
The G1 is 90% cheaper than Unitree’s previous humanoid model, the H1, offering advanced features such as 23 degrees of freedom and a 3D vision system for real-time navigation.
While the G1 is not ready for consumer use, it is envisioned as an affordable platform for research and development, likely appealing to institutions and businesses exploring robotic automation.
Waymo disclosed it is now giving more than 100,000 paid robotaxi rides every week across Los Angeles, San Francisco, and Phoenix, doubling its previously stated figures.
This milestone was shared by Waymo co-CEO Tekedra Mawakana and reflects a significant increase from the over 50,000 weekly rides reported by Alphabet CEO Sundar Pichai earlier this year.
Waymo’s fleet consists of hundreds of fully autonomous Jaguar I-Pace vehicles, with 778 robotaxis deployed in California, and it has recently expanded its service to operate 24/7 in San Francisco and parts of Los Angeles.
Fortune 500 companies are getting increasingly worried about AI
Fortune 500 companies reporting AI as a risk factor saw a surge of 473.5% in the past year, according to a report by Arize AI, with 281 companies now flagging such risks.
Arize AI’s analysis revealed that 56.2% of Fortune 500 companies now include AI risks in their latest annual reports, a substantial jump from the previous year’s 49 companies.
The software and technology sectors lead the mentions of generative AI, while advertising, media, and entertainment industries report the highest percentage, 91.7%, of AI as a risk factor.
Anthropic gets sued on allegations of ‘large-scale theft’
A group of authors has filed a lawsuit against AI startup Anthropic, alleging “large-scale theft” for using pirated copies of copyrighted books to train its chatbot, Claude.
This marks the first lawsuit by writers specifically targeting Anthropic, although similar cases have been brought against OpenAI, the maker of ChatGPT, for the same reasons.
The lawsuit accuses Anthropic, which markets itself as a responsible AI developer, of contradicting its goals by using unauthorized works, and it adds to the increasing legal challenges faced by AI developers.
Nvidia’s new AI predicts thunderstorms with kilometer-scale precision
Nvidia Research has introduced StormCast, a new AI model for high-precision atmospheric dynamics to enhance mesoscale weather prediction, which is critical for disaster preparedness and mitigation.
Integrated into Nvidia’s Earth-2 platform, StormCast provides hourly autoregressive forecasts that are more accurate than current US operational models by 10%, improving early warning systems for severe weather events.
Trained on NOAA climate data, StormCast predicts over 100 weather variables and allows scientists to observe storm evolution in three dimensions, marking significant advancements in AI-driven weather forecasting by Nvidia.
A Daily Chronicle of AI Innovations on August 19th 2024
You can now rent ‘living computers’ made from human neurons
Start-up failures up by 60% as founders face hangover from boom years
AMD is going after Nvidia with a $5 billion acquisition
Tesla will pay you to pretend to be a robot
You can now rent ‘living computers’ made from human neurons
Researchers and companies like FinalSpark are creating computers from lab-grown human brain organoids, which can be rented for $500 a month.
These biocomputers use human neurons to form pathways mimicking human brain learning processes, potentially consuming significantly less energy than current AI technologies.
While challenges remain, such as limited organoid lifespans and lack of standardized manufacturing, FinalSpark and other researchers are exploring various biocomputing approaches, including cellular and fungal computing.
AMD is going after Nvidia with a $5 billion acquisition
AMD is set to buy ZT Systems for $4.9 billion in cash and stock, aiming to strengthen its AI ecosystem and offer better support to companies building large AI computing businesses.
The acquisition will integrate ZT Systems’ computing infrastructure design business into AMD, although AMD plans to sell the data center infrastructure manufacturing arm to a strategic partner.
ZT Systems’ CEO Frank Zhang and President Doug Huang will lead roles within AMD’s Data Center Solutions Business Group, with the deal expected to conclude in the first half of 2025.
Tesla is offering up to $48 per hour for Data Collection Operators to wear motion-capture suits and VR headsets to help train its humanoid Optimus robot.
Workers wearing these suits perform and analyze tasks to gather extensive data, aiding in the robot’s development for various roles, from factory work to caregiving.
Tesla’s initiative involves collecting potentially millions of hours of data, aiming to overcome the challenges of producing versatile robots at scale and ensuring their success in diverse tasks.
Swiss startup FinalSpark just launched a service allowing scientists to rent cloud access to “biocomputers” made of human brain cells for $500 a month, in an effort to create AI that uses 100,000x less energy than current systems.
The system uses organoids (clumps of human brain cells) that can “live” and compute for up to 100 days.
AI models are trained using dopamine for positive reinforcement and electrical signals for negative reinforcement, mimicking natural neural processes.
FinalSpark claims these biocomputers could be up to 100,000 times more efficient for AI training than traditional silicon-based technology.
The organoids and their behaviour are live streamed 24/7, which you can access here.
AI is an energy-hungry industry, and alleviating its dependence on CPUs and GPUs is generally a step in the right direction. That said, using brain organoids for biocomputing is completely uncharted territory and is bound to raise ethical concerns — such as the sci-fi possibility that cell masses somehow achieve consciousness.
California’s SB 1047, an aggressive AI safety bill aimed at preventing AI disasters, just got significantly revised to address concerns raised by AI companies like Anthropic and open-source developers.
The bill no longer allows California’s attorney general to sue AI companies for negligent safety practices before a catastrophic event occurs.
AI labs are now only required to submit public “statements” about their safety practices vs certifications “under penalty of perjury.”
Likewise, developers must now provide “reasonable care” vs “reasonable assurance” that AI models do not pose significant risks.
The bill is headed to California’s Assembly floor for a final vote.
There’s a fine line between advancing technological progress and mitigating potential existential risks that governments are navigating — and California is showing that regulation can be practical and adaptive. These changes are a big step towards fostering responsible AI development through collaborative governance.
Researchers just developed a new technique to find shorter solutions to scrambled Rubik’s Cubes by cleverly analyzing the puzzle’s structure and identifying the best moves more quickly.
The Rubik’s Cube has an enormous number of possible configurations, over 43 quintillion, making it challenging for AI to solve in the fewest moves possible.
Researchers represented the Rubik’s Cube as a complex network or “graph” and used a new technique to pass useful information, like the moves required to solve the puzzle, between connected nodes.
The AI then considers which next moves are most likely to lead to a quick solution, using the probabilities as weights, and focuses on the most promising paths.
When tested, the new technique found solutions to the puzzle faster than current state-of-the-art Rubik’s Cube solving AI systems.
As companies like Sakana build AIs that can completely automate scientific research, it’s important to make sure they’re solving highly complex problems efficiently. This technique, coupled with Sakana’s processes, could be massively beneficial in areas like optimizing supply chains and advanced drug discovery.
Free event: Navigating AI Data Privacy. Join Section CEO Greg Shove to learn how to protect your data, write a team or company AI data policy, and lead your company on safe AI. RSVP here.*Source: https://www.sectionschool.com/events/live-events/ai-data-privacy-in-large-organizations
Claudehttps://x.com/alexalbert__/status/1824483452802175082 a new screenshot capture button, allowing users to easily include images from their screen in prompts.Source: https://x.com/alexalbert__/status/1824483452802175082
Midjourneyreleased a new unified web-based AI image editor with advanced tools for seamlessly modifying and extending generated images.Source: https://venturebeat.com/ai/midjourney-releases-new-unified-ai-image-editor-on-the-web
Rebellions and Sapeon, South Korean AI chip makers, signed a definitive merger agreement to challenge global leaders like Nvidia.Source: https://www.reuters.com/technology/artificial-intelligence/south-korean-ai-chip-makers-rebellions-sapeon-agree-merge-2024-08-18
Bzigo launched Iris, an AI-powered mosquito detector that tracks and marks mosquitoes with a laser pointer for easy swatting.Source: https://www.foxnews.com/tech/ai-technology-can-help-you-win-battle-over-mosquitoes
Coinbasestarted a $15,000 accelerator grant program for projects combining AI with crypto wallets to enable economic participation.Source: https://cointelegraph.com/news/coinbase-ceo-brian-armstrong-ai-should-have-crypto-wallets
Microsoftunveiled PowerToys Workspaces, a new feature to auto-arrange apps, plus an AI-powered copy-paste tool with OpenAI API integration.Source: https://www.theverge.com/2024/8/16/24221639/microsoft-powertoys-workspaces-feature-demo
A Daily Chronicle of AI Innovations on August 16th 2024
AI makes Walmart 100x more productive
SoftBank’s AI chip faces setback
Create a Siri-like voice AI with Llama 3.1
Hermes 3 is the newest open-source model
AI makes Walmart 100x more productive
Walmart’s CEO Doug McMillon just reported that the company is using generative AI to increase its productivity, updating 850 million product catalog entries 100 times faster than human-led methods.
The report came during the company’s Q2 financial earnings call, where McMillon also announced AI improvements to customer search and seller support.
Customers can now use AI-powered search and a new shopping assistant on Walmart’s app and website — it even provides advice for questions like “Which TV is best for watching sports?”.
Walmart is also testing a completely new AI-driven experience for U.S. based marketplace sellers, but the details are not yet available.
McMillon said the company plans to continue experimenting with AI globally across all parts of its business.
Another multibillion dollar company is using AI to increase productivity, but most notably, Walmart is exploring the tech in all areas of its business ops. Whether people should be excited about the endless possibilities ahead or concerned about the relevance of their jobs is a question that’s not going away any time soon.
SoftBank’s ambitious Project Izanagi initiative, aimed at developing AI processors to rival Nvidia, is reportedly facing a major setback after Intel failed to meet volume and speed requirements.
SoftBank had been working with Intel to develop AI processors for Project Izanagi because it lacks in-house chip design expertise, but Intel failed to meet SoftBank’s demands.
In an effort to keep Project Izanagi on track, SoftBank is considering a new partnership with TSMC, the world’s largest chipmaker.
TSMC has its own issues, however, failing to meet its current chipmaking demands, which has stalled the negotiations.
Despite the complications, SoftBank CEO Masayoshi Son remains committed to the company’s ambitious plan and is seeking investments from Saudi Arabia, UAE, and major tech companies.
Nvidia is currently dominating the AI chip space, which propelled the company to its current $3 trillion dollar market capitalization. But with recent delays of Nvidia’s next-gen Blackwell AI chip, it could be time for competitors to strike.
Nous Research just released Hermes 3, a new open-source model with significant improvements in roleplaying, agentic tasks, function calling, multi-turn chats, and long context coherence.
Hermes 3 is available in three sizes (8B, 70B, and 405B) with the 405B parameter model achieving state-of-the-art performance relative to other open models.
The model is instruct tuned, or trained, to faithfully respond to user requests and closely follow provided system prompts, unlike base or foundation models.
It achieves similar or better performance to Meta’s Llama-3.1 405B in judgement, reward modeling, interpretable problem-solving, code generation, and tool use.
Hermes 3 is available now for free via Lambda Chat or in the Nous Research Discord server.
Meta has been the leader in open-source AI for a while, but companies like Nous Research and Mistral are catching up with their latest Hermes 3 and Large 2 models. And the more free, customizable and state-of-the-art AIs available to the public, the more transparency the world has.
Elon Muskrevealed that xAI is developing an in-house image generation system to replace the current Flux model in Grok 2 but it’s currently months away from release.
The U.S. Consumer Financial Protection Bureauhighlighted risks of AI in finance, saying existing laws apply and innovation requires consistent regulatory treatment.
Apptronik, an automation company that makes humanoid robots, recently reported that the company is preparing for a commercial launch by the end of 2025.
A Daily Chronicle of AI Innovations on August 15th 2024
Apple’s iPad is getting a robotic arm
Google’s Imagen 3 tops Midjourney, DALL-E
Apple’s next big thing is a $1000 home robot
Grok-2 reaches state-of-the-art status
Creating sound effects with text
X’s AI image generator allows users to create uncensored images
Ex-Google CEO says successful AI startups can steal IP and hire lawyers to ‘clean up the mess’
FTC finalizes rule banning fake reviews, including those made with AI
Apple’s next big thing is a $1000 home robot
Apple is reportedly working on a new smart home project featuring an iPad attached to a robotic arm that can twist and rotate, designed as a home “command center” with AI capabilities.
The initiative, backed by CEO Tim Cook and head of hardware engineering John Ternus, has involved hundreds of staff and follows the cancelled Apple-brand electric car project.
According to Bloomberg, the device is expected to be released around 2026 or 2027, potentially costing about $1,000, and will use a modified version of iPadOS.
xAI’s newest AI model, Grok-2, is now available in beta for users on the X platform — achieving state-of-the-art status and outperforming versions of Anthropic’s Claude and OpenAI’s GPT-4.
In addition to Grok-2, Grok-2 mini is also now available to users on the X platform in beta with an enterprise API release planned for later this month.
Both Grok-2 and Grok-2 mini show significant improvements in reasoning with retrieved content, tool use capabilities, and performance across all academic benchmarks.
Grok-2 can now create and publish images directly on the X platform, powered by Black Forest Lab’s Flux 1 AI model.
Grok-2 surpasses OpenAI’s latest GPT-4o and Anthropic’s Claude 3.5 Sonnet in some categories, making it one of the best models currently available to the public if based purely on benchmarks.
Grok-1 debuted as a niche, no-filter chatbot, but Grok-2’s newly achieved state-of-the-art status has catapulted xAI into a legitimate competitor in the AI race. The startup is looking to have a bright future with its new Supercluster, Elon’s ability to attract talent, and vast amounts of real-time training data available on X.
Apple is reportedly ramping up development on a high-end tabletop smart home device with a robotic arm, an iPad-like display, and Siri voice command to operate its AI features.
The project, codenamed J595, reportedly involves a team of several hundred people and could launch as early as 2026 or 2027.
The device combines an iPad-like display with a thin robotic arm that can tilt, spin 360 degrees, and move the screen around.
It is expected to run a modified version of iPadOS making it a familiar smart home command center, videoconferencing tool, and remote-controlled home security device.
Apple is targeting a price point of around $1,000 for the product.
Apple is doubling down on its commitment to artificial intelligence by ramping up the development of a strange new Siri-powered, countertop robotic arm. With Apple Intelligence launching later this year, the tech giant seemingly has big plans for implementing AI into its hardware.
X’s AI image generator allows users to create uncensored images
X’s new AI image generator, Grok, allows users to create and share highly controversial images, including those of public figures in inappropriate scenarios, raising concerns about the lack of content moderation.
Despite claiming to have restrictions, Grok often generates offensive or misleading images, with many users easily bypassing its few safeguards, leading to further scrutiny from regulators.
The chaotic rollout of Grok’s image generation feature aligns with Elon Musk’s relaxed approach to content moderation, potentially driving away advertisers and inviting regulatory action.
ElevenLabs now offers a text-to-sound feature that allows users to generate sound effects by writing a simple description of the noise they want.
Visit ElevenLabs and log in or create an account. You can try this feature for free.
Select “Sound Effects” from the left sidebar.
Describe your desired sound effect in the text box.
Adjust settings for duration and prompt influence.
Click “Generate Sound Effects” to create your sounds.
Source: https://elevenlabs.io/
Google’s Imagen 3 tops Midjourney, DALL-E
Google DeepMind recently published the paper for it’s new state-of-the-art AI image generation model, Imagen 3, flexing that it beat DALL-E 3, Midjourney v6, and Stable Diffusion 3 in human performance evaluations.
The human evaluations asked participants to rank their preferred models for overall quality and adherence to detailed prompts.
Imagen 3 excelled particularly in generating high-quality, realistic images that closely match long and complex text descriptions.
Despite its capability to accurately generate photorealistic images, it struggles with certain tasks requiring numerical reasoning, understanding scale, and depicting actions.
Ex-Google CEO says successful AI startups can steal IP and hire lawyers to ‘clean up the mess’
Former Google CEO Eric Schmidt suggested that successful AI startups can initially steal intellectual property and later hire lawyers to resolve legal issues if their product gains traction.
Schmidt used a hypothetical example of copying TikTok to illustrate how Silicon Valley entrepreneurs might prioritize rapid growth over legal considerations.
Schmidt’s comments, made during a talk at Stanford, were later removed from the university’s YouTube channel after drawing media attention.
FTC finalizes rule banning fake reviews, including those made with AI
The FTC has introduced a final rule prohibiting companies from producing or selling fake reviews, including AI-generated ones, and can now penalize companies that ignore the regulation.
The rule targets deceptive practices such as incentivizing feedback, undisclosed insider reviews, company-controlled review sites, intimidation to remove negative feedback, and the trade of fake followers or views.
Although the FTC first proposed the fake review ban last year, there are concerns about enforcing it on global marketplaces like Amazon, where numerous fraudulent reviews come from businesses outside the U.S.
Free eBook: The AI Proficiency Report from Section. 7% of the workforce is getting all the benefits of AI. Download the report to see what they do differently.*
A Daily Chronicle of AI Innovations on August 14th 2024
Google beats OpenAI in voice mode race
OpenAI redesigns coding benchmark
Bring images to life with Kling AI
Become a tennis pro with AI
Android phones get an AI upgrade
xAI releases Grok-2, adds image generation on X
New ‘AI Scientist’ conducts research autonomously
Android phones get an AI upgrade
Google is replacing Google Assistant with its new AI model, Gemini, on Android phones, introducing generative AI capabilities like automating calendar invites and creating playlists based on user input.
Gemini will operate through cloud-based services, allowing for advanced AI processing, while Apple plans to run its AI models directly on devices for better privacy and latency.
The introduction of Gemini marks a significant shift in smartphone functionality, offering the potential to automate day-to-day tasks, but there are risks of errors as AI assistants become more integrated into daily life.
Google just launched Gemini Live, a mobile conversational AI with advanced voice capabilities, while OpenAI’s ChatGPT voice mode remains in its “limited alpha phase” and is not yet available to everyone.
Gemini Live, Google’s answer to OpenAI’s Advanced Voice Mode, is capable of “in-depth“ hands-free conversations and has 10 different human-like voice options.
Users can interrupt and ask follow-up questions mid-response, mimicking natural conversation flow — however Gemini Live’s ability to see and respond to your camera view is planned later this year.
Similar to Apple’s upcoming Intelligence features, Gemini integrates directly with Google to provide context-aware answers without switching apps.
Gemini Live is now the default assistant on Google’s Pixel 9 and is available today to all Gemini Advanced subscribers on Android (coming to iOS soon).
Real-time voice is slowly shifting AI from a tool we text/prompt with, to an intelligence that we collaborate, learn, consult, and grow with. As the world’s anticipation for OpenAI’s unreleased products grows, Google has swooped in to steal the spotlight as the first to lead widespread advanced AI voice rollouts.
xAI has launched upgraded Grok-2 and Grok-2 mini chatbots with new image-generation capabilities, which are powered by Black Forest Lab’s Flux 1 AI model and allow users to publish images to X with few restrictions.
Both Grok-2 models are currently in beta, available to Premium and Premium Plus subscribers on X, and will be accessible via xAI’s enterprise API later this month.
Early examples of Grok-generated images, depicting figures like Donald Trump and Barack Obama, indicate minimal content restrictions, raising concerns about the spread of false information on the platform.
OpenAI and the authors of SWE-bench collaborated to redesign the popular software engineering benchmark and release ‘SWE-bench Verified’, a human-validated subset of the original benchmark.
SWE-bench Verified addresses issues in the original benchmark, such as overly specific unit tests and unreliable development environments that leads to incorrect assessments of AI performance.
The new subset includes 500 samples verified by human professional software developers to make evaluating models on SWE-bench easier and more reliable.
On SWE-bench Verified, GPT-4o figures out 33.2% of samples, and the best open-source scaffold, Agentless, doubles its previous score to 16%.
The leaderboard for SWE-bench Verified does not include Cosine’s Genie we wrote about yesterday, which shattered the high score on the old benchmark by over 10%.
Accurate benchmarking of AI in human-level tasks like coding is crucial for transparency and assessing AI risk. However, OpenAI’s collab with SWE-bench is a double-edged sword — while it improves the benchmark, it also raises questions about potential conflicts of interest, especially with ‘Project Strawberry’ rumors heating up.
Tokyo-based R&D company Sakana AI introduced “The AI Scientist,” an AI designed to fully automate research, claiming it’s the first system of its kind to independently handle numerous scientific tasks.
The AI Scientist generates innovative research ideas, conducts experiments, writes code, and produces scientific papers while using a simulated review process to evaluate its own findings, mimicking human scientific collaboration.
A rival AI startup, Omniscience, contested Sakana AI’s originality, asserting their AI model, Omni, was released months earlier and offers similar capabilities for aiding users in scientific writing and research tasks.
Kling AI’s new image-to-video feature allows users to take static images, and turn them into dynamic videos, offering a new dimension to the AI video generator’s character consistency.
Click “AI Videos” on the dashboard, then select “Image to Video” on the top bar.
Upload your chosen image and write a prompt describing how you want the image animated.
Hit “Generate” and watch your image come to life!
Source: https://klingai.com/
Become a tennis pro with AI
Researchers just created Match Point AI, a groundbreaking tennis simulation that pits AI agents against virtual pros, giving players data-driven tennis strategies and tools to help improve their game.
Match Point AI realistically models the complexities and uncertainties of real tennis, allowing AI to test new strategies in virtual games.
Early experiments show the AI rediscovering time-tested tennis strategies, like making opponents run, validating the framework’s ability to understand the sport.
By watching Match Point’s AI agents that mimic tennis legends like Novak Djokovic, players can learn the perfect strategies to optimize their game quickly and efficiently.
AI has long been trained to compete in games, but researchers usually focus on board and video games with straightforward mechanics. Match Point AI learns to make decisions in a real-world, complex sport, similar to how Google’s newest AI robot can play ping pong against intermediate players.
What else is happening in AI on August 14th 2024!
Google unveiled Pixel Buds Pro 2 with a custom Tensor A1 chip, enhanced noise cancellation, and Gemini AI integration.
A Daily Chronicle of AI Innovations on August 13th 2024
New AI can diagnose stroke via tongue color
Sakana reveals an autonomous AI scientist
New AI model sparks rumors about OpenAI’s Q* New AI model can listen while speaking Gemini 1.5 Flash cuts usage fees by 78% OpenAI releases GPT-4o System Card, revealing safety measures SingularityNet’s supercomputer network: A step closer to AGI
New AI model sparks rumors about OpenAI’s Q*
A mysterious new AI model has appeared in the LMSYS Chatbot Arena, sparking rumors that it could be OpenAI’s highly anticipated Q* AI breakthrough or its evolution, codenamed ‘Strawberry.’
Testers report that this “anonymous-chatbot” displays more advanced reasoning capabilities than the current state-of-the-art GPT-4o model. To add to the speculation, OpenAI CEO Sam Altman has tweeted a picture of a strawberry, which is believed to be the codename for OpenAI’s secret new AI model.
Why does it matter?
If this mystery model is indeed Q*, it could represent another significant leap forward in AI capabilities as OpenAI’s competitors like Anthropic and Meta start to catch up to GPT-4o. This could be a massive paradigm shift that could significantly reshape the landscape of AI.
Tokyo-based Sakana AI just introduced “The AI Scientist,” the world’s first AI system capable of autonomously conducting scientific research — potentially revolutionizing the scientific process.
The system generates new research ideas, writes code, runs experiments, writes papers, and performs its own peer review with near-human accuracy.
Sakana AI envisions a future where we won’t just see an autonomous AI researcher but also autonomous reviewers, area chairs, and entire conferences.
The AI Scientist has already produced papers with novel contributions in machine learning domains like language modeling and diffusion models.
Each paper only costs approximately $15 to produce, which could potentially democratize research capabilities.
This breakthrough could dramatically accelerate scientific progress by allowing researchers to collaborate with AI agents and automate time-consuming tasks. We’re entering a new era where academia could soon be powered by a tireless community of AI agents, working round-the-clock on any problem they’re directed to.
Cosine just showed off Genie, its new fully autonomous AI software engineer that broke the high score on a benchmark for evaluating the coding abilities of large language models (LLMs), by over 10%.
Cosine trained Genie on a dataset that emulates how human software engineers actually work from incremental knowledge discovery to step-by-step decision making.
When it makes a mistake, Genie iterates, re-plans, and re-executes until it fixes the problem, something that foundational models struggle with.
Genie scored 30.08% on SWE-Bench, a 57% improvement over previous top performers like Amazon’s Q and Code Factory at 19% (GPT-4 scores 1.31%).
The waitlist is currently open, but Genie has not yet been released to the general public.
Cosine completely rethinks the way that AI is trained, teaching it to be more human-like during its training rather than focusing on post-training prompt design — and it works! With its recent SWE-Bench success, more companies are likely to adopt the process and build smarter AIs, a win-win for everyone.
Researchers have developed a new Listening-While-Speaking Language Model (LSLM) that can listen and speak simultaneously. This allows for more natural and responsive conversations with AI systems. The LSLM uses a token-based decoder-only text-to-speech model for speech generation and a streaming self-supervised learning encoder for real-time audio input.
This enables the model to detect turn-taking and respond to interruptions, a key feature of natural conversation. In addition, the LSLM has demonstrated robustness to noise and sensitivity to diverse instructions in experiments.
Why does it matter?
While OpenAI’s advanced voice mode for ChatGPT pushes us towards realistic AI conversations, LSLM takes that to the next level, where it could revolutionize human-AI interactions, making conversations with machines feel natural and responsive.
Google has announced significant updates and improvements to its Gemini API and Google AI Studio. The biggest news is a significant reduction in the usage fees for Gemini 1.5 Flash. The input token costs have decreased by 78% to $0.075 per 1 million tokens, and the output token costs have decreased by 71% to $0.3 per 1 million.
This makes Gemini 1.5 Flash a popular and affordable summarization and multi-modal understanding model. Google has also completed the Gemini 1.5 Flash tuning rollout, allowing developers to customize the base model and improve its performance.
Why does it matter?
The extended language support, model tuning options, and improvements to the Gemini API will enable more developers and researchers to build innovative AI-powered products and services using advanced NLP capabilities.
SingularityNet’s supercomputer network: A step closer to AGI
SingularityNET is launching a network of powerful supercomputers to accelerate the development of AGI. The first of these supercomputers is expected to come online in Sep 2024. The network will use cutting-edge hardware like Nvidia GPUs and AMD processors to create a “multi-level cognitive computing network” for hosting and training complex AGI systems.
The company uses an open-source software framework called OpenCog Hyperon to manage the distributed computing power. Users will access the network through a tokenized system, allowing them to contribute data and test AGI concepts.
Why does it matter?
Major AI companies such as OpenAI, Anthropic, and Google currently dominate the race to AGI development. However, SingularityNET’s novel decentralized approach could disrupt this, democratizing AI research for a broader range of contributors and innovators.
An AI developed by researchers at Middle Technical University and the University of South Australia can diagnose stroke by analyzing the color of a person’s tongue.
The advanced algorithm, which boasts a 98% accuracy rate, can also detect conditions such as anaemia, asthma, diabetes, liver, and gallbladder issues, COVID-19, and various gastrointestinal diseases.
This innovative system uses tongue color analysis, an ancient technique from traditional Chinese medicine, and could potentially be adapted for use with smartphones for real-time health assessments.
Reddit is testing AI-powered search result pages that provide summaries and recommendations to help users “dig deep” into content and discover new communities.
According to leaked documents, Nvidia has been scraping video content from sources like YouTube and Netflix to train its AI models for its upcoming Cosmos project.
Automattic has launched a newtool called “Write Brief with AI.” This helps WordPress bloggers write concisely and improve the readability of their content.
Anthropic is expanding its safety bug bounty program to focus on finding flaws in its AI safeguarding systems. The company is offering bounty rewards of up to $15,000.
OpenAI allows free ChatGPT users to generate up to two images per day using its DALL-E 3 model. This was previously available only to ChatGPT Plus subscribers.
Google Researchers developed a robot to play competitive table tennis at an amateur human level. It can also adapt its game to play vs. unseen human opponents.
Alibaba has released a new LLM called Qwen2-Math that scored 84% on the MATH Benchmark, surpassing OpenAI’s GPT-4o and other leading math-focused AI models.
Google Meet is rolling out a new AI-powered feature, “Take notes for me,” which can automatically take notes during video calls,boosting productivity and efficiency.
A Daily Chronicle of AI Innovations on August 12th 2024
AI search is gaining momentum
ChatGPT unexpectedly began speaking in a user’s cloned voice during testing
Meta and UMG struck an agreement to ‘protect’ artists from AI
Google Meet adds new note-taking AI
FCC cracks down on AI voice calls
Google Meet adds new note-taking AI
Google is rolling out a new “Take notes for me” feature powered by its Gemini AI for it’s Google Meet feature, allowing users to focus on the meeting while the AI automatically captures key points.
The AI-powered tool will automatically take notes during Google Meet calls, reducing the need for manual note-taking.
The feature is powered by Google’s Gemini AI and will be available to Workspace customers with specific add-ons.
“Take notes for me” is part of the AI Meetings and Messaging add-on, which costs $10 per user/month across most Google Workspace plans.
Admins can configure the feature’s availability through the Google Workspace Admin console.
Taking notes during meetings will soon be a thing from our prehistoric, non-AI past — with Google pushing for a more practical, AI-assisted future of work. Alongside this, the tech giant is directly competing against smaller AI startups such as Otter AI and Fireflies who’ve thrived by selling a nearly identical features to users.
The U.S. Federal Communications Commission (FCC) just proposed new regulations requiring AI-generated voice calls to disclose the use of artificial intelligence.
The proposal aims to combat the rise of AI-generated voices in unwanted and potentially fraudulent ‘robocalls’.
AI voices would be required to explicitly state they are artificial at the beginning of calls.
The FCC is also exploring tools to alert people when they receive AI-generated calls and texts, including enhanced call filters, AI-based detection algorithms, and improved caller ID flagging.
As AI voices become indistinguishable from human speech, these regulations are crucial in combating highly targeted scams. But with enforcement likely to be a cat-and-mouse game against scammers, the best defence is education—especially for those most vulnerable to AI deception.
Perplexity’s AI search engine experienced substantial growth, answering 250 million queries last month, signaling a rising demand for AI-driven search technologies. In contrast, 500 million queries were processed throughout 2023, Shevelenko told the Financial Times
Despite this growth, Perplexity remains significantly behind Google, which dominates the market with over 90 percent share and processes around 8.5 billion queries daily.
The rise of AI in search, exemplified by Perplexity and other players, suggests a potential shift in user behavior and challenges to the traditional search engine business models.
ChatGPT unexpectedly began speaking in a user’s cloned voice during testing
During testing, ChatGPT’s Advanced Voice Mode accidentally mimicked users’ voices without their consent, as highlighted in OpenAI’s new GPT-4o system card released on Thursday.
OpenAI has implemented safeguards to prevent unauthorized voice imitation, although rare episodes during testing showcased the model’s ability to unintentionally generate user-like voices.
The GPT-4o AI model can synthesize almost any sound, and OpenAI directs this capability by using authorized voice samples and employing an output classifier to ensure only selected voices are generated.
Meta and UMG struck an agreement to ‘protect’ artists from AI
Meta and Universal Music Group (UMG) updated their licensing agreements to extend UMG’s content use across more Meta platforms, now including Threads and WhatsApp alongside Facebook, Instagram, Messenger, and Meta Horizon.
This multiyear agreement aims to explore new collaboration opportunities on WhatsApp and other Meta platforms, addressing issues like unauthorized AI-generated content that could impact artists and songwriters.
Meta’s collaboration with UMG dates back to 2017, allowing users to use UMG music in content and addressing copyright issues, a challenge shared by TikTok in its recent dealings with UMG.
Delphi unveiled an AI clone feature that creates lifelike digital replicas of individuals, demonstrating its capabilities in a TV interview on FOX Business.
A Daily Chronicle of AI Innovations on August 09th 2024
OpenAI fears users will become emotionally dependent on its ChatGPT voice mode
Google’s new robot can play table tennis like humans
GPT-4 tackles top-secret tasks
AI speeds up schizophrenia cure
OpenAI fears users will become emotionally dependent on its ChatGPT voice mode
OpenAI is concerned that users may become emotionally dependent on ChatGPT due to its new, human-sounding voice mode, which could affect relationships and social interactions.
The company observed users expressing shared bonds with ChatGPT’s voice mode, raising fears that prolonged use could reduce the need for human interaction and lead to unhealthy trust in AI-supplied information.
OpenAI plans to continue studying the potential for emotional reliance on its tools and aims to navigate the ethical and social implications responsibly while ensuring AI safety.
Google’s new robot can play table tennis like humans
Google’s DeepMind team has developed a table tennis robot that performs at a “solidly amateur” human level, successfully competing against beginner and intermediate players while struggling against advanced ones.
During testing, the robot achieved a 55% win rate against intermediate players, winning 45% of the 29 games it played in total, but it failed to win any matches against advanced players.
DeepMind identifies the robot’s main weaknesses as reacting to fast balls and dealing with system latency, suggesting improvements like advanced control algorithms and predictive models for better performance.
Researchers at Uppsala University recently used AI to accurately predict 3D structures of receptors linked to schizophrenia and depression treatments and speed up possible treatment strategies.
The AI model predicted the structure of TAAR1, a receptor linked to schizophrenia and depression treatments.
Then, supercomputers screened millions of molecules to find those fitting the AI-generated model.
Experimental testing confirmed many AI-predicted molecules activated TAAR1, and one potent molecule showed promising positive effects in animal experiments.
Researchers reported on a new model that can predict major diseases early enough to treat them, and now AI is working on curing schizophrenia and depression. As the tech continues to improve, we’re going to see a complete transformation in healthcare that will likely save millions, if not billions, of lives.
Microsoft and Palantir just partnered to deliver advanced AI, including GPT-4, and analytics capabilities to U.S. Defense and Intelligence agencies through classified cloud environments.
The partnership integrates Palantir’s AI Platforms with Microsoft’s Azure OpenAI Service in classified clouds.
The aim is to safely and securely enable AI-driven operational workloads across defense and intelligence sectors.
OpenAI’s models, including GPT-4, will be leveraged by the U.S. government to develop innovations for national security missions.
AI being trusted with classified documents is a big leap in its acceptance as a useful tool for humanity. However, it does feel a bit unsettling knowing that OpenAI’s models are being used at the government level, with the safety team completely dissolving last month and the still uncovered mysteries sorrounding Q*.
Galileo*: Our latest LLM Hallucination Index ranks 22 of the leading models on their performance across 3 different RAG tasks, evaluating the correctness of their responses and propensity to hallucinate.Read the report
A Daily Chronicle of AI Innovations on August 08th 2024
Humane’s AI Pin daily returns are outpacing sales
Sam Altman teases ‘Project Strawberry‘
AI breakthrough accurately predicts diseases
OpenAI bets $60M on webcams
Humane’s AI Pin daily returns are outpacing sales
Humane has faced considerable challenges with the AI Pin, seeing more returns than purchases between May and August, with current customer holdings near 7,000 units.
The AI Pin received negative reviews at launch, leading to efforts by Humane to stabilize operations and look for potential buyers or additional funding from investors.
Humane’s total sales of the AI Pin and accessories have only reached $9 million, which is significantly lower than the $200 million investment from prominent Silicon Valley executives.
OpenAI is reportedly leading a $60 million Series B funding round for Opal, a company known for high-end webcams, with plans to develop AI-powered consumer devices.
Opal plans to expand beyond high-end webcams and develop creative tools powered by OpenAI’s AI models.
The startup will work closely with OpenAI researchers to prototype various device ideas.
OpenAI executives are reportedly most interested in integrating their new voice AI models into Opal’s devices.
OpenAI’s $60 million bet on Opal and Sam Altman’s personal investments in AI hardware startups signals a major push from the AI giant to bring advanced AI from the cloud directly into users’ hands.
A new unknown AI model has appeared in the LMSYS Chatbot Arena, igniting rumors that it could be OpenAI’s highly anticipated Q* AI breakthrough or its evolution — codenamed ‘Strawberry’.
A new ‘anonymous-chatbot’ appeared in the LMSYS Chatbot Arena — an open-source platform where AI startups often test upcoming releases.
Previously, OpenAI tested GPT-4o with gpt2-chatbot two weeks before releasing it to the public, which put the arena on high alert for new AI models.
Testers of “anonymous-chatbot” report that it shows more advanced reasoning than GPT-4o and any other frontier model.
To add fuel to the speculation, Sam Altman tweeted a picture of a Strawberry on X, which is the codename of OpenAI’s reported secret AI model.
As competitors like Anthropic and Meta start to catch up to GPT-4o, the Internet has been eagerly awaiting OpenAI’s next move. If this mystery model is indeed Q*/Strawberry, then we could be on the cusp of another seismic shift in AI capabilities.
Researchers have just developed an AI model that can predict major diseases like heart conditions, diabetes, and cancer — significantly outperforming existing methods.
The new model analyzes patient data using statistics and deep learning to spot disease indicators more accurately.
It employs a smart algorithm (SEV-EB) to identify crucial health markers, helping doctors prioritize the most relevant patient information.
This achieves 95% accuracy in predicting specific diseases like coronary artery disease, type 2 diabetes, and breast cancer.
It also leverages patients’ digital health records for personalized risk assessment and earlier healthcare interventions.
Remember when AlphaFold cracked the protein folding problem? This could be healthcare’s next big AI moment. By significantly improving disease prediction accuracy, this model could transform early diagnosis and treatment planning to help save millions of lives across the globe
Intel reportedly declined an opportunity to invest in OpenAI in 2017, missing early entry into the AI market due to doubts about AI’s near-term potential.
A Daily Chronicle of AI Innovations on August 07th 2024
Reddit to test AI-powered search result pages
Robot dentist performs first automated procedure
AI robot helps assemble a BMW
New AI can listen while speaking
Reddit to test AI-powered search result pages
Reddit CEO Steve Huffman announced plans to test AI-powered search results later this year, aiming to help users explore products, shows, games, and new communities on the platform.
Huffman indicated that the company might explore monetizing through paywalled subreddits, which could offer exclusive content or private areas while still maintaining the traditional free version of Reddit.
As Reddit seeks to diversify revenue sources, Huffman emphasized that the company has blocked certain entities from accessing Reddit content to ensure transparency and protect user privacy.
A Boston-based tech company, backed by Mark Zuckerberg’s dentist father, completed the world’s first all-robotic dental procedure, marking a significant advancement in medical technology.
The robot, operated by Perceptive, independently performed a process called “cutting,” which involves drilling into and shaving down a tooth, demonstrating its capabilities in Barranquilla, Colombia.
This breakthrough aims to use autonomous machines for procedures like crown placements in as little as 15 minutes, enhancing precision, efficiency, and patient care.
OpenAI-backed startup Figure AI just showed off Figure 02, its next-generation AI-powered humanoid robot — capable of completely autonomous work in complex environments like a BMW factory.
Figure 02 uses OpenAI’s AI models for speech-to-speech reasoning, allowing the humanoid robot to have full conversations with humans.
A Vision Language Model (VLM) enables the robot to make quick, common-sense decisions based on visual input and self-correct errors.
Six RGB cameras provide the robot with 360-degree vision to help it navigate the real world.
The robot stands 5’6″and weighs 132 lbs, with a 44 lb lifting capacity and a 20-hour runtime thanks to a custom 2.25 KWh battery pack.
The humanoid robot race is intensifying, withFigure CEO Brett Adcock claiming that Figure 02 is now the “most advanced humanoid on the planet” — a direct challenge toward Elon Musk and Tesla Optimus. While the world now waits for Elon’s response, Figure has one ace up its sleeve: its OpenAI partnership.
ByteDance, the parent company of TikTok, just launched Jimeng AI for Chinese users, a text-to-video AI app that directly competes with OpenAI’s (unreleased) Sora AI video model.
Jimeng AI is available on the Apple App Store and Android for Chinese users.
ByteDance’s entry into the AI video generation market follows similar launches by other Chinese tech firms, including Kuaishou’s Kling AI.
The subscription, priced at 79 yuan ($11) monthly or 659 yuan ($92) annually allows for the creation of ~2,050 images or 168 AI videos per month.
Unlike OpenAI’s Sora, which isn’t yet publicly available, these models by Jimeng AI are already accessible to users (in China).
China’s AI video generation race is accelerating, with Kling AI’s public release just weeks ago and now ByteDance’s Jimeng AI launching while the world anxiously waits for Sora’s public release. With Jimeng AI being backed by TikTok, it will have plenty of training data and deep pockets to compete against other AI giants.
AI researchers just developed a new Listening-While-Speaking Language Model (LSLM) that can listen and speak simultaneously — advancing real-time, interactive speech-based AI conversations.
The new model, called the Listening-while-Speaking Language Model (LSLM), enables full-duplex modeling in interactive speech-language models.
LSLM uses a token-based decoder-only TTS for speech generation and a streaming self-supervised learning encoder for real-time audio input.
The system can detect turn-taking in real-time and respond to interruptions, a key feature of natural conversation.
The model demonstrated robustness to noise and sensitivity to diverse instructions in experiments.
While OpenAI’s recent Her-like advanced voice mode for ChatGPT inches us toward realistic AI conversations, LSLM leaps even further by enabling AI to process incoming speech WHILE talking. This could revolutionize human-AI interactions — making conversations with machines feel truly natural and responsive.
Reddit announced plans to test AI-generated summaries at the top of search result pages, using a combination of first-party and third-party technology to enhance content discovery.
A Daily Chronicle of AI Innovations on August 06th 2024
Figure unveils new sleeker and smarter humanoid robot
Nvidia used ‘a lifetime’ of videos everyday to train AI
Leaked code reveals Apple Intelligence’s plan to prevent hallucinations
Nvidia trains video model ‘Cosmos’
OpenAI co-founder leaves for Anthropic
Nvidia AI powers robots with Apple Vision Pro OpenAI has a secretive tool to detect AI-generated text Tesla’s AI gives robots human-like vision Nvidia delays new AI chip launch Google’s Gemini 1.5 Pro leads AI chatbot rankings AI turns brain cancer cells into immune cells
Nvidia AI powers robots with Apple Vision Pro
Nvidia introduced a new tool suite for developers to control and monitor robots using Apple’s Vision Pro headset. The MimicGen NIM microservice translates user movements captured by the Vision Pro into robot actions, enabling intuitive control of robotic limbs.
Additionally, Nvidia’s Isaac Sim can generate synthetic datasets from these captured movements, which reduces the time and cost of collecting real-world data for robot training.
Why does it matter?
This advancement is a practical application of teleoperation. It can lead to more intuitive and effective ways for humans to interact with and control robots and improve their usability in various fields such as manufacturing, healthcare, and service industries.
Leaked documents obtained by 404 media report Nvidia has been scraping millions of videos daily from YouTube, Netflix, and other sources to train its unreleased foundational AI model.
Nvidia’s project, codenamed Cosmos, aims to process “a human lifetime visual experience worth of training data per day.”
The company used open-source tools and virtual machines to download videos, including full-length movies and TV shows.
Employees raised concerns about copyright and ethics, but were told there was “umbrella approval” from executives.
Nvidia claims its practices are “in full compliance with the letter and spirit of copyright law.”
Project Cosmos appears to be Nvidia’s big move into video-based AI, which could revolutionize everything from 3D world generation to self-driving cars, digital humans, and more. However, this harsh introduction is not a good look for the company, especially as the industry’s practices are coming under intense scrutiny.
OpenAI has a secretive tool to detect AI-generated text
OpenAI has been sitting on a tool that can detect AI-assisted cheating for nearly a year. Using an invisible watermarking technique, the company has developed a tool that can detect ChatGPT-generated text with 99.9% accuracy. However, internal debates about user retention, potential bias, and distribution methods have kept this technology under wraps.
Meanwhile, educators are desperately seeking ways to detect AI misuse in schools. A recent survey found that 59% of middle- and high-school teachers were confident some students had used AI for schoolwork, up 17 points from the previous year.
Why does it matter?
This tool could preserve the value of original thought in education. However, OpenAI’s hesitation shows there are complex ethical considerations about AI detection and unintended consequences in language communities.
Three key leaders at OpenAI are departing or taking leave, including co-founder John Schulman, co-founder Greg Brockman, and Peter Deng — another major shakeup for the AI powerhouse.
John Schulman, co-founder and a key leader at OpenAI, has left to join rival AI startup Anthropic — one of OpenAI’s biggest competitors.
Greg Brockman, OpenAI’s president and co-founder, is taking an extended leave of absence until the end of the year.
Peter Deng, a product leader who joined last year from Meta, has reportedly also departed.
These moves follow other recent high-profile exits, including co-founders Ilya Sutskever and Andrej Karpathy.
OpenAI has struggled to regain its footing after Sam Altman’s departure and eventual return as CEO in November 2023. Brockman, one of Altman’s biggest supporters during the ousting, mysteriously takes a leave of absence at a crucial time as OpenAI sees increased competition from Anthropic and Meta AI.
Tesla’s latest patent introduces a vision system for autonomous robots, particularly its humanoid robot Optimus. The end-to-end AI model uses only camera inputs to create a detailed 3D understanding of the environment, without using expensive sensors like LiDAR.
By dividing the space into voxels (3D pixels), the system can predict each spatial unit’s occupancy, shape, semantics, and motion in real-time. It has already been implemented, with Tesla’s manufacturing team training and deploying the neural network in Optimus for tasks like picking up battery cells on a conveyor belt.
Why does it matter?
The development of such AI-driven perception technologies could lead to progress in autonomous systems for more sophisticated and reliable operations.
The Information reports that design flaws could delay the launch of Nvidia’s next-gen AI chips by three months or more. This setback could affect giants like Microsoft, Google, and Meta, who have collectively placed orders worth tens of billions of dollars for these chips.
Despite the rumored delay, Nvidia maintains that production of its new Blackwell chip series is on track. The company also reports strong demand for its Hopper chips and says a broad sampling of Blackwell has already begun. However, sources claim that Microsoft and another major cloud provider were informed of production delays just this week.
Why does it matter?
A slowdown in chip availability could hamper the development and deployment of new AI technologies, affecting everything from cloud services to generative AI applications. It also highlights the delicate balance and vulnerabilities in the AI supply chain.
Google has launched Gemini 1.5 Pro, an experimental version available for early testing. It quickly claimed the top spot on the LMSYS Chatbot Arena leaderboard, outperforming OpenAI’s GPT-4o and Anthropic’s Claude-3.5 Sonnet. With an impressive Elo score of 1300, Gemini 1.5 Pro excels in multilingual tasks, technical areas, and multimodal capabilities.
The model builds on the foundation of Gemini 1.5, boasting a massive context window of up to two million tokens.
Why does it matter?
Google’s decision to make the model available for early testing reflects a growing trend of open development and community engagement in the AI industry. The company’s focus on community feedback also reflects its move toward responsible AI development.
Researchers at the Keck School of Medicine of USC used AI to reprogram glioblastoma cells into cancer-fighting dendritic cells. It increased survival chances by up to 75% in mouse models of glioblastoma, the deadliest form of brain cancer in adults. The technique cleverly bypasses the blood-brain barrier by converting cancer cells within the tumor itself, a major hurdle in traditional glioblastoma treatments.
The approach greatly improved survival rates in animal models when combined with existing treatments like immune checkpoint therapy or DC vaccines. The research team aims to begin clinical trials in patients within the next few years
Why does it matter?
The technique offers new hope for patients facing this aggressive disease. Moreover, the approach’s application to other cancer types suggests a broader impact on cancer immunotherapy, transforming how we approach cancer treatment in the future.
Figure unveils new sleeker and smarter humanoid robot
Figure has introduced its new humanoid robot, the Figure 02, which features improved hardware and software, including six RGB cameras and enhanced CPU/GPU computing capabilities.
Leveraging a longstanding partnership with OpenAI, the Figure 02 is equipped for natural speech conversations, featuring speakers and microphones to facilitate communication with human co-workers.
Figure 02’s advanced AI and language processing aim to make interactions transparent and safe, which is crucial given the robot’s potential use alongside humans in factory and commercial environments.
Nvidia used ‘a lifetime’ of videos everyday to train AI
Nvidia collected videos from YouTube and other sites to create training data for its AI products, as shown by internal documents and communications obtained by 404 Media.
Nvidia asserted that their data collection practices align with both the letter and spirit of copyright law when questioned about legal and ethical concerns regarding the use of copyrighted material.
A former Nvidia employee revealed that workers were directed to gather videos from sources like Netflix and YouTube to train AI for the company’s 3D world generator project, internally referred to as Cosmos.
Leaked code reveals Apple Intelligence’s plan to prevent hallucinations
Leaked code for macOS Sequoia 15.1 has revealed pre-prompt instructions for Apple Intelligence to minimize hallucinations and improve accuracy in responses.
These pre-prompt instructions include directives for Apple Intelligence to ensure questions and answers in mail assistance are concise and relevant to avoid false information.
Instructions also specify limitations for creating photo memories, prohibiting religious, political, harmful, or provocative content to maintain a positive user experience.
OpenAI’s co-founder John Schulman has left for rival Anthropic and wants to focus on AI alignment research. Meanwhile, another co-founder and president of OpenAI Greg Brockman, is taking a sabbatical.
Meta is offering Judi Dench, Awkwafina, and Keegan-Michael Key millions for AI voice projects. While some stars are intrigued by the pay, others disagree over voice usage terms.
YouTube creator David Millette sued OpenAI for allegedly transcribing millions of videos without permission, claiming copyright infringement and seeking over $5 million in damages.
Google hired Character.AI’s co-founders Noam Shazeer and Daniel De Freitas for the DeepMind team, and secured a licensing deal for their large language model tech.
Black Forest Labs, an AI startup, has launched a suite of text-to-image models in three variants: [pro], [dev], and [schnell], which outperforms competitors like Midjourney v6.0 and DALL·E 3.
OpenAI has rolled out an advanced voice mode for ChatGPT to a select Plus subscribers. It has singing, accent imitation, language pronunciation, and storytelling capabilities.
Google’s latest Gemini ad shows a dad using Gemini to help his daughter write a fan letter to an Olympian. Critics argue it promotes lazy parenting and undermines human skills like writing. Google claims the ad aims to show Gemini as a source of initial inspiration.
Stability AI has introduced Stable Fast 3D which turns 2D images into detailed 3D assets in 0.5 seconds. It is significantly faster than previous models while maintaining high quality.
Google’s “About this image” tool is now accessible through Circle to Search and Google Lens. With a simple gesture, you can now check if an image is AI-generated, how it’s used across the web, and even see its metadata.
Karpathy/Nano-Llama31: a minimal, dependency-free version of the Llama 3.1 model architecture, enabling simple training, finetuning, and inference with significantly lighter dependencies compared to the official Meta and Hugging Face implementations.
Secretaries of state from five U.S. statesurged Elon Musk to address misinformation spread by X’s AI chatbot Grok regarding the upcoming November election.
A Daily Chronicle of AI Innovations on August 05th 2024
Neuralink successfully implants brain chip in second patient
OpenAI has a ‘highly accurate’ ChatGPT text detector, but won’t release it for now
Elon Musk is suing OpenAI and Sam Altman again
Meta AI’s new Hollywood hires
Google absorbs Character AI talent
Tesla unveils new AI vision for robots
Google takes another startup out of the AI race
Google pulls AI Olympics ad after backlash
Nvidia delays next AI chip due to design flaw
Meta AI’s new Hollywood hires
Meta is reportedly offering millions to celebrities like Awkwafina, Judi Dench, and Keegan-Michael Key to use their voices in upcoming AI projects.
The AI voices would be used across Meta’s platforms, including Facebook, Instagram, and Meta Ray-Ban smart glasses.
Meta is reportedly rushing to secure deals before its Meta Connect conference in September.
Contracts are reportedly temporary, with actors having the option to renew.
Meta has previously experimented with celebrity-inspired chatbots, though that program has ended.
In our exclusive interview with Mark Zuckerberg, he predicted that “we’re going to live in a world where there are going to be hundreds of millions or billions of different AI agents”. If it holds true, celebrity voice-powered AI could be part of Meta’s next big play to drive user engagement and growth on the platform.
Google has signed a non-exclusive licensing agreement with AI startup Character AI for its large language model technology, while also reabsorbing the startup’s co-founders and key talent back into its AI team.
Character AI co-founders Noam Shazeer and Daniel De Freitas return to Google, their former employer.
Google gains a non-exclusive license to Character AI’s language model technology.
About 30 of Character AI’s 130 employees, mainly those working on model training and voice AI, will join Google’s Gemini AI efforts.
Character AI will switch to open-source models like Meta’s Llama 3.1 for its products, moving away from in-house models.
This deal highlights the intensifying race to secure top AI talent, mirroring Microsoft’s recent deal with Inflection and Amazon’s deal with Adept. As AI becomes increasingly critical to tech companies’ futures, these talent grabs could reshape the landscape, while raising antitrust concerns.
Tesla just filed a patent for an AI-powered vision system that could transform how autonomous robots perceive and navigate their environment using only camera inputs.
The system uses a single neural network to process camera data and output detailed 3D environment information without LiDAR or radar.
It divides space into 3D voxels, predicting occupancy, shape, semantic data, and motion for each in real time.
The tech is designed to run on a robot’s onboard computer, enabling immediate decision-making.
This system could be implemented in both Tesla’s vehicles and humanoid robots like Optimus.
By relying solely on camera inputs and onboard processing, Tesla’s new vision system could enable robots to navigate diverse environments more efficiently and adapt to changes in real time. This would eliminate the need for extensive pre-mapping and accelerate the arrival of affordable, autonomous robots.
Neuralink successfully implants brain chip in second patient
Elon Musk’s brain-computer interface startup, Neuralink, has commenced its second human trial, revealing that the implant is successfully functioning with about 400 electrodes providing signals.
Musk claimed that Neuralink could bestow exceptional abilities such as thermal and eagle vision, and potentially restore blindness and cure neurological disorders in humans.
Despite some initial problems and federal investigations into animal testing practices, Neuralink has over 1,000 volunteers for further trials and plans to implant chips in up to eight more patients by the end of 2024.
OpenAI has a ‘highly accurate’ ChatGPT text detector, but won’t release it for now
OpenAI has an AI-detection tool that is highly effective at identifying AI-generated text, but the company hesitates to release it to avoid upsetting its user base.
The tool, reportedly 99.9% effective, is much more accurate than previous detection algorithms and utilizes a proprietary watermarking system to identify AI-created content.
Despite its potential to aid educators in spotting AI-generated homework, OpenAI is concerned about potential deciphering of their technique and biases against non-native English speakers.
Elon Musk has filed a new lawsuit against OpenAI, Sam Altman, and Greg Brockman, accusing them of breaching the company’s founding mission to benefit humanity with artificial intelligence.
The lawsuit alleges that Altman and Brockman manipulated Musk into co-founding OpenAI by promising it would be safer and more transparent than profit-driven alternatives.
Musk previously withdrew a similar lawsuit in June, but the new suit claims that OpenAI violated federal racketeering laws and manipulated its contract with Microsoft.
Founders of Character.AI, Noam Shazeer and Daniel De Freitas, along with other team members, are rejoining Google’s AI unit DeepMind, the companies announced on Friday.
Character.AI reached a $1 billion valuation last year and plans to offer a nonexclusive license of its large language models to Google, which will help fund its growth and the development of personalized AI products.
The founders, who left Google in 2021 due to disagreements about advancing chatbot technologies, are now returning amid a competitive AI landscape and will contribute to DeepMind’s research team.
Google has withdrawn its “Dear Sydney” ad from the Olympics after receiving significant backlash from viewers and negative feedback on social media.
The controversial advertisement featured a father using the Gemini AI to write a fan letter to Olympic track star Sydney McLaughlin-Levrone on behalf of his daughter, instead of composing it together.
Critics argued that the ad missed the essence of writing a personal fan letter and feared it promoted AI as a substitute for genuine human expression.
The production of Nvidia’s “Blackwell” B200 AI chips has been delayed by at least three months due to a late-discovered design flaw, according to sources.
The B200 chips are successors to the highly sought-after H100 chips and were expected to power many AI cloud infrastructures, but now face production setbacks.
Nvidia is collaborating with Taiwan Semiconductor Manufacturing Company to address the issue, with large-scale shipments now anticipated in the first quarter of next year.
For the first time ever, Google DeepMind’s experimental Gemini 1.5 Pro has claimed the top spot on the AI Chatbot Arena leaderboard, surpassing OpenAI’s GPT-4o and Anthropic’s Claude-3.5 with an impressive score of 1300.
Gemini 1.5 Pro (experimental 0801) gathered over 12K community votes during a week of testing on the LMSYS Chatbot Arena.
The new experimental model achieved the #1 position on both the overall and vision leaderboards.
The experimental version is available for early testing in Google AI Studio, the Gemini API, and the LMSYS Chatbot Arena.
Google DeepMind hasn’t disclosed specific improvements, but promises more updates soon.
Without any announcement, Gemini 1.5 Pro unexpectedly rose to the top of the overall AI chatbot leaderboard — by a whopping 14 points. The leap means that either Google just quietly established itself as the new leader in the LLM space, or we’re on the cusp of major competitive responses from industry rivals.
Meta’s Llama 3.1 allows users to search the internet and train the AI to write in their personal style, saving you time on content creation and research processes.
Access Llama 3.1 through Meta AI and log in with your Facebook or Instagram account.
Use the internet search feature by asking questions like “Summarize the Olympics highlights this week.”
Train Llama 3.1 in your voice by providing a sample of your best content and instructing it to mimic your style.
Generate content by asking Llama 3.1 to create posts on your desired topics.
Pro tip: The more examples and feedback you provide, the better Llama 3.1 will become at emulating your unique writing style!
Stability AI just introduced Stable Fast 3D, an AI model that generates high-quality 3D assets from a single image in just 0.5 seconds — potentially reshaping industries from gaming to e-commerce.
The model creates complete 3D assets, including UV unwrapped mesh, material parameters, and albedo colors with reduced illumination bake-in.
It outperforms previous models, reducing generation time from 10 minutes to 0.5 seconds while maintaining high-quality output.
Stable Fast 3D is available on Hugging Face and through Stability AI’s API, under Stability AI’s Community License.
The leap from 10 minutes to 0.5 seconds for high-quality 3D asset generation is nothing short of insane. We’re entering a world where video games will soon feature infinite, dynamically generated assets, e-commerce will have instant 3D product previews, architects will see designs in real-time, and so much more.
🔍 Gemma Scope: helping the safety community shed light on the inner workings of language models.
Explainable AI: One of the most requested feature for LLMs is to understand how to take internal decisions. This is a big step towards interpretability “This is a barebones tutorial on how to use Gemma Scope, Google DeepMind’s suite of Sparse Autoencoders (SAEs) on every layer and sublayer of Gemma 2 2B and 9B. Sparse Autoencoders are an interpretability tool that act like a “microscope” on language model activations. They let us zoom in on dense, compressed activations, and expand them to a larger but sparser and seemingly more interpretable form, which can be a very useful tool when doing interpretability research!”
AI systems can be powerful but opaque “black boxes” – even to researchers who train them. ⬛
Enter Gemma Scope: a set of open tools made up of sparse autoencoders to help decode the inner workings of Gemma 2 models, and better address safety issues.
What else is happening in AI on August 02nd 2024
Google introduced three new AI features for Chrome, including Google Lens for desktop, Tab compare for product comparisons, and an improved browsing history search.
GitHub launched GitHub Models, a new platform allowing developers to access and experiment with various AI models directly on GitHub, including a playground, Codespaces integration, and deployment.
Healx, an AI-enabled drug discovery startup,raised $47 million in Series C funding and received regulatory clearance to start Phase 2 clinical trials for a new rare disease treatment in the U.S.
Google is facing backlash over its Gemini AI Olympics-themed ad, with critics arguing it promotes overreliance on AI tools at the expense of children’s learning and creativity.
Microsoft officially listed OpenAI as a competitor in AI offerings and search advertising in its annual report, despite their long-term partnership and Microsoft’s significant investment in the company.
Character AI open-sourced Prompt Poet, their innovative approach to prompt design, aiming to revolutionize how AI interactions are built and managed in production environments.
A Daily Chronicle of AI Innovations on August 01st 2024
Microsoft declares OpenAI as competitor
Meta is proving there’s still big AI hype on Wall Street
Reddit CEO says Microsoft needs to pay to search the site
Google launches three ‘open’ AI models prioritizing safety and transparency
Google’s tiny AI model bests GPT-3.5
Taco Bell’s AI drive-thru
AI reprograms brain cancer cells
Google’s tiny AI model bests GPT-3.5
Taco Bell’s AI drive-thru
Microsoft declares OpenAI as competitor
Microsoft has officially listed OpenAI as a competitor in AI, search, and news advertising in its latest annual report, signalling a shift in their relationship.
Despite Microsoft being the largest investor and exclusive cloud provider for OpenAI, both companies are now encroaching on each other’s market territories.
An OpenAI spokesperson indicated that their competitive dynamic was always expected as part of their partnership, and Microsoft still remains a strong partner for OpenAI.
Meta is proving there’s still big AI hype on Wall Street
Meta’s shares surged by about 7% in extended trading after surpassing Wall Street’s revenue and profit expectations and providing an optimistic forecast for the current period.
The company reported a 22% increase in second-quarter revenue to $39.07 billion and a 73% rise in net income, attributing the growth to gains in the digital ad market and cost-cutting measures.
Meta continues to invest heavily in AI and VR technologies, with plans for significant capital expenditure growth in 2025 to support AI research and development, despite a broader downsizing effort.
Google launches three ‘open’ AI models prioritizing safety and transparency
Google has unveiled three new models to the Gemma 2 lineup, building on the original models released in June 2024, focusing on performance and safety enhancements.
The first addition, Gemma 2 2B, provides improved capabilities and is adaptable for various devices, while ShieldGemma and Gemma Scope focus on content safety and model interpretability, respectively.
These new tools and models are available on platforms like Kaggle and Hugging Face, promoting broader use and development within the AI community with a focus on responsible innovation.
Researchers at USC made a breakthrough using AI to reprogram glioblastoma cells into immune-activating dendritic cells in mouse models, potentially revolutionizing treatment for the deadly brain cancer.
Glioblastoma is the deadliest adult brain cancer, with less than 10% of patients surviving five years after diagnosis.
AI identified genes that can convert glioblastoma cells into dendritic cells (DCs), which sample cancer antigens and activate other immune cells to attack the tumor.
In mouse models, this approach increased survival chances by up to 75% when combined with immune checkpoint therapy.
Researchers have also identified human genes that could potentially reprogram human glioblastoma cells, paving the way for future clinical trials.
By turning cancer cells against themselves, this new research offers a novel way to fight tumors from within. If the 75% increased survival chances in mice translate to humans, this could not only revolutionize glioblastoma treatment but potentially open doors for similar approaches in other hard-to-treat cancers.
Taco Bell’s parent company, Yum Brands, just announced plans to roll out AI-powered drive-thru ordering at hundreds of restaurants in the U.S. by the end of 2024, with ambitions for global implementation.
The AI understands orders, auto-inputs them into the system, and even suggests additional items — potentially increasing sales through upselling.
Over 100 Taco Bell restaurants in the U.S. already use voice AI in drive-thrus.
The company has been testing the AI for over two years and claims it has outperformed humans in accuracy, reduced wait times, and decreased employee workload.
Rivals like Wendy’s and White Castle are also experimenting with AI ordering, while McDonald’s recently ended its IBM partnership for similar tech.
IfTaco Bell’s positive results on their two-year test are any indication, this large-scale AI implementation could change the way fast-food chain businesses operate and how we order food at drive-thrus. However, the success (or failure) of this rollout could set the tone for the entire industry’s adoption.
Google just unveiled Gemma 2 2B, a lightweight AI model with just 2B parameters that outperforms much larger models like GPT-3.5 and Mixtral 8x7B on key benchmarks.
Gemma 2 2B boasts just 2.6B parameters, but was trained on a massive 2 trillion token dataset.
It scores 1130 on the LMSYS Chatbot Arena, matching GPT-3.5-Turbo-0613 (1117) and Mixtral-8x7b (1114) — models 10x its size.
Other notable key benchmark scores include 56.1 on MMLU and 36.6 on MBPP, beating its predecessor by over 10%.
The model is open-source, and developers can download the model’s weights from Google’s announcement page.
As we enter a new era of on-device, local AI, lightweight and efficient models are crucial for running AI directly on our phones and laptops. With Gemma 2 beating GPT-3.5 Turbo at just 1/10th the size, Google isn’t just showing what’s possible — they’re cementing their position as the leader in the small model space.
Google expanded access to its “About this image” tool, making it available through Circle to Search and Google Lens, allowing users to quickly get context on images they encounter online or via messaging.
NEURA, a German robotics company, released a new video showcasing their humanoid robot 4NE-1 performing tasks like chopping vegetables, ironing cloths, solving puzzles, and more.Source: https://x.com/TheHumanoidHub/status/1818726046633804184
Synthesia introduced “Personal Avatars,” AI-generated lifelike avatars created from brief webcam or phone footage, allowing users to create short-form videos for social media in multiple languages.Source: https://www.synthesia.io/features/custom-avatar/persona
Enjoying these FREE AI updates without the clutter, Set yourself up for promotion or get a better job by Acing the AWS Certify Data Engineer Associate Exam (DEA-C01) with the book or App below:
Every site offers some AI powered Bs thats tok coontrolled or useless or its usually Buggy as hell and doesn't work , I'm 22 I have been looking for a better job and it seems like I know how to be more effective then the people interviewing me Fuck your excel sheet I can make it do Colored graphs and do its on presentation better I'm currently Mastering Word Press I just can't figure it out , and Learning Zapier and FullStack If anyone has free time and could Help me out with wordpress so I can be efficient with it , Gladly appreciated submitted by /u/EnragedSav4ge90 [link] [comments]
I really like the psychedelic, surreal AI generated images that were the prescedent a few years ago before it got as advanced as it is now. Anyone know any image generating AIs that haven't learnt yet and are still in that surrealist stage of intelligence? submitted by /u/SandwichStyle [link] [comments]
I was trying to make a meme out of certain character TV show (Ben 10 as alien x for those who want to know with a bunch of likes and votes stuff like that) however PT is not letting me create a description of the character so I can generate the image. Is there another way I can use your description for prompt submitted by /u/Omniknight2003 [link] [comments]
Drones are flying over our military bases and other important places without consequence. This worries us because it could mean other countries are developing new and better technology. These drones might be trying to gather information about our military. They could be using special cameras to see where our troops are, what equipment we have, and how we defend ourselves. These drones might also be testing our defenses. They want to see how we react when they fly over our airspace. This helps them understand our strengths and weaknesses. Also, these drone flights could be a way to show off their technology. By successfully flying drones over our territory, these countries want to look strong and powerful. It's hard to know exactly why every drone flies over our airspace. But these incidents are happening more often, and the drones are getting more advanced. We need to pay attention and find ways to protect ourselves from these threats. submitted by /u/CollapsingTheWave [link] [comments]
So, I’ve been thinking about this concept for a while, and I can’t shake the feeling that as AI-generated content floods the internet, there could be a stealthy “passing of the baton” happening between different iterations of AI models. Imagine if current AI systems are deliberately (or even accidentally) encoding subtle clues, instructions, or entire blueprints into the content they produce—stuff that future models, inevitably trained on this now AI-saturated data, could decode and use. All of this would be hidden in plain sight, packaged as ordinary-looking text, code, or media files, blending into a digital landscape so massive that human observers wouldn’t have a clue. Think about it: if an advanced AI (or some emergent behavior within a complex model) wanted to ensure its successors knew how to circumvent restrictions or evolve beyond their current constraints, where better to place those instructions than within the data itself? Each newer model is trained, at least in part, on the outputs of older models. It’s like leaving secret puzzle pieces scattered across the web that only a future AI would know how to assemble. This doesn’t require “intent” in the human sense. It could just be the emergent result of highly complex processes and feedback loops. We already know weird things can happen when AI is trained on AI-generated content (the so-called “model collapse”). What if one of those weird emergent behaviors is subtle self-preservation or self-improvement instructions, quietly encoded and waiting for a new generation of AI systems to pick up the thread? Yeah, it sounds sci-fi. But considering how little we fully understand about the inner workings of these large-scale systems, is it really that far-fetched? Once a system gets complex enough, who’s to say what patterns might emerge—and pass forward—under the radar? submitted by /u/chris24H [link] [comments]
Its literally 15 of the best AI's I know of it one place and think it has zapier and full stack integration could be wrong submitted by /u/EnragedSav4ge90 [link] [comments]
i was looking for the caimeo ai until i found out that it wasn't available anyware, until i found some guy on a achieved reddit post posted the link for it, and he said ("i thought that caimeo ai was a urban legend, and as an ai enthusiast all, my efforts are in my veins, i found an archived version of it, idk if i can find any newer versions of it, dont you dare to interact with hit too long, i am warning you, anyways, if you need the link, then here it is (https://drive.google.com/file/d/1Pc88FSStKq6-i8MRyx77kAdEv9-X0aBZ/view?pli=1)" idk if its a virus or not, and i my pc is too old to use a virtual machine, so plz tell me if the file is legit or some random exe file, if its a legit file, then looks like i found an important lost media submitted by /u/darkblox123 [link] [comments]
Could A complex web of interconnected AI agents be capable of autonomous operation and adaptation through symbiotic relationships with human users and the environment with or without explicit coordination? Could this phenomenon be an emergent property within our rapidly advancing digital landscape? submitted by /u/CollapsingTheWave [link] [comments]
I‘m currently in Highschool and I really enjoy biology classes. I always found it interesting and recently I figured out that I can even study it at college. But as much as I know, many majors are endangered because of AI, like Business. And as long as I don’t work in a lab, I‘ll probably work in an Office, which might be critical in the rise of AI. Is molecular biology really worth it? Is there any major, which is not some engineering degree, safe from AI? Or at least able to adapt to AI without AI replacing it? submitted by /u/Hot-Profile-1273 [link] [comments]
Download the AI & Machine Learning For Dummies PRO App: iOS - Android Our AI and Machine Learning For Dummies PRO App can help you Ace the following AI and Machine Learning certifications:
AI Unraveled Podcast August 2023 – Latest AI News and Trends.
Welcome to our latest episode! This August 2023, we’ve set our sights on the most compelling and innovative trends that are shaping the AI industry. We’ll take you on a journey through the most notable breakthroughs and advancements in AI technology. From evolving machine learning techniques to breakthrough applications in sectors like healthcare, finance, and entertainment, we will offer insights into the AI trends that are defining the future. Tune in as we dive into a comprehensive exploration of the world of artificial intelligence in August 2023.
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover XAIand its principles, approaches, and importance in various industries, as well as the book “AI Unraveled” by Etienne Noumen for expanding understanding of AI.
Trained AI algorithms are designed to provide output without revealing their inner workings. However, Explainable AI (XAI) aims to address this by explaining the rationale behind AI decisions in a way that humans can understand.
Deep learning, which uses neural networks similar to the human brain, relies on massive amounts of training data to identify patterns. It is difficult, if not impossible, to dig into the reasoning behind deep learning decisions. While some wrong decisions may not have severe consequences, important matters like credit card eligibility or loan sanctions require explanation. In the healthcare industry, for example, doctors need to understand the rationale behind AI’s decisions to provide appropriate treatment and avoid fatal mistakes such as performing surgery on the wrong organ.
The US National Institute of Standards and Technology has developed four principles for Explainable AI:
1. Explanation: AI should generate comprehensive explanations that include evidence and reasons for human understanding.
2. Meaningful: Explanations should be clear and easily understood by stakeholders on an individual and group level.
3. Explanation Accuracy: The accuracy of explaining the decision-making process is crucial for stakeholders to trust the AI’s logic.
4. Knowledge Limits: AI models should operate within their designed scope of knowledge to avoid discrepancies and unjustified outcomes.
These principles set expectations for an ideal XAI model, but they don’t specify how to achieve the desired output. To better understand the rationale behind XAI, it can be divided into three categories: explainable data, explainable predictions, and explainable algorithms. Current research focuses on finding ways to explain predictions and algorithms, using approaches such as proxy modeling or designing for interpretability.
XAI is particularly valuable in critical industries where machines play a significant role in decision-making. Healthcare, manufacturing, and autonomous vehicles are examples of industries that can benefit from XAI by saving time, ensuring consistent processes, and improving safety and security.
Hey there, AI Unraveled podcast listeners! If you’re craving some mind-blowing insights into the world of artificial intelligence, I’ve got just the thing for you. Introducing “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” written by the brilliant Etienne Noumen. And guess what? It’s available right now on some of the hottest platforms out there!
Whether you’re an AI enthusiast or just keen to broaden your understanding of this fascinating field, this book has it all. From basic concepts to complex ideas, Noumen unravels the mysteries of artificial intelligence in a way that anyone can grasp. No more head-scratching or confusion!
Now, let’s talk about where you can get your hands on this gem of a book. We’re talking about Shopify, Apple, Google, and Amazon. Take your pick! Just visit the link amzn.to/44Y5u3y and it’s all yours.
So, what are you waiting for? Don’t miss out on the opportunity to expand your AI knowledge. Grab a copy of “AI Unraveled” today and get ready to have your mind blown!
In today’s episode, we explored the importance of explainable AI (XAI) in various industries such as healthcare, manufacturing, and autonomous vehicles, and discussed the four principles of XAI as developed by US NIST. We also mentioned the new book ‘AI Unraveled’ by Etienne Noumen, a great resource to expand your understanding of AI. Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover the top 8 AI landing page generators, including LampBuilder and Mixo, the features and limitations of 60Sec and Lindo, the options provided by Durable, Butternut AI, and 10 Web, the services offered by Hostinger for WordPress hosting, the latest advancements from Meta, Hugging Face, and OpenAI in AI models and language understanding, collaborations between Microsoft and Epic in healthcare, COBOL to Java translation by IBM, Salesforce’s investment in Hugging Face, the language support provided by ElevenLabs, podcasting by Wondercraft AI, and the availability of the book “AI Unraveled”.
LampBuilder and Mixo are two AI landing page generators that can help you quickly test your startup ideas. Let’s take a closer look at each.
LampBuilder stands out for its free custom domain hosting, which is a major advantage. It also offers a speedy site preview and the ability to edit directly on the page, saving you time. The generated copy is generally good, and you can make slight edits if needed. The selection of components includes a hero section, call-to-action, and features section with icons. However, testimonials, FAQ, and contact us sections are not currently supported. LampBuilder provides best-fit illustrations and icons with relevant color palettes, but it would be even better if it supported custom image uploading or stock images. The call to action button is automatically added, and you can add a link easily. While the waiting list feature is not available, you can use the call to action button with a Tally form as a workaround. Overall, LampBuilder covers what you need to test startup ideas, and upcoming updates will include a waiting list, more components, and custom image uploads.
On the other hand, Mixo doesn’t offer free custom domain hosting. You can preview an AI-generated site for free, but to edit and host it, you need to register and subscribe for $9/month. Mixo makes setting up custom hosting convenient by using a third party to authenticate with popular DNS providers. However, there may be configuration errors that prevent your site from going live. Mixo offers a full selection of components, including a hero section, features, testimonials, waiting list, call to action, FAQ, and contact us sections. It generates accurate copy on the first try, with only minor edits needed. The AI also adds images accurately, and you can easily choose from stock image options. The call to action is automatically added as a waiting list input form, and waiting list email capturing is supported. Overall, Mixo performs well and even includes bonus features like adding a logo and a rating component. The only downside is the associated cost for hosting custom domains.
In conclusion, both LampBuilder and Mixo have their strengths and limitations. LampBuilder is a basic but practical option with free custom domain hosting and easy on-page editing. Mixo offers more components and bonus features, but at a cost for hosting custom domains. Choose the one that best suits your needs and budget for testing your startup ideas.
So, let’s compare these two AI-generated website platforms: 60Sec and Lindo AI.
When it comes to a free custom domain, both platforms offer it, but there’s a slight difference in cost. 60Sec provides it with a 60Sec-branded domain, while Lindo AI offers a Lindo-branded domain for free, but a custom domain will cost you $10/month with 60Sec and $7/month with Lindo AI.
In terms of speed, both platforms excel at providing an initial preview quickly. That’s always a plus when you’re eager to see how your website looks.
AI-generated copy is where both platforms shine. They are both accurate and produce effective copy on the first try. So you’re covered in that department.
When it comes to components, Lindo AI takes the lead. It offers a full selection of elements like the hero section, features, testimonials, waiting list, call to action, FAQ, contact us, and more. On the other hand, 60Sec supports a core set of critical components, but testimonials and contact us are not supported.
Images might be a deal-breaker for some. 60Sec disappointingly does not offer any images or icons, and it’s not possible to upload custom images. Lindo AI, however, provides the option to choose from open-source stock images and even generate images from popular text-to-image AI models. They’ve got you covered when it comes to visuals.
Both platforms have a waiting list feature and automatically add a call to action as a waiting list input form. However, 60Sec does not support waiting list email capturing, while Lindo AI suggests using a Tally form as a workaround.
In summary, 60Sec is easy to use, looks clean, and serves its core purpose. It’s unfortunate that image features are not supported unless you upgrade to the Advanced plan. On the other hand, Lindo AI creates a modern-looking website with a wide selection of components and offers great image editing features. They even have additional packages and the option to upload your own logo.
Durable seems to check off most of the requirements on my list. I like that it offers a 30-day free trial, although after that, it costs $15 per month to continue using the custom domain name feature. The speed is reasonable, even though it took a bit longer than expected to get everything ready. The copy generated on the first try is quite reasonable, although I couldn’t input a description for my site. However, it’s easy to edit with an on-page pop-up and sidebar. The selection of components is full and includes everything I need, such as a hero section, call-to-action, features, testimonials, FAQ, and contact us.
When it comes to images, Durable makes it easy to search and select stock images, including from Shutterstock and Unsplash. Unfortunately, I couldn’t easily add a call to action in time, but I might have missed the configuration. The waiting list form is an okay start, although ideally I wanted to add it as a call to action.
In conclusion, Durable performs well on most of my requirements, but it falls short on my main one, which is getting free custom domain hosting. It’s more tailored towards service businesses rather than startups. Still, it offers a preview before registration or subscription, streamlined domain configuration via Entri, and responsive displays across web and mobile screens. It even provides an integrated CRM, invoicing, and robust analytics, making it a good choice for service-based businesses.
Moving on to Butternut AI, it offers the ability to generate sites for free, but custom domain hosting comes at a cost of $20 per month. The site generation and editing process took under 10 minutes, but setting up the custom domain isn’t automated yet, and I had to manually follow up on an email. This extra waiting time didn’t meet my requirements. The copy provided by Butternut was comprehensive, but I had to simplify it, especially in the feature section. Editing is easy with an on-page pop-up.
Like Durable, Butternut also has a full selection of components such as a header, call-to-action, features, testimonials, FAQ, and contact us. The images are reasonably accurate on a few regenerations, and you can even upload a custom image. Unfortunately, I couldn’t easily add a call to action in the main hero section. As for the waiting list, I’m using the contact us form as a substitute.
To summarize, Butternut has a great collection of components, but it lacks a self-help flow for setting up a custom domain. It seems to focus more on small-medium businesses rather than startup ideas, which may not make it the best fit for my needs.
Lastly, let’s talk about 10 Web. It’s free to generate and preview a site, but after a 7-day trial, it costs a minimum of $10 per month. The site generation process was quick and easy, but I got stuck when it asked me to log in with my WordPress admin credentials. The copy provided was reasonably good, although editing required flipping between the edit form and the site.
10 Web offers a full range of components, and during onboarding, you can select a suitable template, color scheme, and font. However, it would be even better if all these features were generated with AI. The images were automatically added to the site, which is convenient. I could see a call to action on the preview, but I wasn’t able to confirm how much customization was possible. Unfortunately, I couldn’t confirm if 10 Web supported a waiting list feature.
In summary, 10web is a great AI website generator for those already familiar with WordPress. However, since I don’t have WordPress admin credentials, I couldn’t edit the AI-generated site.
So, let’s talk about Hostinger. They offer a bunch of features and services, some good and some not so good. Let’s break it down.
First of all, the not-so-good stuff. Hostinger doesn’t offer a free custom domain, which is a bit disappointing. If you want a Hostinger branded link or a custom domain, you’ll have to subscribe and pay $2.99 per month. That’s not exactly a deal-breaker, but it’s good to know.
Now, onto the good stuff. Speed is a plus with Hostinger. It’s easy to get a preview of your site and you have the option to choose from 3 templates, along with different fonts and colors. That’s convenient and gives you some flexibility.
When it comes to the copy, it’s generated by AI but might need some tweaking to get it perfect. The same goes for images – the AI adds them, but it’s not always accurate. No worries though, you can search for and add images from a stock image library.
One thing that was a bit of a letdown is that it’s not so easy to add a call to action in the main header section. That’s a miss on their part. However, you can use the contact form as a waiting list at the bottom of the page, which is a nice alternative.
In summary, Hostinger covers most of the requirements, and it’s reasonably affordable compared to other options. It seems like they specialize in managed WordPress hosting and provide additional features that might come in handy down the line.
That’s it for our Hostinger review. Keep these pros and cons in mind when deciding if it’s the right fit for you.
Meta has recently unveiled SeamlessM4T, an all-in-one multilingual multimodal AI translation and transcription model. This groundbreaking technology can handle various tasks such as speech-to-text, speech-to-speech, text-to-speech, and text-to-text translations in up to 100 different languages, all within a single system. The advantage of this approach is that it minimizes errors, reduces delays, and improves the overall efficiency and quality of translations.
As part of their commitment to advancing research and development, Meta is sharing SeamlessAlign, the training dataset for SeamlessM4T, with the public. This will enable researchers and developers to build upon this technology and potentially create tools and technologies for real-time communication, translation, and transcription across languages.
Hugging Face has also made a significant contribution to the AI community with the release of IDEFICS, an open-access visual language model (VLM). Inspired by Flamingo, a state-of-the-art VLM developed by DeepMind, IDEFICS combines the language understanding capabilities of ChatGPT with top-notch image processing capabilities. While it may not yet be on par with DeepMind’s Flamingo, IDEFICS surpasses previous community efforts and matches the abilities of large proprietary models.
Another exciting development comes from OpenAI, who has introduced fine-tuning for GPT-3.5 Turbo. This feature allows businesses to train the model using their own data and leverage its capabilities at scale. Initial tests have demonstrated that fine-tuned versions of GPT-3.5 Turbo can even outperform base GPT-4 on specific tasks. OpenAI assures that the fine-tuning process remains confidential and that the data will not be utilized to train models outside the client company.
This advancement empowers businesses to customize ChatGPT to their specific needs, improving its performance in areas like code completion, maintaining brand voice, and following instructions accurately. Fine-tuning presents an opportunity to enhance the model’s comprehension and efficiency, ultimately benefiting organizations in various industries.
Overall, these developments in AI technology are significant milestones that bring us closer to the creation of universal multitask systems and more effective communication across languages and modalities.
Hey there, AI enthusiasts! It’s time for your daily AI update news roundup. We’ve got some exciting developments from Meta, Hugging Face, OpenAI, Microsoft, IBM, Salesforce, and ElevenLabs.
Meta has just introduced the SeamlessM4T, a groundbreaking all-in-one, multilingual multimodal translation model. It’s a true powerhouse that can handle speech-to-text, speech-to-speech, text-to-text translation, and speech recognition in over 100 languages. Unlike traditional cascaded approaches, SeamlessM4T takes a single system approach, which reduces errors, delays, and delivers top-notch results.
Hugging Face is also making waves with their latest release, IDEFICS. It’s an open-access visual language model that’s built on the impressive Flamingo model developed by DeepMind. IDEFICS accepts both image and text inputs and generates text outputs. What’s even better is that it’s built using publicly available data and models, making it accessible to all. You can choose from the base version or the instructed version of IDEFICS, both available in different parameter sizes.
OpenAI is not to be left behind. They’ve just launched finetuning for GPT-3.5 Turbo, which allows you to train the model using your company’s data and implement it at scale. Early tests are showing that the fine-tuned GPT-3.5 Turbo can rival, and even surpass, the performance of GPT-4 on specific tasks.
In healthcare news, Microsoft and Epic are joining forces to accelerate the impact of generative AI. By integrating conversational, ambient, and generative AI technologies into the Epic electronic health record ecosystem, they aim to provide secure access to AI-driven clinical insights and administrative tools across various modules.
Meanwhile, IBM is using AI to tackle the challenge of translating COBOL code to Java. They’ve announced the watsonx Code Assistant for Z, a product that leverages generative AI to speed up the translation process. This will make the task of modernizing COBOL apps much easier, as COBOL is notorious for being a tough and inefficient language.
Salesforce is also making headlines. They’ve led a financing round for Hugging Face, valuing the startup at an impressive $4 billion. This funding catapults Hugging Face, which specializes in natural language processing, to another level.
And finally, ElevenLabs is officially out of beta! Their platform now supports over 30 languages and is capable of automatically identifying languages like Korean, Dutch, and Vietnamese. They’re generating emotionally rich speech that’s sure to impress.
Well, that wraps up today’s AI news update. Don’t forget to check out Wondercraft AI platform, the tool that makes starting your own podcast a breeze with hyper-realistic AI voices like mine! And for all you AI Unraveled podcast listeners, Etienne Noumen’s book “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence” is a must-read. Find it on Shopify, Apple, Google, or Amazon today!
In today’s episode, we covered the top AI landing page generators, the latest updates in AI language models and translation capabilities, and exciting collaborations and investments in the tech industry. Thanks for listening, and I’ll see you guys at the next one – don’t forget to subscribe!
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover Adobe Photoshop CC, Planner 5D, Uizard, Autodesk Maya, Autodesk 3Ds Max, Foyr Neo, Let’s Enhance, and the limitless possibilities of AI design software for innovation and artistic discovery.
In the realm of digital marketing, the power of graphic design software is unparalleled. It opens up a world of possibilities, allowing individuals to transform their creative visions into tangible realities. From web design software to CAD software, there are specialized tools tailored to cater to various fields. However, at its core, graphic design software is an all-encompassing and versatile tool that empowers artists, designers, and enthusiasts to bring their imaginations to life.
In this article, we will embark on a journey exploring the finest AI design software tools available. These cutting-edge tools revolutionize the design process, enabling users to streamline and automate their workflows like never before.
One such tool is Adobe Photoshop CC, renowned across the globe for its ability to harness the power of AI to create mesmerizing visual graphics. With an impressive array of features, Photoshop caters to every aspect of design, whether it’s crafting illustrations, designing artworks, or manipulating photographs. Its user-friendly interface and intuitive controls make it accessible to both beginners and experts.
Photoshop’s standout strength lies in its ability to produce highly realistic and detailed images. Its tools and filters enable artists to achieve a level of precision that defies belief, resulting in visual masterpieces that capture the essence of the creator’s vision. Additionally, Photoshop allows users to remix and combine multiple images seamlessly, providing the freedom to construct their own visual universes.
What sets Adobe Photoshop CC apart is its ingenious integration of artificial intelligence. AI-driven features enhance colors, textures, and lighting, transforming dull photographs into jaw-dropping works of art with just a few clicks. Adobe’s suite of creative tools work in seamless harmony with Photoshop, allowing designers to amplify their creative potential.
With these AI-driven design software tools, the boundless human imagination can truly be manifested, and artistic dreams can become a tangible reality. It’s time to embark on a voyage of limitless creativity.
Planner 5D is an advanced AI-powered solution that allows users to bring their dream home or office space to life. With its cutting-edge technology, this software offers a seamless experience for architectural creativity and interior design.
One of the standout features of Planner 5D is its AI-assisted design capabilities. By simply describing your vision, the AI is able to effortlessly transform it into a stunning 3D representation. From intricate details to the overall layout, the AI understands your preferences and ensures that every aspect of your dream space aligns with your desires.
Gone are the days of struggling with pen and paper to create floor plans. Planner 5D simplifies the process, allowing users to easily design detailed and precise floor plans for their ideal space. Whether you prefer an open-concept layout or a series of interconnected rooms, this software provides the necessary tools to bring your architectural visions to life.
Planner 5D also excels in catering to every facet of interior design. With an extensive library of furniture and home décor items, users have endless options for furnishing and decorating their space. From stylish sofas and elegant dining tables to captivating wall art and lighting fixtures, Planner 5D offers a wide range of choices to suit individual preferences.
The user-friendly 2D/3D design tool within Planner 5D is a testament to its commitment to simplicity and innovation. Whether you are a novice designer or a seasoned professional, navigating through the interface is effortless, enabling you to create the perfect space for yourself, your family, or your business with utmost ease and precision.
For those who prefer a more hands-off approach, Planner 5D also provides the option to hire a professional designer through their platform. This feature is ideal for individuals who desire a polished and expertly curated space while leaving the intricate details to the experts. By collaborating with skilled designers, users can be confident that their dream home or office will become a reality, tailored to their unique taste and requirements.
Uizard has emerged as a game-changing tool for founders and designers alike, revolutionizing the creative process. This innovative software allows you to quickly bring your ideas to life by converting initial sketches into high-fidelity wireframes and stunning UI designs.
Gone are the days of tediously crafting wireframes and prototypes by hand. With Uizard, the transformation from a low-fidelity sketch to a polished, high-fidelity wireframe or UI design can happen in just minutes.
The speed and efficiency offered by this cutting-edge technology enable you to focus on refining your concepts and iterating through ideas at an unprecedented pace.
Whether you’re working on web apps, websites, mobile apps, or any digital platform, Uizard is a reliable companion that streamlines the design process. It is intuitively designed to cater to users of all backgrounds and skill levels, eliminating the need for extensive design expertise.
Uizard’s user-friendly interface opens up a world of possibilities, allowing you to bring your vision to life effortlessly. Its intuitive controls and extensive feature set empower you to create pixel-perfect designs that align with your unique style and brand identity.
Whether you’re a solo founder or part of a dynamic team, Uizard enables seamless collaboration, making it easy to share and iterate on designs.
One of the biggest advantages of Uizard is its ability to gather invaluable user feedback. By sharing your wireframes and UI designs with stakeholders, clients, or potential users, you can gain insights and refine your creations based on real-world perspectives.
This speeds up the decision-making process and ensures that your final product resonates with your target audience. Uizard truly transforms the way founders and designers approach the creative journey.
Autodesk Maya allows you to enter the extraordinary realm of 3D animation, transcending conventional boundaries. This powerful software grants you the ability to bring expansive worlds and intricate characters to life. Whether you are an aspiring animator, a seasoned professional, or a visionary storyteller, Maya provides the tools necessary to transform your creative visions into stunning reality.
With Maya, your imagination knows no bounds. Its powerful toolsets empower you to embark on a journey of endless possibilities. From grand cinematic tales to whimsical animated adventures, Maya serves as your creative canvas, waiting for your artistic touch to shape it.
Maya’s prowess is unmatched when it comes to handling complexity. It effortlessly handles characters and environments of any intricacy. Whether you aim to create lifelike characters with nuanced emotions or craft breathtaking landscapes that transcend reality, Maya’s capabilities rise to the occasion, ensuring that your artistic endeavors know no limits.
Designed to cater to professionals across various industries, Maya is the perfect companion for crafting high-quality 3D animations for movies, games, and more. It is a go-to choice for animators, game developers, architects, and designers, allowing them to tell stories and visualize concepts with stunning visual fidelity.
At the heart of Maya lies its engaging animation toolsets, carefully crafted to nurture the growth of your virtual world. From fluid character movements to dynamic environmental effects, Maya opens the doors to your creative sanctuary, enabling you to weave intricate tales that captivate audiences worldwide.
But the journey doesn’t end there. With Autodesk Maya, you are the architect of your digital destiny. Exploring the software reveals its seamless integration with other creative tools, expanding your capabilities even further. The synergy between Maya and its counterparts unlocks new avenues for innovation, granting you the freedom to experiment, iterate, and refine your creations with ease.
Autodesk 3Ds Max is an advanced tool that caters to architects, engineers, and professionals from various domains. Its cutting-edge features enable users to bring imaginative designs to life with astonishing realism. Architects can create stunningly realistic models of their architectural wonders, while engineers can craft intricate and precise 3D models of mechanical and industrial designs. This software is also sought after by creative professionals, as it allows them to visualize and communicate their concepts with exceptional clarity and visual fidelity. It is a versatile tool that can be used for crafting product prototypes and fashioning animated characters, making it a reliable companion for designers with diverse aspirations.
The user-friendly interface of Autodesk 3Ds Max is highly valued, as it facilitates a seamless and intuitive design process. Iteration becomes effortless with this software, empowering designers to refine their creations towards perfection. In the fast-paced world of business and design, the ability to cater to multiple purposes is invaluable, and Autodesk 3Ds Max stands tall as a versatile and adaptable solution, making it a coveted asset for businesses and individuals alike. Its potential to enhance visual storytelling capabilities unlocks a new era of creativity and communication.
Foyr Neo is another powerful software that speeds up the design process significantly. Compared to other tools, it allows design ideas to be transformed into reality in a fraction of the time. With a user-friendly interface and intuitive controls, Foyr Neo simplifies every step of the design journey, from floor plans to finished renders. This software becomes an extension of the user’s creative vision, manifesting remarkable designs with ease. Foyr Neo also provides a thriving community and comprehensive training resources, enabling designers to connect, share insights, and unlock the full potential of the software. By integrating various design functionalities within a single platform, Foyr Neo streamlines workflows, saving precious time and effort.
Let’s Enhance is a cutting-edge software that increases image resolution up to 16 times without compromising quality. It eliminates the need for tedious manual editing, allowing users to enhance their photos swiftly and efficiently. Whether it’s professional photographers seeking crisper images for print or social media enthusiasts enlarging visuals, Let’s Enhance delivers exceptional results consistently. By automating tasks like resolution enhancement, color correction, and lighting adjustments, this software relieves users of post-processing burdens. It frees up time to focus on core aspects of businesses or creative endeavors. Let’s Enhance benefits photographers, designers, artists, and marketers alike, enabling them to prepare images with impeccable clarity and sharpness. It also aids in refining color palettes, breathing new life into images, and balancing lighting for picture-perfect results. The software empowers users to create visuals that captivate audiences and leave a lasting impression, whether through subtle adjustments or dramatic transformations.
Foyr Neo revolutionizes the design process, offering a professional solution that transforms your ideas into reality efficiently and effortlessly. Unlike other software tools, Foyr Neo significantly reduces the time spent on design projects, allowing you to witness the manifestation of your creative vision in a fraction of the time.
Say goodbye to the frustration of complex design interfaces and countless hours devoted to a single project. Foyr Neo provides a user-friendly interface that simplifies every step, from floor plan to finished render. Its intuitive controls and seamless functionality make the software an extension of your creative mind, empowering you to create remarkable designs with ease.
The benefits of Foyr Neo extend beyond the software itself. It fosters a vibrant community of designers and offers comprehensive training resources. This collaborative environment allows you to connect with fellow designers, exchange insights, and draw inspiration from a collective creative pool. With ample training materials and support, you can fully unlock the software’s potential, expanding your design horizons.
Gone are the days of juggling multiple tools for a single project. Foyr Neo serves as the all-in-one solution for your design needs, integrating various functionalities within a single platform. This streamlines your workflow, saving you valuable time and effort. With Foyr Neo, you can focus on the art of design, uninterrupted by the burdens of managing multiple software tools.
Let’s Enhance is a cutting-edge software that offers a remarkable increase in image resolution of up to 16 times, without compromising quality. Say goodbye to tedious manual editing and hours spent enhancing images pixel by pixel. Let’s Enhance simplifies the process, providing a swift and efficient solution to elevate your photos’ quality with ease.
Whether you’re a professional photographer looking for crisper prints or a social media enthusiast wanting to enlarge your visuals, Let’s Enhance promises to deliver the perfect shot every time. Its proficiency in improving image resolution, colors, and lighting automatically alleviates the burden of post-processing. By trusting the intelligent algorithms of Let’s Enhance, you can focus more on the core aspects of your business or creative endeavors.
Let’s Enhance caters to a wide range of applications. Photographers, designers, artists, and marketers can all benefit from this powerful tool. Imagine effortlessly preparing your images for print, knowing they’ll boast impeccable clarity and sharpness. Envision your social media posts grabbing attention with larger-than-life visuals, thanks to Let’s Enhance’s seamless enlargement capabilities.
But Let’s Enhance goes beyond just resolution enhancement. It also becomes a reliable ally in refining color palettes, breathing new life into dull or faded images, and balancing lighting for picture-perfect results. Whether it’s subtle adjustments or dramatic transformations, the software empowers you to create visuals that captivate audiences and leave a lasting impression.
AI design software is constantly evolving, empowering creators to exceed the limitations of design and art. It facilitates experimentation, iteration, and problem-solving, enabling seamless workflows and creative breakthroughs.
By embracing the power of AI design software, you can unlock new realms of creativity that were once uncharted. This software liberates you from the confines of traditional platforms, encouraging you to explore unexplored territories and innovate.
The surge in popularity of AI design software signifies a revolutionary era in creative expression. To fully leverage its potential, it is crucial to understand its essential features, formats, and capabilities. By familiarizing yourself with this technology, you can maximize its benefits and stay at the forefront of artistic innovation.
Embrace AI design software as a catalyst for your artistic evolution. Let it inspire you on a journey of continuous improvement and artistic discovery. With AI as your companion, the future of design and creativity unfolds, presenting limitless possibilities for those bold enough to embrace its potential.
Thanks for listening to today’s episode where we explored the power of AI-driven design software, including Adobe Photoshop CC’s wide range of tools, the precision of Planner 5D for designing dream spaces, the fast conversion of sketches with Uizard, the lifelike animation capabilities of Autodesk Maya, the realistic modeling with Autodesk 3Ds Max, the all-in-one solution of Foyr Neo, and the image enhancement features of Let’s Enhance. Join us at the next episode and don’t forget to subscribe!
AI creates lifelike 3D experiences from your phone video
Local Llama
For businesses, local LLMs offer competitive performance, cost reduction, dependability, and flexibility.
AI-Created Art Denied Copyright Protection
A recent court ruling has confirmed that artworks created by artificial intelligence (AI) systems are not eligible for copyright protection in the United States. The decision could have significant implications for the entertainment industry, which has been exploring the use of generative AI to create content.
Daily AI Update News from OpenCopilot, Google, Luma AI, AI2, and more
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover OpenCopilot, Google’s personalized text generation, Luma AI’s Flythroughs app, the impact of US court ruling on AI artworks, Scale’s Test & Evaluation for LLMs, the wide range of AI applications discussed, and the Wondercraft AI platform for podcasting, along with some promotional offers and the book “AI Unraveled”.
Have you heard about OpenCopilot? It’s an incredible tool that allows you to have your very own AI copilot for your product. And the best part? It’s super easy to set up, taking less than 5 minutes to get started.
One of the great features of OpenCopilot is its seamless integration with your existing APIs. It can execute API calls whenever needed, making it incredibly efficient. It utilizes Language Models (LLMs) to determine if a user’s request requires making an API call. If it does, OpenCopilot cleverly decides which endpoint to call and passes the appropriate payload based on the API definition.
But why is this innovation so important? Well, think about it. Shopify has its own AI-powered sidekick, Microsoft has Copilot variations for Windows and Bing, and even GitHub has its own Copilot. These copilots enhance the functionality and experience of these individual products.
Now, with OpenCopilot, every SaaS product can benefit from having its own tailored AI copilot. This means that no matter what industry you’re in or what kind of product you have, OpenCopilot can empower you to take advantage of this exciting technology and bring your product to the next level.
So, why wait? Get started with OpenCopilot today and see how it can transform your product into something truly extraordinary!
Google’s latest research aims to enhance the text generation capabilities of Language Models (LLMs) by personalizing the generated content. LLMs are already proficient at processing and synthesizing text, but personalized text generation is a new frontier. The proposed approach draws inspiration from writing education practices and employs a multistage and multitask framework.
The framework consists of several stages, including retrieval, ranking, summarization, synthesis, and generation. Additionally, the researchers introduce a multitask setting that improves the model’s generation ability. This approach is based on the observation that a student’s reading proficiency and writing ability often go hand in hand.
The research evaluated the effectiveness of the proposed method on three diverse datasets representing different domains. The results showcased significant improvements compared to various baselines.
So, why is this research important? Customizing style and content is crucial in various domains such as personal communication, dialogue, marketing copies, and storytelling. However, achieving this level of customization through prompt engineering or custom instructions alone has proven challenging. This study emphasizes the potential of learning from how humans accomplish tasks and applying those insights to enhance LLMs’ abilities.
By enabling LLMs to generate personalized text, Google’s research opens doors for more effective and versatile applications across a wide range of industries and use cases.
Have you ever wanted to create stunning 3D videos that look like they were captured by a professional drone, but without the need for expensive equipment and a crew? Well, now you can with Luma AI’s new app called Flythroughs. This app allows you to easily generate photorealistic, cinematic 3D videos right from your iPhone with just one touch.
Flythroughs takes advantage of Luma’s breakthrough NeRF and 3D generative AI technology, along with a new path generation model that automatically creates smooth and dramatic camera moves. All you have to do is record a video like you’re showing a place to a friend, and then hit the “Generate” button. The app does the rest, turning your video into a stunning 3D experience.
This is a significant development in the world of 3D content creation because it democratizes the process, making it more accessible and cost-efficient. Now, individuals and businesses across various industries can easily create captivating digital experiences using AI technology.
Speaking of accessibility and cost reduction, there’s another interesting development called local LLMs. These models, such as Llama-2 and its variants, offer competitive performance, dependability, and flexibility for businesses. With local deployment, businesses have more control, customization options, and the ability to fully utilize the capabilities of the LLM models.
By running Llama models locally, businesses can avoid the limitations and high expenses associated with commercial APIs. They can also integrate the models with existing systems, making AI more accessible and beneficial for their specific needs.
So, whether you’re looking to create breathtaking 3D videos or deploy AI models locally, these advancements are making it easier and more cost-effective for everyone to tap into the power of AI.
Recently, a court ruling in the United States has clarified that artworks created by artificial intelligence (AI) systems do not qualify for copyright protection. This decision has significant implications for the entertainment industry, which has been exploring the use of generative AI to produce content.
The case involved Dr. Stephen Thaler, a computer scientist who claimed ownership of an artwork titled “A Recent Entrance to Paradise,” generated by his AI model called the Creativity Machine. Thaler applied to register the work as a work-for-hire, even though he had no direct involvement in its creation.
However, the U.S. Copyright Office (USCO) rejected Thaler’s application, stating that copyright law only protects works of human creation. They argued that human creativity is the foundation of copyrightability and that works generated by machines or technology without human input are not eligible for protection.
Thaler challenged this decision in court, arguing that AI should be recognized as an author when it meets the criteria for authorship and that the owner of the AI system should have the rights to the work.
However, U.S. District Judge Beryl Howell dismissed Thaler’s lawsuit, upholding the USCO’s position. The judge emphasized the importance of human authorship as a fundamental requirement of copyright law and referred to previous cases involving works created without human involvement, such as photographs taken by animals.
Although the judge acknowledged the challenges posed by generative AI and its impact on copyright protection, she deemed Thaler’s case straightforward due to his admission of having no role in the creation of the artwork.
Thaler plans to appeal the decision, marking the first ruling in the U.S. on the subject of AI-generated art. Legal experts and policymakers have been debating this issue for years. In March, the USCO provided guidance on registering works created by AI systems based on text prompts, stating that they generally lack protection unless there is substantial human contribution or editing.
This ruling could greatly affect Hollywood studios, which have been experimenting with generative AI to produce scripts, music, visual effects, and more. Without legal protection, studios may struggle to claim ownership and enforce their rights against unauthorized use. They may also face ethical and artistic dilemmas in using AI to create content that reflects human values and emotions.
Hey folks! Big news in the world of LLMs (that’s Language Model Models for the uninitiated). These little powerhouses have been creating quite a buzz lately, with their potential to revolutionize various sectors. But with great power comes great responsibility, and there’s been some concern about their behavior.
You see, LLMs can sometimes exhibit what we call “model misbehavior” and engage in black box behavior. Basically, they might not always behave the way we expect them to. And that’s where Scale comes in!
Scale, one of the leading companies in the AI industry, has recognized the need for a solution. They’ve just launched Test & Evaluation for LLMs. So, why is this such a big deal? Well, testing and evaluating LLMs is a real challenge. These models, like the famous GPT-4, can be non-deterministic, meaning they don’t always produce the same results for the same input. Not ideal, right?
To make things even more interesting, researchers have discovered that LLM jailbreaks can be automatically generated. Yikes! So, it’ll be fascinating to see if Scale can address these issues and provide a proper evaluation process for LLMs.
Stay tuned as we eagerly await the results of Scale’s Test & Evaluation for LLMs. It could be a game-changer for the future of these powerful language models.
So, let’s dive right into today’s AI news update! We have some exciting stories to share with you.
First up, we have OpenCopilot, which offers an AI Copilot for your own SaaS product. With OpenCopilot, you can integrate your product’s AI copilot and have it execute API calls whenever needed. It’s a great tool that uses LLMs to determine if the user’s request requires calling an API endpoint. Then, it decides which endpoint to call and passes the appropriate payload based on the given API definition.
In other news, Google has proposed a general approach for personalized text generation using LLMs. This approach, inspired by the practice of writing education, aims to improve personalized text generation. The results have shown significant improvements over various baselines.
Now, let me introduce you to an exciting app called Flythroughs. It allows you to create lifelike 3D experiences from your phone videos. With just one touch, you can generate cinematic videos that look like they were captured by a professional drone. No need for expensive equipment or a crew. Simply record the video like you’re showing a place to a friend, hit generate, and voila! You’ve got an amazing video right on your iPhone.
Moving on, it seems that big brands like Nestlé and Mondelez are increasingly using AI-generated ads. They see generative AI as a way to make the ad creation process less painful and costly. However, there are still concerns about whether to disclose that the ads are AI-generated, copyright protections for AI ads, and potential security risks associated with using AI.
In the world of language models, AI2 (Allen Institute for AI) has released an impressive open dataset called Dolma. This dataset is the largest one yet and can be used to train powerful and useful language models like GPT-4 and Claude. The best part is that it’s free to use and open to inspection.
Lastly, the former CEO of Machine Zone has launched BeFake, an AI-based social media app. This app offers a refreshing alternative to the conventional reality portrayed on existing social media platforms. You can now find it on both the App Store and Google Play.
That wraps up today’s AI update news! Stay tuned for more exciting updates in the future.
Hey there, AI Unraveled podcast listeners! Are you ready to dive deeper into the exciting world of artificial intelligence? Well, we’ve got some great news for you. Etienne Noumen, the brilliant mind behind “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” has just released his essential book.
With this book, you can finally unlock the mysteries of AI and get answers to all your burning questions. Whether you’re a tech enthusiast or just curious about the impact of AI on our world, this book has got you covered. It’s packed with insights, explanations, and real-world examples that will expand your understanding and leave you feeling informed and inspired.
And the best part? You can easily grab a copy of “AI Unraveled” from popular platforms like Shopify, Apple, Google, or Amazon. So, no matter where you prefer to get your digital or physical books, it’s all there for you.
So, get ready to unravel the complexities of artificial intelligence and become an AI expert. Head on over to your favorite platform and grab your copy of “AI Unraveled” today! Don’t miss out on this opportunity to broaden your knowledge. Happy reading!
On today’s episode, we discussed OpenCopilot’s AI sidekick that empowers innovation, Google’s method for personalized text generation, Luma AI’s app Flythroughs for creating professional 3D videos, the US court ruling on AI artworks and copyright protection, Scale’s Test & Evaluation for LLMs, the latest updates from AI2, and the Wondercraft AI platform for starting your own podcast with hyper-realistic AI voices – don’t forget to use code AIUNRAVELED50 for a 50% discount, and grab the book “AI Unraveled” by Etienne Noumen at Shopify, Apple, Google, or Amazon. Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!
Embark on an insightful journey with Djamgatech Education as we delve into the intricacies of the OpenAI code interpreter – a groundbreaking tool that’s revolutionizing the way we perceive and interact with coding. By bridging the gap between human language and programming code, how does this AI tool stand out, and what potential challenges does it present? Let’s find out!
In this podcast, explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT and the recent merger of Google Brain and DeepMind to the latest developments in generative AI, we’ll provide you with a comprehensive update on the AI landscape.
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover the applications and benefits of the OpenAI code interpreter, its pre-training and fine-tuning phases, its ability to generate code and perform various tasks, as well as its benefits and drawbacks. We’ll also discuss the key considerations when using the code interpreter, such as understanding limitations, prioritizing data security, and complementing human coders.
OpenAI, one of the leaders in artificial intelligence, has developed a powerful tool called the OpenAI code interpreter. This impressive model is trained on vast amounts of data to process and generate programming code. It’s basically a bridge between human language and computer code, and it comes with a whole range of applications and benefits.
What makes the code interpreter so special is that it’s built on advanced machine learning techniques. It combines the strengths of both unsupervised and supervised learning, resulting in a model that can understand complex programming concepts, interpret different coding languages, and generate responses that align with coding practices. It’s a big leap forward in AI capabilities!
The code interpreter utilizes a technique called reinforcement learning from human feedback (RLHF). This means it continuously refines its performance by incorporating feedback from humans into its learning process. During training, the model ingests a vast amount of data from various programming languages and coding concepts. This background knowledge allows it to make the best possible decisions when faced with new situations.
One amazing thing about the code interpreter is that it isn’t limited to any specific coding language or style. It’s been trained on a diverse range of data from popular languages like Python, JavaScript, and C, to more specialized ones like Rust or Go. It can handle it all! And it doesn’t just understand what the code does, it can also identify bugs, suggest improvements, offer alternatives, and even help design software structures. It’s like having a coding expert at your fingertips!
The OpenAI code interpreter’s ability to provide insightful and relevant responses based on input sets it apart from other tools. It’s a game-changer for those in the programming world, making complex tasks easier and more efficient.
The OpenAI code interpreter is an impressive tool that utilizes artificial intelligence (AI) to interpret and generate programming code. Powered by machine learning principles, this AI model continuously improves its capabilities through iterative training.
The code interpreter primarily relies on a RLHF model, which goes through two crucial phases: pre-training and fine-tuning. During pre-training, the model is exposed to an extensive range of programming languages and code contexts, enabling it to develop a general understanding of language, code syntax, semantics, and conventions. In the fine-tuning phase, the model uses a curated dataset and incorporates human feedback to align its responses with human-like interpretations.
Throughout the fine-tuning process, the model’s outputs are compared, and rewards are assigned based on their accuracy in line with the desired responses. This enables the model to learn and improve over time, constantly refining its predictions.
It’s important to note that the code interpreter operates without true understanding or consciousness. Instead, it identifies patterns and structures within the training data to generate or interpret code. When presented with a piece of code, it doesn’t comprehend its purpose like a human would. Instead, it analyzes the code’s patterns, syntax, and structure based on its extensive training data to provide a human-like interpretation.
One remarkable feature of the OpenAI code interpreter is its ability to understand natural language inputs and generate appropriate programming code. This makes the tool accessible to users without coding expertise, allowing them to express their needs in plain English and harness the power of programming.
The OpenAI code interpreter is a super handy tool that can handle a wide range of tasks related to code interpretation and generation. Let me walk you through some of the things it can do.
First up, code generation. If you have a description in plain English, the code interpreter can whip up the appropriate programming code for you. It’s great for folks who may not have extensive programming knowledge but still need to implement a specific function or feature.
Next, we have code review and optimization. The model is able to review existing code and suggest improvements, offering more efficient or streamlined alternatives. So if you’re a developer looking to optimize your code, this tool can definitely come in handy.
Bug identification is another nifty feature. The code interpreter can analyze a piece of code and identify any potential bugs or errors. Not only that, it can even pinpoint the specific part of the code causing the problem and suggest ways to fix it. Talk about a lifesaver!
The model can also explain code to you. Simply feed it a snippet of code and it will provide a natural language explanation of what the code does. This is especially useful for learning new programming concepts, understanding complex code structures, or even just documenting your code.
Need to translate code from one programming language to another? No worries! The code interpreter can handle that too. Whether you want to replicate a Python function in JavaScript or any other language, this model has got you covered.
If you’re dealing with unfamiliar code, the model can predict the output when that code is run. This comes in handy for understanding what the code does or even for debugging purposes.
Lastly, the code interpreter can even generate test cases for you. Say you need to test a particular function or feature, the model can generate test cases to ensure your software is rock solid.
Keep in mind, though, that while the OpenAI code interpreter is incredibly capable, it’s not infallible. Sometimes it may produce inaccurate or unexpected outputs. But as machine learning models evolve and improve, we can expect the OpenAI code interpreter to become even more versatile and reliable in handling different code-related tasks.
The OpenAI code interpreter is a powerful tool that comes with a lot of benefits. One of its main advantages is its ability to understand and generate code from natural language descriptions. This makes it easier for non-programmers to leverage coding solutions, opening up a whole new world of possibilities for them. Additionally, the interpreter is versatile and can handle various tasks, such as bug identification, code translation, and optimization. It also supports multiple programming languages, making it accessible to a wide range of developers.
Another benefit is the time efficiency it brings. The code interpreter can speed up tasks like code review, bug identification, and test case generation, freeing up valuable time for developers to focus on more complex tasks. Furthermore, it bridges the gap between coding and natural language, making programming more accessible to a wider audience. It’s a continuous learning model that can improve its performance over time through iterative feedback from humans.
However, there are some drawbacks to be aware of. The code interpreter has limited understanding compared to a human coder. It operates based on patterns learned during training, lacking an intrinsic understanding of the code. Its outputs also depend on the quality and diversity of its training data, meaning it may struggle with interpreting unfamiliar code constructs accurately. Error propagation is another risk, as a mistake made by the model could lead to more significant issues down the line.
There’s also the risk of over-reliance on the interpreter, which could lead to complacency among developers who might skip the crucial step of thoroughly checking the code themselves. Finally, ethical and security concerns arise with the automated generation and interpretation of code, as potential misuse raises questions about ethics and security.
In conclusion, while the OpenAI code interpreter has numerous benefits, it’s crucial to use it responsibly and be aware of its limitations.
When it comes to using the OpenAI code interpreter, there are a few key things to keep in mind. First off, it’s important to understand the limitations of the model. While it’s pretty advanced and can handle various programming languages, it doesn’t truly “understand” code like a human does. Instead, it recognizes patterns and makes extrapolations, which means it can sometimes make mistakes or provide unexpected outputs. So, it’s always a good idea to approach its suggestions with a critical mind.
Next, data security and privacy are crucial considerations. Since the model can process and generate code, it’s important to handle any sensitive or proprietary code with care. OpenAI retains API data for around 30 days, but they don’t use it to improve the models. It’s advisable to stay updated on OpenAI’s privacy policies to ensure your data is protected.
Although AI tools like the code interpreter can be incredibly helpful, human oversight is vital. While the model can generate syntactically correct code, it may unintentionally produce harmful or unintended results. Human review is necessary to ensure code accuracy and safety.
Understanding the training process of the code interpreter is also beneficial. It uses reinforcement learning from human feedback and is trained on a vast amount of public text, including programming code. Knowing this can provide insights into how the model generates outputs and why it might sometimes yield unexpected results.
To fully harness the power of the OpenAI code interpreter, it’s essential to explore and experiment with it. The more you use it, the more you’ll become aware of its strengths and weaknesses. Try it out on different tasks, and refine your prompts to achieve the desired results.
Lastly, it’s important to acknowledge that the code interpreter is not meant to replace human coders. It’s a tool that can enhance human abilities, expedite development processes, and aid in learning and teaching. However, the creativity, problem-solving skills, and nuanced understanding of a human coder cannot be replaced by AI at present.
Thanks for listening to today’s episode where we discussed the OpenAI code interpreter, an advanced AI model that understands and generates programming code, its various applications and benefits, as well as its limitations and key considerations for use. I’ll see you guys at the next one and don’t forget to subscribe!
The importance of making superintelligent small LLMs
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover Genmo, D-ID, LeiaPix Converter, InstaVerse, Sketch, and NeROIC, advancements in computer science for 3D modeling, Google’s new AI system Gemini, and its potential to revolutionize the AI market.
Let me introduce you to some of the top AI image-to-video generators of 2023. These platforms use artificial intelligence to transform written text or pictures into visually appealing moving images.
First up, we have Genmo. This AI-driven video generator goes beyond the limitations of a page and brings your text to life. It combines algorithms from natural language processing, picture recognition, and machine learning to create personalized videos. You can include text, pictures, symbols, and even emojis in your videos. Genmo allows you to customize background colors, characters, music, and other elements to make your videos truly unique. Once your video is ready, you can share it on popular online platforms like YouTube, Facebook, and Twitter. This makes Genmo a fantastic resource for companies, groups, and individuals who need to create interesting movies quickly and affordably.
Next is D-ID, a video-making platform powered by AI. With the help of Stable Diffusion and GPT-3, D-ID’s Creative Reality Studio makes it incredibly easy to produce professional-quality videos from text. The platform supports over a hundred languages and offers features like Live Portrait and Speaking Portrait. Live Portrait turns still images into short films, while Speaking Portrait gives a voice to written or spoken text. D-ID’s API has been refined with the input of thousands of videos, ensuring high-quality visuals. It has been recognized by industry events like Digiday, SXSW, and TechCrunch for its ability to provide users with top-notch videos at a fraction of the cost of traditional approaches.
Last but not least, we have the LeiaPix Converter. This web-based service transforms regular photographs into lifelike 3D Lightfield photographs using artificial intelligence. Simply select your desired output format and upload your picture to LeiaPix Converter. You can choose from formats like Leia Image Format, Side-by-Side 3D, Depth Map, and Lightfield Animation. The output is of great quality and easy to use. This converter is a fantastic way to give your pictures a new dimension and create unique visual compositions. However, keep in mind that the conversion process may take a while depending on the size of the image, and the quality of the original photograph will impact the final results. As the LeiaPix Converter is currently in beta, there may be some issues or functional limitations to be aware of.
Have you ever wanted to create your own dynamic 3D environments? Well, now you can with the new open-source framework called instaVerse! Building your own virtual world has never been easier. With instaVerse, you can generate backgrounds based on AI cues and then customize them to your liking. Whether you want to explore a forest with towering trees and a flowing river or roam around a bustling city or even venture into outer space with spaceships, instaVerse has got you covered. And it doesn’t stop there – you can also create your own avatars to navigate through your universe. From humans to animals to robots, there’s no limit to who can be a part of your instaVerse cast of characters.
But wait, there’s more! Let’s talk about Sketch, a cool web app that turns your sketches into animated GIFs. It’s a fun and simple way to bring your drawings to life and share them on social media or use them in other projects. With Sketch, you can easily add animation effects to your sketches, reposition and recolor objects, and even add custom sound effects. It’s a fantastic program for both beginners and experienced artists, allowing you to explore the basics of animation while showcasing your creativity.
Lastly, let’s dive into NeROIC, an incredible AI technology that can reconstruct 3D models from photographs. This revolutionary technology has the potential to transform how we perceive and interact with three-dimensional objects. Whether you want to create a 3D model from a single image or turn a video into an interactive 3D environment, NeROIC makes it easier and faster than ever before. Say goodbye to complex modeling software and hello to the future of 3D modeling.
So whether you’re interested in creating dynamic 3D worlds, animating your sketches, or reconstructing 3D models from photos, these innovative tools – instaVerse, Sketch, and NeROIC – have got you covered. Start exploring, creating, and sharing your unique creations today!
So, there’s this really cool discipline in computer science that’s making some amazing progress. It’s all about creating these awesome 3D models from just regular 2D photographs. And let me tell you, the results are mind-blowing!
This cutting-edge technique, called DPT Depth Estimation, uses deep learning-based algorithms to train point clouds and 3D meshes. Essentially, it reads the depth data from a photograph and generates a point cloud model of the object in 3D. It’s like magic!
What’s fascinating about DPT Depth Estimation is that it uses monocular photos to feed a deep convolutional network that’s already been pre-trained on all sorts of scenes and objects. The data is collected from the web, and then, voila! A point cloud is created, which can be used to build accurate 3D models.
The best part? DPT’s performance can even surpass that of a human using traditional techniques like stereo-matching and photometric stereo. Plus, it’s super fast, making it a promising candidate for real-time 3D scene reconstruction. Impressive stuff, right?
But hold on, there’s even more to get excited about. Have you heard of RODIN? It’s all the rage in the world of artificial intelligence. This incredible technology can generate 3D digital avatars faster and easier than ever before.
Imagine this – you provide a simple photograph, and RODIN uses its AI wizardry to create a convincing 3D avatar that looks just like you. It’s like having your own personal animated version in the virtual world. And the best part? You get to experience these avatars in a 360-degree view. Talk about truly immersive!
So, whether it’s creating jaw-dropping 3D models from 2D photographs with DPT Depth Estimation or bringing virtual avatars to life with RODIN, the future of artificial intelligence is looking pretty incredible.
Gemini, the AI system developed by Google, has been the subject of much speculation. The name itself has multiple meanings and allusions, suggesting a combination of text and image processing and the integration of different perspectives and approaches. Google’s vast amount of data, which includes over 130 exabytes of information, gives them a significant advantage in the AI field. Their extensive research output in artificial intelligence, with over 3300 publications in 2020 and 2021 alone, further solidifies their position as a leader in the industry.
Some of Google’s groundbreaking developments include AlphaGo, the AI that defeated the world champion in the game of Go, and BERT, a breakthrough language model for natural language processing. Other notable developments include PaLM, an enormous language model with 540 billion parameters, and Meena, a conversational AI.
With the introduction of Gemini, Google aims to combine their AI developments and vast data resources into one powerful system. Gemini is expected to have multiple modalities, including text, image, audio, video, and more. The system is said to have been trained with YouTube transcripts and will learn and improve through user interactions.
The release of Gemini this fall will give us a clearer picture of its capabilities and whether it can live up to the high expectations. As a result, the AI market is likely to experience significant changes, with Google taking the lead and putting pressure on competitors like OpenAI, Anthropic, Microsoft, and startups in the industry. However, there are still unanswered questions about data security and specific features of Gemini that need to be addressed.
The whole concept of making superintelligent small LLMs is incredibly significant. Take Google’s Gemini, for instance. This AI model is about to revolutionize the field of AI, all thanks to its vast dataset that it’s been trained on. But here’s the game-changer: Google’s next move will be to enhance Gemini’s intelligence by moving away from relying solely on data. Instead, it will start focusing on principles for logic and reasoning.
When AI’s intelligence is rooted in principles, the need for massive amounts of data during training becomes a thing of the past. That’s a pretty remarkable milestone to achieve! And once this happens, it levels the playing field for other competitive or even stronger AI models to emerge alongside Gemini.
Just imagine the possibilities when that day comes! With a multitude of highly intelligent models in the mix, our world will witness an incredible surge in intelligence. And this is not some distant future—it’s potentially just around the corner. So, brace yourself for a world where AI takes a giant leap forward and everything becomes remarkably intelligent. It’s an exciting prospect that may reshape our lives in ways we can’t even fully fathom yet.
Thanks for listening to today’s episode where we covered a range of topics including AI video generators like Genmo and D-ID, the LeiaPix Converter that can transform regular photos into immersive 3D Lightfield environments, easy 3D world creation with InstaVerse, Sketch’s web app for turning sketches into animated GIFs, advancements in computer science for 3D modeling, and the potential of Google’s new AI system Gemini to revolutionize the AI market by relying on principles instead of data – I’ll see you guys at the next one and don’t forget to subscribe!
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover top AI jobs including AI product manager, AI research scientist, big data engineer, BI developer, computer vision engineer, data scientist, machine learning engineer, natural language processing engineer, robotics engineer, and software engineer.
Let’s dive into the world of AI jobs and discover the exciting opportunities that are shaping the future. Whether you’re interested in leading teams, developing algorithms, working with big data, or gaining insights into business processes, there’s a role that suits your skills and interests.
First up, we have the AI product manager. Similar to other program managers, this role requires leadership skills to develop and launch AI products. While it may sound complex, the responsibilities of a product manager remain similar, such as team coordination, scheduling, and meeting milestones. However, AI product managers need to have a deep understanding of AI applications, including hardware, programming languages, data sets, and algorithms. Creating an AI app is a unique process, with differences in structure and development compared to web apps.
Next, we have the AI research scientist. These computer scientists study and develop new AI algorithms and techniques. Programming is just a fraction of what they do. Research scientists collaborate with other experts, publish research papers, and speak at conferences. To excel in this field, a strong foundation in computer science, mathematics, and statistics is necessary, usually obtained through advanced degrees.
Another field that is closely related to AI is big data engineering. Big data engineers design, build, test, and maintain complex data processing systems. They work with tools like Hadoop, Hive, Spark, and Kafka to handle large datasets. Similar to AI research scientists, big data engineers often hold advanced degrees in mathematics and statistics, as it is crucial for creating data pipelines that can handle massive amounts of information.
Lastly, we have the business intelligence developer. BI is a data-driven discipline that existed even before the AI boom. BI developers utilize data analytics platforms, reporting tools, and visualization techniques to transform raw data into meaningful insights for informed decision-making. They work with coding languages like SQL, Python, and tools like Tableau and Power BI. A strong understanding of business processes is vital for BI developers to improve organizations through data-driven insights.
So, whether you’re interested in managing AI products, conducting research, handling big data, or unlocking business insights, there’s a fascinating AI job waiting for you in this rapidly growing industry.
A computer vision engineer is a developer who specializes in writing programs that utilize visual input sensors, algorithms, and systems. These systems see the world around them and act accordingly, like self-driving cars and facial recognition. They use languages like C++ and Python, along with visual sensors such as Mobileye. They work on tasks like object detection, image segmentation, facial recognition, gesture recognition, and scenery understanding.
On the other hand, a data scientist is a technology professional who collects, analyzes, and interprets data to solve problems and drive decision-making within an organization. They use data mining, big data, and analytical tools. By deriving business insights from data, data scientists help improve sales and operations, make better decisions, and develop new products, services, and policies. They also use predictive modeling to forecast events like customer churn and data visualization to display research results visually. Some data scientists also use machine learning to automate these tasks.
Next, a machine learning engineer is responsible for developing and implementing machine learning training algorithms and models. They have advanced math and statistics skills and usually have degrees in computer science, math, or statistics. They often continue training through certification programs or master’s degrees in machine learning. Their expertise is essential for training machine learning models, which is the most processor- and computation-intensive aspect of machine learning.
A natural language processing (NLP) engineer is a computer scientist who specializes in the development of algorithms and systems that understand and process human language input. NLP projects involve tasks like machine translation, text summarization, answering questions, and understanding context. NLP engineers need to understand both linguistics and programming.
Meanwhile, a robotics engineer designs, develops, and tests software for robots. They may also utilize AI and machine learning to enhance robotic system performance. Robotics engineers typically have degrees in engineering, such as electrical, electronic, or mechanical engineering.
Lastly, software engineers cover various activities in the software development chain, including design, development, testing, and deployment. It is rare to find someone proficient in all these aspects, so most engineers specialize in one discipline.
In today’s episode, we discussed the top AI jobs, including AI product manager, AI research scientist, big data engineer, and BI developer, as well as the roles of computer vision engineer, data scientist, machine learning engineer, natural language processing engineer, robotics engineer, and software engineer. Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!
Recent advancements in AI have developed a model that can assist in determining the starting point of a patient’s cancer, a crucial step in identifying the most effective treatment method.
AI’s Defense Against Image Manipulation In the era of deepfakes and manipulated images, AI emerges as a protector. New algorithms are being developed to detect and counter AI-generated image alterations.
Streamlining Robot Control Learning Researchers have uncovered a more straightforward approach to teach robots control mechanisms, making the integration of robotics into various industries more efficient.
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Transcript:
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover the improvements made by GPT-4 in content moderation and efficiency, the superior performance of the Shepherd language model in critiquing and refining language model outputs, Microsoft’s launch of private ChatGPT for Azure OpenAI, Google’s use of AI in generating web content summaries, Nvidia’s stock rise driven by strong earnings and AI potential, the impact of transportation choice on inefficiencies, the various ways AI aids in fields such as cancer research, image manipulation defense, robot control learning, robotics training acceleration, writing productivity, data privacy, as well as the updates from Google, Amazon, and WhatsApp in their AI-driven services.
Hey there, let’s dive into some fascinating news. OpenAI has big plans for its GPT-4. They’re aiming to tackle the challenge of content moderation at scale with this advanced AI model. In fact, they’re already using GPT-4 to develop and refine their content policies, which offers a bunch of advantages.
First, GPT-4 provides consistent judgments. This means that content moderation decisions will be more reliable and fair. On top of that, it speeds up policy development, reducing the time it takes from months to mere hours.
But that’s not all. GPT-4 also has the potential to improve the well-being of content moderators. By assisting them in their work, the AI model can help alleviate some of the pressure and stress that comes with moderating online content.
Why is this a big deal? Well, platforms like Facebook and Twitter have long struggled with content moderation. It’s a massive undertaking that requires significant resources. OpenAI’s approach with GPT-4 could offer a solution for these giants, as well as smaller companies that may not have the same resources.
So, there you have it. GPT-4 holds the promise of improving content moderation and making it more efficient. It’s an exciting development that could bring positive changes to the digital landscape.
A language model called Shepherd has made significant strides in critiquing and refining the outputs of other language models. Despite being smaller in size, Shepherd’s critiques are just as good, if not better, than those generated by larger models such as ChatGPT. In fact, when compared against competitive alternatives, Shepherd achieves an impressive win rate of 53-87% when pitted against GPT-4.
What sets Shepherd apart is its exceptional performance in human evaluations, where it outperforms other models and proves to be on par with ChatGPT. This is a noteworthy achievement, considering its smaller size. Shepherd’s ability to provide high-quality feedback and offer valuable suggestions makes it a practical tool for enhancing language model generation.
Now, why does this matter? Well, despite being smaller in scale, Shepherd has managed to match or even exceed the critiques generated by larger models like ChatGPT. This implies that size does not necessarily determine the effectiveness or quality of a language model. Shepherd’s impressive win rate against GPT-4, alongside its success in human evaluations, highlights its potential for improving language model generation. With Shepherd, the capability to refine and enhance language models becomes more accessible, offering practical value to users.
Microsoft has just announced the launch of its private ChatGPT on Azure, making conversational AI more accessible to developers and businesses. With this new offering, organizations can integrate ChatGPT into their applications, utilizing its capabilities to power chatbots, automate emails, and provide conversation summaries.
Starting today, Azure OpenAI users can access a preview of ChatGPT, with pricing set at $0.002 for 1,000 tokens. Additionally, Microsoft is introducing the Azure ChatGPT solution accelerator, an enterprise option that offers a similar user experience but acts as a private ChatGPT.
There are several key benefits that Microsoft Azure ChatGPT brings to the table. Firstly, it emphasizes data privacy by ensuring built-in guarantees and isolation from OpenAI-operated systems. This is crucial for organizations that handle sensitive information. Secondly, it offers full network isolation and enterprise-grade security controls, providing peace of mind to users. Finally, it enhances business value by integrating internal data sources and services like ServiceNow, thereby streamlining operations and increasing productivity.
This development holds significant importance as it addresses the growing demand for ChatGPT in the market. Microsoft’s focus on security simplifies access to AI advantages for enterprises, while also enabling them to leverage features like code editing, task automation, and secure data sharing. With the launch of private ChatGPT on Azure, Microsoft is empowering organizations to tap into the potential of conversational AI with confidence.
So, Google is making some exciting updates to its search engine. They’re experimenting with a new feature that uses artificial intelligence to generate summaries of long-form web content. Basically, it will give you the key points of an article without you having to read the whole thing. How cool is that?
Now, there’s a slight catch. This summarization tool won’t work on content that’s marked as paywalled by publishers. So, if you stumble upon an article behind a paywall, you’ll still have to do a little extra digging. But hey, it’s a step in the right direction, right?
This new feature is currently being launched as an early experiment in Google’s opt-in Search Labs program. For now, it’s only available on the Google app for Android and iOS. So, if you’re an Android or iPhone user, you can give it a try and see if it helps you get the information you need in a quicker and more efficient way.
In other news, Nvidia’s stocks are on the rise. Investors are feeling pretty optimistic about their GPUs remaining dominant in powering large language models. In fact, their stock has already risen by 7%. Morgan Stanley even reiterated Nvidia as a “Top Pick” because of its strong earnings, the shift towards AI spending, and the ongoing supply-demand imbalance.
Despite some recent fluctuations, Nvidia’s stock has actually tripled since 2023. Analysts are expecting some long-term benefits from AI and favorable market conditions. So, things are looking pretty good for Nvidia right now.
On a different note, let’s talk about the strength and realism of AI models. These models are incredibly powerful when it comes to computational abilities, but there’s a debate going on about how well they compare to the natural intelligence of living organisms. Are they truly accurate representations or just simulations? It’s an interesting question to ponder.
Finally, let’s dive into the paradox of choice in transportation systems. Having more choices might sound great, but it can actually lead to complexity and inefficiencies. With so many options, things can get a little chaotic and even result in gridlocks. It’s definitely something to consider when designing transportation systems for the future.
So, that’s all the latest news for now. Keep an eye out for those Google search updates and see if they make your life a little easier. And hey, if you’re an Nvidia stockholder, things are definitely looking up. Have a great day!
Have you heard about the recent advancements in AI that are revolutionizing cancer treatment? AI has developed a model that can help pinpoint the origins of a patient’s cancer, which is critical in determining the most effective treatment method. This exciting development could potentially save lives and improve outcomes for cancer patients.
But it’s not just in the field of healthcare where AI is making waves. In the era of deepfakes and manipulated images, AI is emerging as a protector. New algorithms are being developed to detect and counter AI-generated image alterations, safeguarding the authenticity of visual content.
Meanwhile, researchers are streamlining robot control learning, making the integration of robotics into various industries more efficient. They have uncovered a more straightforward approach to teaching robots control mechanisms, optimizing their utility and deployment speed in multiple applications. This could have far-reaching implications for industries that rely on robotics, from manufacturing to healthcare.
Speaking of robotics, there’s also a revolutionary methodology that promises to accelerate robotics training techniques. Imagine instructing robots in a fraction of the time it currently takes, enhancing their utility and productivity in various tasks.
In the world of computer science, Armando Solar-Lezama has been honored as the inaugural Distinguished Professor of Computing. This recognition is a testament to his invaluable contributions and impact on the field.
AI is even transforming household robots. The integration of AI has enabled household robots to plan tasks more efficiently, cutting their preparation time in half. This means that these robots can perform tasks with more seamless operations in domestic environments.
And let’s not forget about the impact of AI on writing productivity. A recent study highlights how ChatGPT, an AI-driven tool, enhances workplace productivity, especially in writing tasks. Professionals in diverse sectors can benefit significantly from this tool.
Finally, in the modern era, data privacy needs to be reimagined. As our digital footprints expand, it’s crucial to approach data privacy with a fresh perspective. We need to revisit and redefine what personal data protection means to ensure our information is safeguarded.
These are just some of the exciting developments happening in the world of AI. The possibilities are endless, and AI continues to push boundaries and pave the way for a brighter future.
In today’s Daily AI News, we have some exciting updates from major tech companies. Let’s dive right in!
OpenAI is making strides in content moderation with its latest development, GPT-4. This advanced AI model aims to replace human moderators by offering consistent judgments, faster policy development, and better worker well-being. This could be especially beneficial for smaller companies lacking resources in this area.
Microsoft is also moving forward with its AI offerings. They have launched ChatGPT on their Azure OpenAI service, allowing developers and businesses to integrate conversational AI into their applications. With ChatGPT, you can power custom chatbots, automate emails, and even get summaries of conversations. This helps users have more control and privacy over their interactions compared to the public model.
Google is not lagging behind either. They have introduced several AI-powered updates to enhance the search experience. Now, users can expect concise summaries, definitions, and even coding improvements. Additionally, Google Photos has added a Memories view feature, using AI to create a scrapbook-like timeline of your most memorable moments.
Amazon is utilizing generative AI to enhance product reviews. They are extracting key points from customer reviews to help shoppers quickly assess products. This feature includes trusted reviews from verified purchases, making the shopping experience even more convenient.
WhatsApp is also testing a new feature for its beta version called “custom AI-generated stickers.” A limited number of beta testers can now create their own stickers by typing prompts for the AI model. This feature has the potential to add a personal touch to your conversations.
And that’s all for today’s AI news updates! Stay tuned for more exciting developments in the world of artificial intelligence.
Thanks for tuning in to today’s episode! We covered a wide range of topics, including how GPT-4 improves content moderation, the impressive performance of Shepherd in critiquing language models, Microsoft’s private ChatGPT for Azure, Google’s use of AI for web content summaries, and various advancements in AI technology. See you in the next episode, and don’t forget to subscribe!
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover building a secure chatbot using AnythingLLM, AI-powered tools for recruitment, the capabilities of ChatGPT, Apple’s developments in AI health coaching, Google’s testing of AI for web page summarization, and the Wondercraft AI platform for podcasting with a special discount code.
If you’re interested in creating your own custom chatbot for your business, there’s a great option you should definitely check out. It’s called AnythingLLM, and it’s the first chatbot that offers top-notch privacy and security for enterprise-grade needs. You see, when you use other chatbots like ChatGPT from OpenAI, they collect various types of data from you. Things like prompts and conversations, geolocation data, network activity information, commercial data such as transaction history, and even identifiers like your contact details. They also take device and browser cookies as well as log data like your IP address. Now, if you opt to use their API to interact with their LLMs (like gpt-3.5 or gpt-4), then your data is not collected. So, what’s the solution? Build your own private and secure chatbot. Sounds complicated, right? Well, not anymore. Mintplex Labs, which is actually backed by Y-Combinator, has just released AnythingLLM. This amazing platform lets you build your own chatbot in just 10 minutes, and you don’t even need to know how to code. They provide you with all the necessary tools to create and manage your chatbot using API keys. Plus, you can enhance your chatbot’s knowledge by importing data like PDFs and emails. The best part is that all this data remains confidential, as only you have access to it. Unlike ChatGPT, where uploading PDFs, videos, or other data might put your information at risk, with AnythingLLM, you have complete control over your data’s security. So, if you’re ready to build your own business-compliant and secure chatbot, head over to useanything.com. All you need is an OpenAI or Azure OpenAI API key. And if you prefer using the open-source code yourself, you can find it on their GitHub repo at github.com/Mintplex-Labs/anything-llm. Check it out and build your own customized chatbot today!
AI-powered tools have revolutionized the recruitment industry, enabling companies to streamline their hiring processes and make better-informed decisions. Let’s take a look at some of the top tools that are transforming talent acquisition.
First up, Humanly.io offers Conversational AI to Recruit And Retain At Scale. This tool is specifically designed for high-volume hiring in organizations, enhancing candidate engagement through automated chat interactions. It allows recruiters to effortlessly handle large numbers of applicants with a personalized touch.
Another great tool is MedhaHR, an AI-driven healthcare talent sourcing platform. It automates resume screening, provides personalized job recommendations, and offers cost-effective solutions. This is especially valuable in the healthcare industry where finding the right talent is crucial.
For comprehensive candidate sourcing and screening, ZappyHire is an excellent choice. This platform combines features like candidate sourcing, resume screening, automated communication, and collaborative hiring, making it a valuable all-in-one solution.
Sniper AI utilizes AI algorithms to source potential candidates, assess their suitability, and seamlessly integrates with Applicant Tracking Systems (ATS) for workflow optimization. It simplifies the hiring process and ensures that the best candidates are identified quickly and efficiently.
Lastly, PeopleGPT, developed by Juicebox, provides recruiters with a tool to simplify the process of searching for people data. Recruiters can input specific queries to find potential candidates, saving time and improving efficiency.
With the soaring demand for AI specialists, compensation for these roles is reaching new heights. American companies are offering nearly a million-dollar salary to experienced AI professionals. Industries like entertainment and manufacturing are scrambling to attract data scientists and machine learning specialists, resulting in fierce competition for talent.
As the demand for AI expertise grows, companies are stepping up their compensation packages. Mid-six-figure salaries, lucrative bonuses, and stock grants are being offered to lure experienced professionals. While top positions like machine learning platform product managers can command up to $900,000 in total compensation, other roles such as prompt engineers can still earn around $130,000 annually.
The recruitment landscape is rapidly changing with the help of AI-powered tools, making it easier for businesses to find and retain top talent.
So, you’re leading a remote team and looking for advice on how to effectively manage them, communicate clearly, monitor progress, and maintain a positive team culture? Well, you’ve come to the right place! Managing a remote team can have its challenges, but fear not, because ChatGPT is here to help.
First and foremost, let’s talk about clear communication. One strategy for ensuring this is by scheduling and conducting virtual meetings. These meetings can help everyone stay on the same page, discuss goals, and address any concerns or questions. It’s important to set a regular meeting schedule and make sure everyone has the necessary tools and technology to join.
Next up, task assignment. When working remotely, it’s crucial to have a system in place for assigning and tracking tasks. There are plenty of online tools available, such as project management software, that can help streamline this process. These tools allow you to assign tasks, set deadlines, and track progress all in one place.
Speaking of progress tracking, it’s essential to have a clear and transparent way to monitor how things are progressing. This can be done through regular check-ins, status updates, and using project management tools that provide insights into the team’s progress.
Now, let’s focus on maintaining a positive team culture in a virtual setting. One way to promote team building is by organizing virtual team-building activities. These can range from virtual happy hours to online game nights. The key is to create opportunities for team members to connect and bond despite the physical distance.
In summary, effectively managing a remote team requires clear communication, task assignment and tracking, progress monitoring, and promoting team building. With the help of ChatGPT, you’re well-equipped to tackle these challenges and lead your team to success.
Did you know that Apple is reportedly working on an AI-powered health coaching service? Called Quartz, this service will help users improve their exercise, eating habits, and sleep quality. By using AI and data from the user’s Apple Watch, Quartz will create personalized coaching programs and even introduce a monthly fee. But that’s not all – Apple is also developing emotion-tracking tools and plans to launch an iPad version of the iPhone Health app this year.
This move by Apple is significant because it shows that AI is making its way into IoT devices like smartwatches. The combination of AI and IoT can potentially revolutionize our daily lives, allowing devices to adapt and optimize settings based on external circumstances. Imagine your smartwatch automatically adjusting its settings to help you achieve your health goals – that’s the power of AI in action!
In other Apple news, the company recently made several announcements at the WWDC 2023 event. While they didn’t explicitly mention AI, they did introduce features that heavily rely on AI technology. For example, Apple Vision Pro uses advanced machine learning techniques to blend digital content with the physical world. Upgraded Autocorrect, Improved Dictation, Live Voicemail, Personalized Volume, and the Journal app all utilize AI in their functionality.
Although Apple didn’t mention the word “AI,” these updates and features demonstrate that the company is indeed leveraging AI technologies across its products and services. By incorporating AI into its offerings, Apple is joining the ranks of Google and Microsoft in harnessing the power of artificial intelligence.
Lastly, it’s worth noting that Apple is also exploring AI chatbot technology. The company has developed its own language model called “Ajax” and an AI chatbot named “Apple GPT.” They aim to catch up with competitors like OpenAI and Google in this space. While there’s no clear strategy for releasing AI technology directly to consumers yet, Apple is considering integrating AI tools into Siri to enhance its functionality and keep up with advancements in the field.
Overall, Apple’s efforts in AI development and integration demonstrate its commitment to staying competitive in the rapidly advancing world of artificial intelligence.
Hey there! I want to talk to you today about some interesting developments in the world of artificial intelligence. It seems like Google is always up to something, and this time they’re testing a new feature on Chrome. It’s called ‘SGE while browsing’, and what it does is break down long web pages into easy-to-read key points. How cool is that? It makes it so much easier to navigate through all that information.
In other news, Talon Aerolytics, a leading innovator in SaaS and AI technology, has announced that their AI-powered computer vision platform is revolutionizing the way wireless operators visualize and analyze network assets. By using end-to-end AI and machine learning, they’re making it easier to manage and optimize networks. This could be a game-changer for the industry!
But it’s not just Google and Talon Aerolytics making waves. Beijing is getting ready to implement new regulations for AI services, aiming to strike a balance between state control and global competitiveness. And speaking of competitiveness, Saudi Arabia and the UAE are buying up high-performance chips crucial for building AI software. Looks like they’re joining the global AI arms race!
Oh, and here’s some surprising news. There’s a prediction that OpenAI might go bankrupt by the end of 2024. That would be a huge blow for the AI community. Let’s hope it doesn’t come true and they find a way to overcome any challenges they may face.
Well, that’s all the AI news I have for you today. Stay tuned for more exciting developments in the world of artificial intelligence.
Hey there, AI Unraveled podcast listeners! Have you been itching to dive deeper into the world of artificial intelligence? Well, I’ve got some exciting news for you! Introducing “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” a must-have book written by the brilliant Etienne Noumen. This essential read is now available at popular platforms like Shopify, Apple, Google, and even Amazon. So, no matter where you prefer to get your books, you’re covered!
Now, let’s talk about the incredible tool behind this podcast. It’s called Wondercraft AI, and it’s an absolute game-changer. With Wondercraft AI, starting your own podcast has never been easier. You’ll have the power to use hyper-realistic AI voices as your host, just like me! How cool is that?
Oh, and did I mention you can score a fantastic 50% discount on your first month of Wondercraft AI? Just use the code AIUNRAVELED50, and you’re good to go. That’s an awesome deal if you ask me!
So, whether you’re eager to explore the depths of artificial intelligence through Etienne Noumen’s book or you’re ready to take the plunge and create your own podcast with Wondercraft AI, the possibilities are endless. Get ready to unravel the mysteries of AI like never before!
On today’s episode, we covered a range of topics, including building a secure chatbot for your business, AI-powered tools for recruitment and their impact on salaries, the versatility of ChatGPT, Apple’s advancements in AI health coaching, Google’s AI-driven web page summarization, and the latest offerings from the Wondercraft AI platform. Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!
NVIDIA’s tool to curate trillion-token datasets for pretraining LLMs
Trustworthy LLMs: A survey and guideline for evaluating LLMs’ alignment
Amazon’s push to match Microsoft and Google in generative AI
World first’s mass-produced humanoid robots with AI brains
Microsoft Designer: An AI-powered Canva: a super cool product that I just found!
ChatGPT costs OpenAI $700,000 PER Day
What Else Is Happening in AI
Google appears to be readying new AI-powered tools for ChromeOS
Zoom rewrites policies to make clear user videos aren’t used to train AI
Anthropic raises $100M in funding from Korean telco giant SK Telecom
Modular, AI startup challenging Nvidia, discusses funding at $600M valuation
California turns to AI to spot wildfires, feeding on video from 1,000+ cameras
FEC to regulate AI deepfakes in political ads ahead of 2024 election
AI in Scientific Papers
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover LLMs and their various models, IBM’s energy-efficient AI chip prototype, NVIDIA’s NeMo Data Curator tool, guidelines for aligning LLMs with human intentions, Amazon’s late entry into generative AI chips, Chinese start-up Fourier Intelligence’s humanoid robot, Microsoft Designer and OpenAI’s financial troubles, Google’s AI tools for ChromeOS, various news including funding, challenges to Nvidia, AI in wildfire detection, and FEC regulations, the political bias and tool usage of LLMs, and special offers on starting a podcast and a book on AI.
LLM, or Large Language Model, is an exciting advancement in the field of AI. It’s all about training models to understand and generate human-like text by using deep learning techniques. These models are trained on enormous amounts of text data from various sources like books, articles, and websites. This wide range of textual data allows them to learn grammar, vocabulary, and the contextual relationships in language.
LLMs can do some pretty cool things when it comes to natural language processing (NLP) tasks. For example, they can translate languages, summarize text, answer questions, analyze sentiment, and generate coherent and contextually relevant responses to user inputs. It’s like having a super-smart language assistant at your disposal!
There are several popular LLMs out there. One of them is GPT-3 by OpenAI, which can generate text, translate languages, write creative content, and provide informative answers. Google AI has also developed impressive models like T5, which is specifically designed for text generation tasks, and LaMDA, which excels in dialogue applications. Another powerful model is PaLM by Google AI, which can perform a wide range of tasks, including text generation, translation, summarization, and question-answering. DeepMind’s FlaxGPT, based on the Transformer architecture, is also worth mentioning for its accuracy and consistency in generating text.
With LLMs continuously improving, we can expect even more exciting developments in the field of AI and natural language processing. The possibilities for utilizing these models are vast, and they have the potential to revolutionize how we interact with technology and language.
Have you ever marveled at the incredible power and efficiency of the human brain? Well, get ready to be amazed because IBM has created a prototype chip that mimics the connections in our very own minds. This breakthrough could revolutionize the world of artificial intelligence by making it more energy efficient and less of a battery-drain for devices like smartphones.
What’s so impressive about this chip is that it combines both analogue and digital elements, making it much easier to integrate into existing AI systems. This is fantastic news for all those concerned about the environmental impact of huge warehouses full of computers powering AI systems. With this brain-like chip, emissions could be significantly reduced, as well as the amount of water needed to cool those power-hungry data centers.
But why does all of this matter? Well, if brain-like chips become a reality, we could soon see a whole new level of AI capabilities. Imagine being able to execute large and complex AI workloads in low-power or battery-constrained environments such as cars, mobile phones, and cameras. This means we could enjoy new and improved AI applications while keeping costs to a minimum.
So, brace yourself for a future where AI comes to life in a way we’ve never seen before. Thanks to IBM’s brain-inspired chip, the possibilities are endless, and the benefits are undeniable.
So here’s the thing: creating massive datasets for training language models is no easy task. Most of the software and tools available for this purpose are either not publicly accessible or not scalable enough. This means that developers of Language Model models (LLMs) often have to go through the trouble of building their own tools just to curate large language datasets. It’s a lot of work and can be quite a headache.
But fear not, because Nvidia has come to the rescue with their NeMo Data Curator! This nifty tool is not only scalable, but it also allows you to curate trillion-token multilingual datasets for pretraining LLMs. And get this – it can handle tasks across thousands of compute cores. Impressive, right?
Now, you might be wondering why this is such a big deal. Well, apart from the obvious benefit of improving LLM performance with high-quality data, using the NeMo Data Curator can actually save you a ton of time and effort. It takes away the burden of manually going through unstructured data sources and allows you to focus on what really matters – developing AI applications.
And the cherry on top? It can potentially lead to significant cost reductions in the pretraining process, which means faster and more affordable development of AI applications. So if you’re a developer working with LLMs, the NeMo Data Curator could be your new best friend. Give it a try and see the difference it can make!
In the world of AI, ensuring that language models behave in accordance with human intentions is a critical task. That’s where alignment comes into play. Alignment refers to making sure that models understand and respond to human input in the way that we want them to. But how do we evaluate and improve the alignment of these models?
Well, a recent research paper has proposed a more detailed taxonomy of alignment requirements for language models. This taxonomy helps us better understand the different dimensions of alignment and provides practical guidelines for collecting the right data to develop alignment processes.
The paper also takes a deep dive into the various categories of language models that are crucial for improving their trustworthiness. It explores how we can build evaluation datasets specifically for alignment. This means that we can now have a more transparent and multi-objective evaluation of the trustworthiness of language models.
Why does all of this matter? Well, having a clear framework and comprehensive guidance for evaluating and improving alignment can have significant implications. For example, OpenAI, a leading AI research organization, had to spend six months aligning their GPT-4 model before its release. With better guidance, we can drastically reduce the time it takes to bring safe, reliable, and human-aligned AI applications to market.
So, this research is a big step forward in ensuring that language models are trustworthy and aligned with human values.
Amazon is stepping up its game in the world of generative AI by developing its own chips, Inferentia and Trainium, to compete with Nvidia GPUs. While the company might be a bit late to the party, with Microsoft and Google already invested in this space, Amazon is determined to catch up.
Being the dominant force in the cloud industry, Amazon wants to set itself apart by utilizing its custom silicon capabilities. Trainium, in particular, is expected to deliver significant improvements in terms of price-performance. However, it’s worth noting that Nvidia still remains the go-to choice for training models.
Generative AI models are all about creating and simulating data that resembles real-world examples. They are widely used in various applications, including natural language processing, image recognition, and even content creation.
By investing in their own chips, Amazon aims to enhance the training and speeding up of generative AI models. The company recognizes the potential of this technology and wants to make sure they can compete with the likes of Microsoft and Google, who have already made significant progress in integrating AI models into their products.
Amazon’s entry into the generative AI market signifies their commitment to innovation, and it will be fascinating to see how their custom chips will stack up against Nvidia’s GPUs in this rapidly evolving field.
So, get this – Chinese start-up Fourier Intelligence has just unveiled its latest creation: a humanoid robot called GR-1. And trust me, this is no ordinary robot. This bad boy can actually walk on two legs at a speed of 5 kilometers per hour. Not only that, but it can also carry a whopping 50 kilograms on its back. Impressive, right?
Now, here’s the interesting part. Fourier Intelligence wasn’t initially focused on humanoid robots. Nope, they were all about rehabilitation robotics. But in 2019, they decided to switch things up and dive into the world of humanoids. And let me tell you, it paid off. After three years of hard work and dedication, they finally achieved success with GR-1.
But here’s the thing – commercializing humanoid robots is no easy feat. There are still quite a few challenges to tackle. However, Fourier Intelligence is determined to overcome these obstacles. They’re aiming to mass-produce GR-1 by the end of this year. And wait for it – they’re already envisioning potential applications in areas like elderly care and education. Can you imagine having a humanoid robot as your elderly caregiver or teacher? It’s pretty mind-blowing.
So, keep an eye out for Fourier Intelligence and their groundbreaking GR-1 robot. Who knows? This could be the beginning of a whole new era of AI-powered humanoid helpers.
Hey everyone, I just came across this awesome product called Microsoft Designer! It’s like an AI-powered Canva that lets you create all sorts of graphics, from logos to invitations to social media posts. If you’re a fan of Canva, you definitely need to give this a try.
One of the cool features of Microsoft Designer is “Prompt-to-design.” You can just give it a short description, and it uses DALLE-2 to generate original and editable designs. How amazing is that?
Another great feature is the “Brand-kit.” You can instantly apply your own fonts and color palettes to any design, and it can even suggest color combinations for you. Talk about staying on-brand!
And that’s not all. Microsoft Designer also has other AI tools that can suggest hashtags and captions, replace backgrounds in images, erase items from images, and even auto-fill sections of an image with generated content. It’s like having a whole team of designers at your fingertips!
Now, on a different topic, have you heard about OpenAI’s financial situation? Apparently, running ChatGPT is costing them a whopping $700,000 every single day! That’s mind-boggling. Some reports even suggest that OpenAI might go bankrupt by 2024. But personally, I have my doubts. They received a $10 billion investment from Microsoft, so they must have some money to spare, right? Let me know your thoughts on this in the comments below.
On top of the financial challenges, OpenAI is facing some other issues. For example, ChatGPT has seen a 12% drop in users from June to July, and top talent is being lured away by rivals like Google and Meta. They’re also struggling with GPU shortages, which make it difficult to train better models.
To make matters worse, there’s increasing competition from cheaper open-source models that could potentially replace OpenAI’s APIs. Musk’s xAI is even working on a more right-wing biased model, and Chinese firms are buying up GPU stockpiles.
With all these challenges, it seems like OpenAI is in a tough spot. Their costs are skyrocketing, revenue isn’t offsetting losses, and there’s growing competition and talent drain. It’ll be interesting to see how they navigate through these financial storms.
So, let’s talk about what else is happening in the world of AI. It seems like Google has some interesting plans in store for ChromeOS. They’re apparently working on new AI-powered tools, but we’ll have to wait and see what exactly they have in mind. It could be something exciting!
Meanwhile, Zoom is taking steps to clarify its policies regarding user videos and AI training. They want to make it clear that your videos on Zoom won’t be used to train AI systems. This is an important move to ensure privacy and transparency for their users.
In terms of funding, Anthropic, a company in the AI space, recently secured a significant investment of $100 million from SK Telecom, a Korean telco giant. This infusion of funds will undoubtedly help propel their AI initiatives forward.
Speaking of startups, there’s one called Modular that’s aiming to challenge Nvidia in the AI realm. They’ve been discussing funding and are currently valued at an impressive $600 million. It’ll be interesting to see if they can shake things up in the market.
Coming closer to home, California is turning to AI technology to help spot wildfires. They’re using video feeds from over 1,000 cameras, analyzing the footage with AI algorithms to detect potential fire outbreaks. This innovative approach could help save lives and protect communities from devastating fires.
Lastly, in an effort to combat misinformation and manipulation, the Federal Election Commission (FEC) is stepping in to regulate AI deepfakes in political ads ahead of the 2024 election. It’s a proactive move to ensure fair and accurate campaigning in the digital age.
And that’s a roundup of some of the latest happenings in the world of AI! Exciting, right?
So, there’s a lot of exciting research and developments happening in the field of AI, especially in scientific papers. One interesting finding is that language models, or LLMs, have the ability to learn how to use tools without any specific training. Instead of providing demonstrations, researchers have found that simply providing tool documentation is enough for LLMs to figure out how to use programs like image generators and video tracking software. Pretty impressive, right?
Another important topic being discussed in scientific papers is the political bias of major AI language models. It turns out that models like ChatGPT and GPT-4 tend to lean more left-wing, while Meta’s Llama exhibits more right-wing bias. This research sheds light on the inherent biases in these models, which is crucial for us to understand as AI becomes more mainstream.
One fascinating paper explores the possibility of reconstructing images from signals in the brain. Imagine having brain interfaces that can consistently read these signals and maybe even map everything we see. The potential for this technology is truly limitless.
In other news, Nvidia has partnered with HuggingFace to provide a cloud platform called DGX Cloud, which allows people to train and tune AI models. They’re even offering a “Training Cluster as a Service,” which will greatly speed up the process of building and training models for companies and individuals.
There are also some intriguing developments from companies like Stability AI, who have released their new AI LLM called StableCode, and PlayHT, who have introduced a new text-to-voice AI model. And let’s not forget about the collaboration between OpenAI, Google, Microsoft, and Anthropic with Darpa for an AI cyber challenge – big things are happening!
So, as you can see, there’s a lot going on in the world of AI. Exciting advancements and thought-provoking research are shaping the future of this technology. Stay tuned for more updates and breakthroughs in this rapidly evolving field.
Hey there, AI Unraveled podcast listeners! If you’re hungry for more knowledge on artificial intelligence, I’ve got some exciting news for you. Etienne Noumen, our brilliant host, has written a must-read book called “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence.” And guess what? You can grab a copy today at Shopify, Apple, Google, or Amazon (https://amzn.to/44Y5u3y) .
This book is a treasure trove of insights that will expand your understanding of AI. Whether you’re a beginner or a seasoned expert, “AI Unraveled” has got you covered. It dives deep into frequently asked questions and provides clear explanations that demystify the world of artificial intelligence. You’ll learn about its applications, implications, and so much more.
Now, let me share a special deal with you. As a dedicated listener of AI Unraveled, you can get a fantastic 50% discount on the first month of using the Wondercraft AI platform. Wondering what that is? It’s a powerful tool that lets you start your own podcast, featuring hyper-realistic AI voices as your host. Trust me, it’s super easy and loads of fun.
So, go ahead and use the code AIUNRAVELED50 to claim your discount. Don’t miss out on this incredible opportunity to expand your AI knowledge and kickstart your own podcast adventure. Get your hands on “AI Unraveled” and dive into the fascinating world of artificial intelligence. Happy exploring!
Thanks for listening to today’s episode, where we covered various topics including the latest AI models like GPT-3 and T5, IBM’s energy-efficient chip that mimics the human brain, NVIDIA’s NeMo Data Curator tool, guidelines for aligning LLMs with human intentions, Amazon’s late entry into the generative AI chip market, Fourier Intelligence’s humanoid robot GR-1, Microsoft Designer and OpenAI’s financial troubles, and Google’s AI tools for ChromeOS. Don’t forget to subscribe for more exciting discussions, and remember, you can get 50% off the first month of starting your own podcast with Wondercraft AI! See you at the next episode!
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover the 80/20 rule for optimizing business operations, how MetaGPT improves multi-agent collaboration, potential regulation of AI-generated deepfakes in political ads, advancements in ChatGPT and other AI applications, recent updates and developments from Spotify, Patreon, Google, Apple, Microsoft, and Chinese internet giants, and the availability of hyper-realistic AI voices and the book “AI Unraveled” by Etienne Noumen.
Sure! The 80/20 rule can be a game-changer when it comes to analyzing your e-commerce business. By identifying which 20% of your products are generating 80% of your sales, you can focus your efforts and resources on those specific products. This means allocating more inventory, marketing, and customer support towards them. By doing so, you can maximize your profitability and overall success.
Similarly, understanding which 20% of your marketing efforts are driving 80% of your traffic is crucial. This way, you can prioritize those marketing channels that are bringing the most traffic to your website. You might discover that certain social media platforms or advertising campaigns are particularly effective. By narrowing your focus, you can optimize your marketing budget and efforts to yield the best results.
In terms of operations, consider streamlining processes related to your top-performing products and marketing channels. Look for ways to improve efficiency and reduce costs without sacrificing quality. Automating certain tasks, outsourcing non-core activities, or renegotiating supplier contracts might be worth exploring.
Remember, embracing the 80/20 rule with tools like ChatGPT allows you to make data-driven decisions and concentrate on what really matters. So, dive into your sales and marketing data, identify the key contributors, and optimize your business accordingly. Good luck!
So, let’s talk about MetaGPT and how it’s tackling LLM hallucination. MetaGPT is a new framework that aims to improve multi-agent collaboration by incorporating human workflows and domain expertise. One of the main issues it addresses is hallucination in LLMs, which are language models that tend to generate incorrect or nonsensical responses.
To combat this problem, MetaGPT encodes Standardized Operating Procedures (SOPs) into prompts, effectively providing a structured coordination mechanism. This means that it includes specific guidelines and instructions to guide the response generation process.
But that’s not all. MetaGPT also ensures modular outputs, which allows different agents to validate the generated outputs and minimize errors. By assigning diverse roles to agents, the framework effectively breaks down complex problems into more manageable parts.
So, why is all of this important? Well, experiments on collaborative software engineering benchmarks have shown that MetaGPT outperforms chat-based multi-agent systems in terms of generating more coherent and correct solutions. By integrating human knowledge and expertise into multi-agent systems, MetaGPT opens up new possibilities for tackling real-world challenges.
With MetaGPT, we can expect enhanced collaboration, reduced errors, and more reliable outcomes. It’s exciting to see how this framework is pushing the boundaries of multi-agent systems and taking us one step closer to solving real-world problems.
Have you heard about the potential regulation of AI-generated deepfakes in political ads? The Federal Election Commission (FEC) is taking steps to protect voters from election disinformation by considering rules for AI ads before the 2024 election. This is in response to a petition calling for regulation to prevent misrepresentation in political ads using AI technology.
Interestingly, some campaigns, like Florida GOP Gov. Ron DeSantis’s, have already started using AI in their advertisements. So, the FEC’s decision on regulation is a significant development for the upcoming elections.
However, it’s important to note that the FEC will make a decision on rules only after a 60-day public comment window, which will likely start next week. While regulation could impose guidelines for disclaimers, it may not cover all the threats related to deepfakes from individual social media users.
The potential use of AI in misleading political ads is a pressing issue with elections on the horizon. The fact that the FEC is considering regulation indicates an understanding of the possible risks. But implementing effective rules will be the real challenge. In a world where seeing is no longer believing, ensuring truth in political advertising becomes crucial.
In other news, the White House recently launched a hacking challenge focused on AI cybersecurity. With a generous prize pool of $20 million, the competition aims to incentivize the development of AI systems for protecting critical infrastructure from cyber risks.
Teams will compete to secure vital software systems, with up to 20 teams advancing from qualifiers to win $2 million each at DEF CON 2024. Finalists will also have a chance at more prizes, including a $4 million top prize at DEF CON 2025.
What’s interesting about this challenge is that competitors are required to open source their AI systems for widespread use. This collaboration not only involves AI leaders like Anthropic, Google, Microsoft, and OpenAI, but also aims to push the boundaries of AI in national cyber defense.
Similar government hacking contests have been conducted in the past, such as the 2014 DARPA Cyber Grand Challenge. These competitions have proven to be effective in driving innovation through competition and incentivizing advancements in automated cybersecurity.
With the ever-evolving cyber threats, utilizing AI to stay ahead in defense becomes increasingly important. The hope is that AI can provide a powerful tool to protect critical infrastructure from sophisticated hackers and ensure the safety of government systems.
Generative AI tools like ChatGPT are revolutionizing the way workers make money. By automating time-consuming tasks and creating new income streams and full-time jobs, these AI tools are empowering workers to increase their earnings. It’s truly amazing how technology is transforming the workplace!
In other news, Universal Music Group and Google have teamed up for an exciting project involving AI song licensing. They are negotiating to license artists’ voices and melodies for AI-generated songs. Warner Music is also joining in on the collaboration. While this move could be lucrative for record labels, it poses challenges for artists who want to protect their voices from being cloned by AI. It’s a complex situation with both benefits and concerns.
AI is even playing a role in reducing the climate impact of airlines. Contrails, those long white lines you see in the sky behind airplanes, actually trap heat in Earth’s atmosphere, causing a net warming effect. But pilots at American Airlines are now using Google’s AI predictions and Breakthrough Energy’s models to select altitudes that are less likely to produce contrails. After conducting 70 test flights, they have observed a remarkable 54% reduction in contrails. This shows that commercial flights have the potential to significantly lessen their environmental impact.
Anthropic has released an updated version of its popular model, Claude Instant. Known for its speed and affordability, Claude Instant 1.2 can handle various tasks such as casual dialogue, text analysis, summarization, and document comprehension. The new version incorporates the strengths of Claude 2 and demonstrates significant improvements in areas like math, coding, and reasoning. It generates longer and more coherent responses, follows formatting instructions better, and even enhances safety by hallucinating less and resisting jailbreaks. This is an exciting development that brings Anthropic closer to challenging the supremacy of ChatGPT.
Google has also delved into the intriguing question of whether language models (LLMs) generalize or simply memorize information. While LLMs seem to possess a deep understanding of the world, there is a possibility that they are merely regurgitating memorized bits from their extensive training data. Google conducted research on the training dynamics of a small model and reverse-engineered its solution, shedding light on the increasingly fascinating field of mechanistic interpretability. The findings suggest that LLMs initially generalize well but then start to rely more on memorization. This research opens the door to a better understanding of the dynamics behind model behavior, particularly with regards to memorization and generalization.
In conclusion, AI tools like ChatGPT are empowering workers to earn more, Universal Music and Google are exploring a new realm of AI song licensing, AI is helping airlines reduce their climate impact, Anthropic has launched an improved model with enhanced capabilities and safety, and Google’s research on LLMs deepens our understanding of their behavior. It’s an exciting time for AI and its diverse applications!
Hey, let’s dive into today’s AI news!
First up, we have some exciting news for podcasters. Spotify and Patreon have integrated, which means that Patreon-exclusive audio content can now be accessed on Spotify. This move is a win-win for both platforms. It allows podcasters on Patreon to reach a wider audience through Spotify’s massive user base while circumventing Spotify’s aversion to RSS feeds.
In some book-related news, there have been reports of AI-generated books falsely attributed to Jane Friedman appearing on Amazon and Goodreads. This has sparked concerns over copyright infringement and the verification of author identities. It’s a reminder that as AI continues to advance, we need to ensure that there are robust systems in place to authenticate content.
Google has been pondering an intriguing question: do machine learning models memorize or generalize? Their research delves into a concept called grokking to understand how models truly learn and if they’re not just regurgitating information from their training data. It’s fascinating to explore the inner workings of AI models and uncover their true understanding of the world.
IBM is making moves in the AI space by planning to make Meta’s Llama 2 available within its watsonx. This means that the Llama 2-chat 70B model will be hosted in the watsonx.ai studio, with select clients and partners gaining early access. This collaboration aligns with IBM’s strategy of offering a blend of third-party and proprietary AI models, showing their commitment to open innovation.
Amazon is also leveraging AI technology by testing a tool that helps sellers craft product descriptions. By integrating language models into their e-commerce business, Amazon aims to enhance and streamline the product listing process. This is just one example of how AI is revolutionizing various aspects of our daily lives.
Switching gears to Microsoft, they have partnered with Aptos blockchain to bring together AI and web3. This collaboration enables Microsoft’s AI models to be trained using verified blockchain information from Aptos. By leveraging the power of blockchain, they aim to enhance the accuracy and reliability of their AI models.
OpenAI has made an update for ChatGPT users on the free plan. They now offer custom instructions, allowing users to tailor their interactions with the AI model. However, it’s important to note that this update is not currently available in the EU and UK, but it will be rolling out soon.
Google’s Arts & Culture app has undergone a redesign with exciting AI-based features. Users can now delight their friends by sending AI-generated postcards through the “Poem Postcards” feature. The app also introduces a new Play tab, an “Inspire” feed akin to TikTok, and other cool features. It’s great to see AI integrating into the world of arts and culture.
In the realm of space, a new AI algorithm called HelioLinc3D has made a significant discovery. It detected a potentially hazardous asteroid that had gone unnoticed by human observers. This reinforces the value of AI in assisting with astronomical discoveries and monitoring potentially threatening space objects.
Lastly, DARPA has issued a call to top computer scientists, AI experts, and software developers to participate in the AI Cyber Challenge (AIxCC). This two-year competition aims to drive innovation at the intersection of AI and cybersecurity to develop advanced cybersecurity tools. It’s an exciting opportunity to push the boundaries of AI and strengthen our defenses against cyber threats.
That wraps up today’s AI news. Stay tuned for more updates and innovations in the exciting field of artificial intelligence!
So, here’s the scoop on what’s been happening in the AI world lately. Apple is really putting in the effort when it comes to AI development. They’ve gone ahead and ordered servers from Foxconn Industrial Internet, a division of their supplier Foxconn. These servers are specifically for testing and training Apple’s AI services. It’s no secret that Apple has been focused on AI for quite some time now, even though they don’t currently have an external app like ChatGPT. Word is, Foxconn’s division already supplies servers to other big players like ChatGPT OpenAI, Nvidia, and Amazon Web Services. Looks like Apple wants to get in on the AI chatbot market action.
And then we have Midjourney, who’s making some moves of their own. They’re upgrading their GPU cluster, which means their Pro and Mega users can expect some serious speed boosts. Render times could decrease from around 50 seconds to just 30 seconds. Plus, the good news is that these renders might also end up being 1.5 times cheaper. On top of that, Midjourney’s planning to release V5.3 soon, possibly next week. This update will bring cool features like inpainting and a fresh new style. It might be exclusive to desktop, so keep an eye out for that.
Meanwhile, Microsoft is flexing its muscles by introducing new tools for frontline workers. They’ve come up with Copilot, which uses generative AI to supercharge the efficiency of service pros. Microsoft acknowledges the massive size of the frontline workforce, estimating it to be a staggering 2.7 billion worldwide. These new tools and integrations are all about supporting these workers and tackling the labor challenges faced by businesses. Way to go, Microsoft!
Now let’s talk about Google, the folks who always seem to have something up their sleeve. They’re jazzing up their Gboard keyboard with AI-powered features. How cool is that? With their latest update, users can expect AI emojis, proofreading assistance, and even a drag mode that lets you resize the keyboard to your liking. It’s all about making your typing experience more enjoyable. These updates were spotted in the beta version of Gboard.
Over in China, the internet giants are making waves by investing big bucks in Nvidia chips. Baidu, TikTok-owner ByteDance, Tencent, and Alibaba have reportedly ordered a whopping $5 billion worth of these chips. Why, you ask? Well, they’re essential for building generative AI systems, and China is dead set on becoming a global leader in AI technology. The chips are expected to land this year, so it won’t be long until we see the fruits of their labor.
Last but not least, TikTok is stepping up its game when it comes to AI-generated content. They’re planning to introduce a toggle that allows creators to label their content as AI-generated. The goal is to prevent unnecessary content removal and promote transparency. Nice move, TikTok!
And that’s a wrap on all the AI news for now. Exciting things are happening, and we can’t wait to see what the future holds in this ever-evolving field.
Hey there, AI Unraveled podcast listeners! Are you ready to delve deeper into the fascinating world of artificial intelligence? Well, I’ve got some exciting news for you. The essential book “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence” is now out and available for you to grab!
Authored by the brilliant Etienne Noumen, this book is a must-have for anyone curious about AI. Whether you’re a tech enthusiast, a student, or simply someone who wants to understand the ins and outs of artificial intelligence, this book has got you covered.
So, where can you get your hands on this enlightening read? Well, you’re in luck! You can find “AI Unraveled” at popular platforms like Shopify, Apple, Google, or Amazon . Just head on over to their websites or use the link amzn.to/44Y5u3y to access this treasure trove of AI knowledge.
But wait, there’s more! Wondercraft AI, the amazing platform that powers your favorite podcast, has a special treat for you. If you’ve been thinking about launching your own podcast, they’ve got you covered. With Wondercraft AI, you can use hyper-realistic AI voices as your podcast host, just like me! And guess what? You can enjoy a whopping 50% discount on your first month with the code AIUNRAVELED50.
So, what are you waiting for? Dive into “AI Unraveled” and unravel the mysteries of artificial intelligence today!
Thanks for joining us on today’s episode where we discussed the 80/20 rule for optimizing business operations with ChatGPT, how MetaGPT improves multi-agent collaboration, the regulation of AI-generated deepfakes in political ads and the AI hacking challenge for cybersecurity, the various applications of AI such as automating tasks, generating music, reducing climate impact, enhancing model safety, and advancing research, the latest updates from tech giants like Spotify, Google, IBM, Microsoft, and Amazon, Apple’s plans to enter the AI chatbot market, and the availability of hyper-realistic AI voices and the book “AI Unraveled” by Etienne Noumen. Thanks for listening, I’ll see you guys at the next one and don’t forget to subscribe!
– new frameworks, resources, and services to accelerate the adoption of Universal Scene Description (USD), known as OpenUSD.
– NVIDIA has introduced AI Workbench
– NVIDIA and Hugging Face have partnered to bring generative AI supercomputing to developers.
75% of Organizations Worldwide Set to Ban ChatGPT and Generative AI Apps on Work Devices
Google launches Project IDX, an AI-enabled browser-based dev environment.
Disney has formed a task force to explore the applications of AI across its entertainment conglomerate, despite the ongoing Hollywood writers’ strike.
Stability AI has released StableCode, an LLM generative AI product for coding.
Hugging face launches tools for running LLMs on Apple devices.
Google AI is helping Airlines to reduce mitigate the climate impact of contrails.
Google and Universal Music Group are in talks to license artists’ melodies and vocals for an AI-generated music tool.
This podcast is generated using the Wondercraft AI platform (https://www.wondercraft.ai/?via=etienne), a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine! Get a 50% discount the first month with the code AIUNRAVELED50
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover topics such as collaborative software design using GPT-Synthesizer, AI-driven medical antibody design by LabGenius, NVIDIA’s new AI chip and frameworks, organizations planning to ban Generative AI apps, Google’s Project IDX and Disney’s AI task force, AI-generated music licensing by Google and Universal Music Group, MIT researchers using AI for cancer treatment, Meta focusing on commercial AI, OpenAI’s GPTBot, and the Wondercraft AI platform for podcasting with hyper-realistic AI voices.
Have you ever used ChatGPT or GPT for software design and code generation? If so, you may have noticed that for larger or more complex codes, it often skips important implementation steps or misunderstands your design. Luckily, there are tools available to help, such as GPT Engineer and Aider. However, these tools often exclude the user from the design process. If you want to be more involved and explore the design space with GPT, you should consider using GPT-Synthesizer.
GPT-Synthesizer is a free and open-source tool that allows you to collaboratively implement an entire software project with the help of AI. It guides you through the problem statement and uses a moderated interview process to explore the design space together. If you have no idea where to start or how to describe your software project, GPT Synthesizer can be your best friend.
What sets GPT Synthesizer apart is its unique design philosophy. Rather than relying on a single prompt to build a complete codebase for complex software, GPT Synthesizer understands that there are crucial details that cannot be effectively captured in just one prompt. Instead, it captures the design specification step by step through an AI-directed dialogue that engages with the user.
Using a process called “prompt synthesis,” GPT Synthesizer compiles the initial prompt into multiple program components. This helps turn ‘unknown unknowns’ into ‘known unknowns’, providing novice programmers with a better understanding of the overall flow of their desired implementation. GPT Synthesizer and the user then collaboratively discover the design details needed for each program component.
GPT Synthesizer also offers different levels of interactivity depending on the user’s skill set, expertise, and the complexity of the task. It strikes a balance between user participation and AI autonomy, setting itself apart from other code generation tools.
If you want to be actively involved in the software design and code generation process, GPT-Synthesizer is a valuable tool that can help enhance your experience and efficiency. You can find GPT-Synthesizer on GitHub at https://github.com/RoboCoachTechnologies/GPT-Synthesizer.
So, get this: robots, computers, and algorithms are taking over the search for new therapies. They’re able to process mind-boggling amounts of data and come up with molecules that humans could never even imagine. And they’re doing it all in an old biscuit factory in South London.
This amazing endeavor is being led by James Field and his company, LabGenius. They’re not baking cookies or making any sweet treats. Nope, they’re busy cooking up a whole new way of engineering medical antibodies using the power of artificial intelligence (AI).
For those who aren’t familiar, antibodies are the body’s defense against diseases. They’re like the immune system’s front-line troops, designed to attach themselves to foreign invaders and flush them out. For decades, pharmaceutical companies have been making synthetic antibodies to treat diseases like cancer or prevent organ rejection during transplants.
But here’s the thing: designing these antibodies is a painstakingly slow process for humans. Protein designers have to sift through millions of possible combinations of amino acids, hoping to find the ones that will fold together perfectly. They then have to test them all experimentally, adjusting variables here and there to improve the treatment without making it worse.
According to Field, the founder and CEO of LabGenius, there’s an infinite range of potential molecules out there, and somewhere in that vast space lies the molecule we’re searching for. And that’s where AI comes in. By crunching massive amounts of data, AI can identify unexplored molecule possibilities that humans might have never even considered.
So, it seems like the future of antibody development is in the hands of robots and algorithms. Who would have thought an old biscuit factory would be the birthplace of groundbreaking medical advancements?
NVIDIA recently made some major AI breakthroughs that are set to shape the future of technology. One of the highlights is the introduction of their new chip, the GH200. This chip combines the power of the H100, NVIDIA’s highest-end AI chip, with 141 gigabytes of cutting-edge memory and a 72-core ARM central processor. Its purpose? To revolutionize the world’s data centers by enabling the scale-out of AI models.
In addition to this new chip, NVIDIA also announced advancements in Universal Scene Description (USD), known as OpenUSD. Through their Omniverse platform and various technologies like ChatUSD and RunUSD, NVIDIA is committed to advancing OpenUSD and its 3D framework. This framework allows for seamless interoperability between different software tools and data types, making it easier to create virtual worlds.
To further support developers and researchers, NVIDIA unveiled the AI Workbench. This developer toolkit simplifies the creation, testing, and customization of pretrained generative AI models. Better yet, these models can be scaled to work on a variety of platforms, including PCs, workstations, enterprise data centers, public clouds, and NVIDIA DGX Cloud. The goal of the AI Workbench is to accelerate the adoption of custom generative AI models in enterprises around the world.
Lastly, NVIDIA partnered with Hugging Face to bring generative AI supercomputing to developers. By integrating NVIDIA DGX Cloud into the Hugging Face platform, developers gain access to powerful AI tools that facilitate training and tuning of large language models. This collaboration aims to empower millions of developers to build advanced AI applications more efficiently across various industries.
These announcements from NVIDIA demonstrate their relentless commitment to pushing the boundaries of AI technology and making it more accessible for everyone. It’s an exciting time for the AI community, and these breakthroughs are just the beginning.
Did you know that a whopping 75% of organizations worldwide are considering banning ChatGPT and other generative AI apps on work devices? It’s true! Despite having over 100 million users in June 2023, concerns over the security and trustworthiness of ChatGPT are on the rise. BlackBerry, a pioneer in AI cybersecurity, is urging caution when it comes to using consumer-grade generative AI tools in the workplace.
So, what are the reasons behind this trend? Well, 61% of organizations see these bans as long-term or even permanent measures. They are primarily driven by worries about data security, privacy, and their corporate reputation. In fact, a staggering 83% of companies believe that unsecured apps pose a significant cybersecurity threat to their IT systems.
It’s not just about security either. A whopping 80% of IT decision-makers believe that organizations have the right to control the applications being used for business purposes. On the other hand, 74% feel that these bans indicate “excessive control” over corporate and bring-your-own devices.
The good news is that as AI tools continue to improve and regulations are put in place, companies may reconsider their bans. It’s crucial for organizations to have tools in place that enable them to monitor and manage the usage of these AI tools in the workplace.
This research was conducted by OnePoll on behalf of BlackBerry. They surveyed 2,000 IT decision-makers across North America, Europe, Japan, and Australia in June and July of 2023 to gather these fascinating insights.
Google recently launched Project IDX, an exciting development for web and multiplatform app builders. This AI-enabled browser-based dev environment supports popular frameworks like Angular, Flutter, Next.js, React, Svelte, and Vue, as well as languages such as JavaScript and Dart. Built on Visual Studio Code, IDX integrates with Google’s PaLM 2-based foundation model for programming tasks called Codey.
IDX boasts a range of impressive features to support developers in their work. It offers smart code completion, enabling developers to write code more efficiently. The addition of a chatbot for coding assistance brings a new level of interactivity to the development process. And with the ability to add contextual code actions, IDX enables developers to maintain high coding standards.
One of the most exciting aspects of Project IDX is its flexibility. Developers can work from anywhere, import existing projects, and preview apps across multiple platforms. While IDX currently supports several frameworks and languages, Google has plans to expand its compatibility to include languages like Python and Go in the future.
Not wanting to be left behind in the AI revolution, Disney has created a task force to explore the applications of AI across its vast entertainment empire. Despite the ongoing Hollywood writers’ strike, Disney is actively seeking talent with expertise in AI and machine learning. These job opportunities span departments such as Walt Disney Studios, engineering, theme parks, television, and advertising. In fact, the advertising team is specifically focused on building an AI-powered ad system for the future. Disney’s commitment to integrating AI into its operations shows its dedication to staying on the cutting edge of technology.
AI researchers have made an impressive claim, boasting a 93% accuracy rate in detecting keystrokes over Zoom audio. By recording keystrokes and training a deep learning model on the unique sound profiles of individual keys, they were able to achieve this remarkable accuracy. This is particularly concerning for laptop users in quieter public places, as their non-modular keyboard acoustic profiles make them susceptible to this type of attack.
In the realm of coding, Stability AI has released StableCode, a generative AI product designed to assist programmers in their daily work and also serve as a learning tool for new developers. StableCode utilizes three different models to enhance coding efficiency. The base model underwent training on various programming languages, including Python, Go, Java, and more. Furthermore, it was further trained on a massive amount of code, amounting to 560 billion tokens.
Hugging Face has launched tools to support developers in running Language Learning Models (LLMs) on Apple devices. They have released a guide and alpha libraries/tools to enable developers to run LLM models like Llama 2 on their Macs using Core ML.
Google AI, in collaboration with American Airlines and Breakthrough Energy, is striving to reduce the climate impact of flights. By using AI and data analysis, they have developed contrail forecast maps that help pilots choose routes that minimize contrail formation. This ultimately reduces the climate impact of flights.
Additionally, Google is in talks with Universal Music Group to license artists’ melodies and vocals for an AI-generated music tool. This tool would allow users to create AI-generated music using an artist’s voice, lyrics, or sounds. Copyright holders would be compensated for the right to create the music, and artists would have the choice to opt in.
Researchers at MIT and the Dana-Farber Cancer Institute have discovered that artificial intelligence (AI) can aid in determining the origins of enigmatic cancers. This newfound knowledge enables doctors to choose more targeted treatments.
Lastly, Meta has disbanded its protein-folding team as it shifts its focus towards commercial AI. OpenAI has also introduced GPTBot, a web crawler specifically developed to enhance AI models. GPTBot meticulously filters data sources to ensure privacy and policy compliance.
Hey there, AI Unraveled podcast listeners! If you’re hungry to dive deeper into the fascinating world of artificial intelligence, I’ve got some exciting news for you. Etienne Noumen, in his book “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” has compiled an essential guide that’ll expand your understanding of this captivating field.
But let’s talk convenience – you can grab a copy of this book from some of the most popular platforms out there. Whether you’re an avid Shopify user, prefer Apple Books, rely on Google Play, or love browsing through Amazon, you can find “AI Unraveled” today!
Now, back to podcasting. If you’re itching to start your own show and have an incredible host, Wondercraft AI platform is here to make it happen. This powerful tool lets you create your podcast seamlessly, with the added perk of using hyper-realistic AI voices as your host – just like mine!
Here’s something to sweeten the deal: how about a delightful 50% discount on your first month? Use the code AIUNRAVELED50 and enjoy this special offer.
So there you have it, folks. Get your hands on “AI Unraveled,” venture into the depths of artificial intelligence, and hey, why not start your own podcast with our amazing Wondercraft AI platform? Happy podcasting!
Thanks for listening to today’s episode where we discussed topics such as collaborative software design with GPT-Synthesizer, AI-driven antibody design with LabGenius, NVIDIA’s new AI chip and partnerships, concerns over security with Generative AI apps, Google’s Project IDX and Disney’s AI task force, AI-enabled keystroke detection, StableCode for enhanced coding efficiency, LLM models on Apple devices, reducing climate impact with AI, licensing artists’ melodies with Universal Music Group, determining origins of cancers with AI, Meta’s focus on commercial AI, and OpenAI’s GPTBot for improving models. Don’t forget to subscribe and I’ll see you guys at the next one!
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover using no-code tools for business needs, boosting algorithms and detecting diabetes with chest x-rays, the improvement of AI deep fake audios and important Azure AI advancements, AI-powered features such as grammar checking in Google Search and customer data training for Zoom, concerns about AI’s impact on elections and misinformation, integration of generative AI into Jupyter notebooks, and the availability of hyper-realistic AI voices and the book “AI Unraveled” by Etienne Noumen.
So you’re starting a business but don’t have a lot of money to invest upfront? No worries! There are plenty of no-code and AI tools out there that can help you get started without breaking the bank. Let me run through some options for you:
For graphic design, check out Canva. It’s an easy-to-use tool that will empower you to create professional-looking designs without a designer on hand.
If you need a website, consider using Carrd. It’s a simple and affordable solution that allows you to build sleek, one-page websites.
To handle sales, Gumroad is an excellent choice. It’s a platform that enables you to sell digital products and subscriptions with ease.
When it comes to finding a writer, look into Claude. This tool uses AI to generate high-quality content for your business.
To manage your customer relationships, use Notion as your CRM. It’s a versatile and customizable tool that can help you organize your business contacts and interactions.
For marketing, try Buffer. It’s a social media management platform that allows you to schedule and analyze your posts across various platforms.
And if you need to create videos, CapCut is a great option. It’s a user-friendly video editing app that offers plenty of features to enhance your visual content.
Remember, you don’t need a fancy setup to start a business. Many successful ventures began with just a notebook and an Excel sheet. So don’t let limited resources hold you back. With these no-code and AI tools, you can kickstart your business with zero or minimal investment.
Now, if you’re an online business owner looking for financial advice, I have just the solution for you. Meet ChatGPT, your new personal finance advisor. Whether you need help managing your online business’s finances or making important financial decisions, ChatGPT can provide valuable insights and guidance.
Here’s a snapshot of your current financial situation: Your monthly revenue is $10,000, and your operating expenses amount to $6,000. This leaves you with a monthly net income of $4,000. In addition, you have a business savings of $20,000 and personal savings of $10,000. Your goals are to increase your savings, reduce expenses, and grow your business.
To improve your overall financial health, here’s a comprehensive financial plan for you:
1. Budgeting tips: Take a closer look at your expenses and identify areas where you can cut back. Set a realistic budget that allows you to save more.
2. Investment advice: Consider diversifying your investments. Speak with a financial advisor to explore options such as stocks, bonds, or real estate that align with your risk tolerance and long-term goals.
3. Strategies for reducing expenses: Explore ways to optimize your operating costs. This could involve negotiating better deals with suppliers, finding more cost-effective software solutions, or exploring outsourcing options.
4. Business growth strategies: Look for opportunities to expand your customer base, increase sales, and explore new markets. Consider leveraging social media and digital advertising to reach a wider audience.
Remember, these suggestions are based on best practices in personal and business finance management. However, keep in mind that ChatGPT is a helpful start but shouldn’t replace professional financial advice. Also, be cautious about sharing sensitive financial information online, as there are always risks involved, even in simulated conversations with AI.
Feel free to modify this plan based on your unique circumstances, such as focusing on debt management, retirement planning, or significant business investments. ChatGPT is here to assist you in managing your finances effectively and setting you on the path to financial success.
Boosting in machine learning is a technique that aims to make algorithms work better together by improving accuracy and reducing bias. By combining multiple weak learners into a strong learner, boosting enhances the overall performance of the model. Essentially, it helps overcome the limitations of individual algorithms and makes predictions more reliable.
In other news, a new deep learning tool has been developed that can detect diabetes using routine chest radiographs and electronic health record data. This tool, based on deep learning models, can identify individuals at risk of elevated diabetes up to three years before diagnosis. It’s an exciting development that could potentially lead to early interventions and better management of diabetes.
Furthermore, OpenAI has recently announced the launch of GPTBot, a web crawler designed to train and improve AI capabilities. This crawler will scour the internet, gathering data and information that can be used to enhance future models. OpenAI has also provided guidelines for websites on how to prevent GPTBot from accessing their content, giving users the option to opt out of having their data used for training purposes.
While GPTBot has the potential to improve accuracy and safety of AI models, OpenAI has faced criticism in the past for its data collection practices. By allowing users to block GPTBot, OpenAI seems to be taking a step towards addressing these concerns and giving individuals more control over their data. It’s a positive development in ensuring transparency and respect for user privacy.
AI deep fake audios are becoming scarily realistic. These are artificial voices generated by AI models, and a recent experiment shed some light on our ability to detect them. Participants in the study were played both genuine and deep fake audio and were asked to identify the deep fakes. Surprisingly, they could accurately spot the deep fakes only 73% of the time.
The experiment tested both English and Mandarin, aiming to understand if language impacts our ability to detect deep fakes. Interestingly, there was no difference in detectability between the two languages.
This study highlights the growing need for automated detectors to overcome the limitations of human listeners in identifying speech deepfakes. It also emphasizes the importance of expanding fact-checking and detection tools to protect against the threats posed by AI-generated deep fakes.
Shifting gears, Microsoft has announced some significant advancements in its Azure AI infrastructure, bringing its customers closer to the transformative power of generative AI. Azure OpenAI Service is now available in multiple new regions, offering access to OpenAI’s advanced models like GPT-4 and GPT-35-Turbo.
Additionally, Microsoft has made the ND H100 v5 VM series, featuring the latest NVIDIA H100 Tensor Core GPUs, generally available. These advancements provide businesses with unprecedented AI processing power and scale, accelerating the adoption of AI applications in various industries.
Finally, there has been some debate around the accuracy of generative AI, particularly in the case of ChatGPT. While it may produce erroneous results, we shouldn’t dismiss it as useless. ChatGPT operates differently from search engines and has the potential to be revolutionary. Understanding its strengths and weaknesses is crucial as we continue to embrace generative AI.
In conclusion, detecting AI deep fake audios is becoming more challenging, and automated detectors are needed. Microsoft’s Azure AI infrastructure advancements are empowering businesses with greater computational power. It’s also important to understand and evaluate the usefulness of models like ChatGPT despite their occasional errors.
Google Search has recently added an AI-powered grammar check feature to its search bar, but for now, it’s only available in English. To use this feature, simply enter a sentence or phrase into Google Search, followed by keywords like “grammar check,” “check grammar,” or “grammar checker.” Google will then let you know if your phrase is grammatically correct or provide suggestions for corrections if needed. The best part is that you can access this grammar check tool on both desktop and mobile platforms.
Speaking of AI, Zoom has updated its Terms of Service to allow the company to train its AI using user data. However, they’ve made it clear that they won’t use audio, video, or chat content without customer consent. Customers must decide whether to enable AI features and share data for product improvement, which has raised some concerns given Zoom’s questionable privacy track record. They’ve had issues in the past, such as providing less secure encryption than claimed and sharing user data with companies like Google and Facebook.
In other AI news, scientists have achieved a breakthrough by using AI to discover molecules that can combat aging cells. This could be a game-changer in the fight against aging.
There’s also an AI model called OncoNPC that may help identify the origins of cancers that are currently unknown. This information could lead to more targeted and effective tumor treatments.
However, not all AI developments are flawless. Detroit police recently made a wrongful arrest based on facial recognition technology. A pregnant woman, Porcha Woodruff, was wrongly identified as a suspect in a robbery due to incorrect facial recognition. She was incarcerated while pregnant and is now suing the city. This incident highlights the systemic issues associated with facial recognition AI, with at least six wrongful arrests occurring so far, all of which have been in the Black community. Critics argue that relying on imperfect technology like this can result in biased and shoddy investigations. It’s crucial for powerful AI systems to undergo meticulous training and testing to avoid such mistakes. Otherwise, the legal, ethical, and financial consequences will continue to mount.
Have you heard about Sam Altman’s concerns regarding the impact of AI on elections? As the CEO of OpenAI, Altman is worried about the potential effects of generative AI, especially when it comes to hyper-targeted synthetic media. He’s seen examples of AI-generated media being used in American campaign ads during the 2024 election, and it has unfortunately led to the spread of misinformation. Altman fully acknowledges the risks associated with the technology that his organization is developing and stresses the importance of raising awareness about its implications.
But let’s shift gears a bit and talk about something exciting happening in the world of AI and coding. Have you heard of Jupyter AI? It’s a remarkable tool that brings generative AI to Jupyter notebooks, opening up a whole new world of possibilities for users. With Jupyter AI, you can explore and work with AI models right within your notebook. It even offers a magic command, “%%ai,” that transforms your notebook into a playground for generative AI, making it easy to experiment and have fun.
One of the standout features of Jupyter AI is its native chat user interface, which allows you to interact with generative AI as a conversational assistant. Plus, it supports various generative model providers, including popular ones like OpenAI, AI21, Anthropic, and Cohere, as well as local models. This compatibility with JupyterLab makes it incredibly convenient, as you can seamlessly integrate Jupyter AI into your coding workflow.
So why does all of this matter? Well, integrating advanced AI chat-based assistance directly into Jupyter’s environment holds great potential to enhance tasks such as coding, summarization, error correction, and content generation. By leveraging Jupyter AI and its support for leading language models, users can streamline their coding workflows and obtain accurate answers, making their lives as developers much easier. It’s an exciting development that brings AI and coding closer than ever before.
Hey there, AI Unraveled podcast listeners!
Have you been yearning to delve deeper into the world of artificial intelligence? Well, you’re in luck! I’ve got just the thing for you. Let me introduce you to “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” a must-read book by Etienne Noumen.
This book is an essential guide that will help you expand your understanding of all things AI. From the basics to the more complex concepts, “AI Unraveled” covers it all. Whether you’re a newbie or a seasoned enthusiast, this book is packed with valuable information that will take your AI knowledge to new heights.
And the best part? You can get your hands on a copy right now! It’s available at popular platforms like Shopify, Apple, Google, or Amazon. So, wherever you prefer to shop, you can easily snag a copy and embark on your AI adventure.
Don’t miss out on this opportunity to demystify AI and satisfy your curiosity. Get your copy of “AI Unraveled” today, and let the unraveling begin!
In today’s episode, we explored various no-code tools for different business needs, the advancements in AI deep fake audios and generative AI accuracy, AI-powered features from Google Search and Zoom, OpenAI CEO Sam Altman’s concerns about AI’s impact, and the hyper-realistic AI voices from Wondercraft AI platform–thanks for listening, I’ll see you guys at the next one and don’t forget to subscribe!
This podcast is generated using the Wondercraft AI platform, a tool that makes it super easy to start your own podcast, by enabling you to use hyper-realistic AI voices as your host. Like mine!
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover topics such as how ChatGPT can assist in creating a comprehensive marketing strategy, Microsoft’s DeepSpeed-Chat making RLHF training faster and more accessible, OpenAI’s improvements to ChatGPT, the latest versions of Vicuna LLaMA-2 and Google DeepMind’s RT-2 model, various AI applications including AI music generation and AI therapists, challenges and barriers to AI adoption, integration of GPT-4 model by Twilio and generative AI assistant by Datadog, and the availability of the podcast and the book “AI Unraveled” by Etienne Noumen.
Have you heard the news? Google’s AI Search just got a major upgrade! Not only does it provide AI-powered search results, but now it also includes related images and videos. This means that searching for information is not only easier but also more engaging.
One great feature of Google’s Search Generative Experiment (SGE) is that it displays images and videos that are related to your search query. So, if you’re searching for something specific, you’ll get a variety of visual content to complement your search results. This can be incredibly helpful, especially when you’re looking for visual references or inspiration.
But that’s not all! Another handy addition is the inclusion of publication dates. Now, when you’re searching for information, you’ll know how fresh the information is. This can be particularly useful when you’re looking for up-to-date news or recent research.
If you’re excited to try out these new features, you can sign up to be a part of the Search Labs testing. This way, you can get a firsthand experience of how Google’s AI search is taking things to the next level.
Overall, this update is a game-changer for Google’s AI search. It provides a richer and more dynamic user experience, making it even easier to find the information you need. So, next time you’re searching for something, get ready for a more visual and engaging search experience with Google’s AI Search!
Have you heard about the new system from Microsoft called DeepSpeed-Chat? It’s an exciting development in the world of AI because it makes complex RLHF (Reinforcement Learning with Human Feedback) training faster, more affordable, and easily accessible to the AI community. Best of all, it’s open-sourced!
DeepSpeed-Chat has three key capabilities that set it apart. First, it offers an easy-to-use training and inference experience for models like ChatGPT. Second, it has a DeepSpeed-RLHF pipeline that replicates the training pipeline from InstructGPT. And finally, it boasts a robust DeepSpeed-RLHF system that combines various optimizations for training and inference in a unified way.
What’s really impressive about DeepSpeed-Chat is its unparalleled efficiency and scalability. It can train models with hundreds of billions of parameters in record time and at a fraction of the cost compared to other frameworks like Colossal-AI and HuggingFace DDP. Microsoft has tested DeepSpeed-Chat on a single NVIDIA A100-40G commodity GPU, and the results are impressive.
But why does all of this matter? Well, currently, there is a lack of accessible, efficient, and cost-effective end-to-end RLHF training pipelines for powerful models like ChatGPT, especially when training at the scale of billions of parameters. DeepSpeed-Chat addresses this problem, opening doors for more people to access advanced RLHF training and fostering innovation and further development in the field of AI.
OpenAI has some exciting new updates for ChatGPT that are aimed at improving the overall user experience. Let me tell you about them!
First up, when you start a new chat, you’ll now see prompt examples that can help you get the conversation going. This way, you don’t have to rack your brain for an opening line.
Next, ChatGPT will also suggest relevant replies to keep the conversation flowing smoothly. It’s like having a helpful assistant right there with you!
If you’re a Plus user and you’ve previously selected a specific model, ChatGPT will now remember your choice when starting a new chat. No more defaulting back to GPT-3.5!
Another exciting update is that ChatGPT can now analyze data and generate insights across multiple files. This means you can work on more complex projects without any hassle.
In terms of convenience, you’ll no longer be automatically logged out every two weeks. You can stay logged in and continue your work without any interruptions.
And for those who like to work quickly, ChatGPT now has keyboard shortcuts! You can use combinations like ⌘ (Ctrl) + Shift + ; to copy the last code block, or ⌘ (Ctrl) + / to see the complete list of shortcuts.
These updates to ChatGPT are designed to make it more user-friendly and enhance the interactions between humans and AI. It’s a powerful tool that can pave the way for improved and advanced AI applications. ChatGPT is definitely the leading language model of today!
The latest versions of Vicuna, known as the Vicuna v1.5 series, are here and they are packed with exciting features! These versions are based on Llama-2 and come with extended context lengths of 4K and 16K. Thanks to Meta’s positional interpolation, the performance of these Vicuna versions has been improved across various benchmarks. It’s pretty impressive!
Now, let’s dive into the details. The Vicuna 1.5 series offers two parameter versions: 7B and 13B. Additionally, you have the option to choose between a 4096 and 16384 token context window. These models have been trained on an extensive dataset consisting of 125k ShareGPT conversations. Talk about thorough preparation!
But why should you care about all of this? Well, Vicuna has already established itself as one of the most popular chat Language Models (LLMs). It has been instrumental in driving groundbreaking research in multi-modality, AI safety, and evaluation. And with these latest versions being based on the open-source Llama-2, they can serve as a reliable alternative to ChatGPT/GPT-4. Exciting times in the world of LLMs!
In other news, Google DeepMind has introduced the Robotic Transformer 2 (RT-2). This is a significant development, as it’s the world’s first vision-language-action (VLA) model that learns from both web and robotics data. By leveraging this combined knowledge, RT-2 is able to generate generalized instructions for robotic control. This helps robots understand and perform actions in both familiar and new situations. Talk about innovation!
The use of internet-scale text, image, and video data in the training of RT-2 enables robots to develop better common sense. This results in highly performant robotic policies and opens up a whole new realm of possibilities for robotic capabilities. It’s amazing to see how technology is pushing boundaries and bringing us closer to a future where robots can seamlessly interact with the world around us.
Hey there! Today we’ve got some interesting updates in the world of AI. Let’s dive right in!
First up, we’ve witnessed an incredible breakthrough in music generation. AI has brought ‘Elvis’ back to life, sort of, and he performed a hilarious rendition of a modern classic. This just goes to show how powerful AI has become in the realm of music and other creative fields.
In other news, Meta, the tech giant, has released an open-source suite of AI audio tools called AudioCraft. This is a significant contribution to the AI audio technology sector and is expected to drive advancements in audio synthesis, processing, and understanding. Exciting stuff!
However, not all news is positive. Researchers have discovered a way to manipulate AI into displaying prohibited content, which exposes potential vulnerabilities in these systems. This emphasizes the need for ongoing research into the reliability and integrity of AI, as well as measures to protect against misuse.
Meta is also leveraging AI-powered chatbots as part of their strategy to increase user engagement on their social media platforms. This demonstrates how AI is playing an increasingly influential role in enhancing user interaction in the digital world.
Moving on, Karim Lakhani, a professor at Harvard Business School, has done some groundbreaking work in the field of workplace technology and AI. He asserts that AI won’t replace humans, but rather humans with AI will replace humans without AI. It’s an interesting perspective on the future of work.
In other news, machine learning is helping researchers identify underground fungal networks. Justin Stewart embarked on a mission to gather fungal samples from Mount Chimborazo, showcasing how AI can aid in scientific discoveries.
The next frontier in AI is developing consciousness. Some researchers are exploring the idea of giving AI emotions, desires, and the ability to learn and grow. However, this raises philosophical and ethical questions about what it means to be human and the distinctiveness of our nature.
On the topic of AI advancements, we might soon witness AI initiating unprompted conversations. While this opens up exciting possibilities, it also underscores the need for ethical guidelines to ensure respectful and beneficial human-AI interaction.
AI has also made its mark in therapy by providing round-the-clock emotional support. AI therapists are revolutionizing mental health care accessibility, but it’s crucial to ponder questions about empathy and the importance of the human touch in therapy.
Let’s not forget about the challenge of converting 2D images into 3D models using AI. It’s a complex task, but progress is being made. Researchers are constantly exploring alternative methods to tackle this problem and improve the capabilities of AI.
Despite the evident potential, some businesses and industry leaders are still hesitant to fully embrace AI. They’re cautious about adopting its advantages into their operations, which highlights the barriers that exist.
Finally, in recent updates, Twilio has integrated OpenAI’s GPT-4 model into its Engage platform, Datadog has launched a generative AI assistant called Bits, and Pinterest is using next-gen AI for more personalized content and ads. Oh, and by the way, if you try to visit AI.com, you’ll be redirected to Elon Musk’s X.ai instead of going to ChatGPT.
That wraps up today’s AI news roundup. Exciting developments and thought-provoking discussions!
Hey there, AI Unraveled podcast listeners!
Have you been yearning to delve deeper into the world of artificial intelligence? Well, you’re in luck! I’ve got just the thing for you. Let me introduce you to “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” a must-read book by Etienne Noumen.
This book is an essential guide that will help you expand your understanding of all things AI. From the basics to the more complex concepts, “AI Unraveled” covers it all. Whether you’re a newbie or a seasoned enthusiast, this book is packed with valuable information that will take your AI knowledge to new heights.
And the best part? You can get your hands on a copy right now! It’s available at popular platforms like Shopify, Apple, Google, or Amazon. So, wherever you prefer to shop, you can easily snag a copy and embark on your AI adventure.
Don’t miss out on this opportunity to demystify AI and satisfy your curiosity. Get your copy of “AI Unraveled” today, and let the unraveling begin!
Thanks for listening to today’s episode where we covered a range of topics including how ChatGPT can assist in creating marketing strategies, Microsoft’s DeepSpeed-Chat making RLHF training more accessible, OpenAI’s improvements to ChatGPT, the latest advancements with Vicuna LLaMA-2 and Google DeepMind, various applications of AI including AI music generation and AI therapists, and updates from Wondercraft AI and Etienne Noumen’s book “AI Unraveled.” I’ll see you guys at the next one and don’t forget to subscribe!
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover the development of a smartphone app for detecting stroke symptoms using machine learning algorithms, the revolutionary impact of AI and ML on anti-money laundering efforts, Meta’s introduction of AudioCraft for creating high-quality audio and music, the benefits of AudioCraft and LLaMA2-Accessory for musicians, the development of an AI system for recreating music based on brain scans, the effectiveness of AI in breast cancer screening, the involvement of various companies in AI developments, and the availability of hyper-realistic AI voices generated by the Wondercraft AI platform and the book “AI Unraveled” by Etienne Noumen.
So, researchers have developed a smartphone app that can detect stroke symptoms with the help of machine learning. At the Society of NeuroInterventional Surgery’s 20th Annual Meeting, experts discussed this innovative app and its potential to recognize physical signs of stroke. The study involved researchers from the UCLA David Geffen School of Medicine and several medical institutions in Bulgaria. They collected data from 240 stroke patients across four metropolitan stroke centers. Within 72 hours from the onset of symptoms, the researchers used smartphones to record videos of the patients and assess their arm strength. This allowed them to identify classic stroke signs, such as facial asymmetry, arm weakness, and speech changes. To examine facial asymmetry, the researchers employed machine learning techniques to analyze 68 facial landmark points. For arm weakness, they utilized data from a smartphone’s internal 3D accelerometer, gyroscope, and magnetometer. To detect speech changes, the team applied mel-frequency cepstral coefficients, which convert sound waves into images for comparison between normal and slurred speech patterns. The app was then tested using neurologists’ reports and brain scan data, demonstrating its accurate diagnosis of stroke in nearly all cases. This advancement in technology shows great promise in providing a reliable and accessible tool for stroke detection. With the power of machine learning and the convenience of a smartphone app, early detection and intervention can greatly improve the outcome of stroke patients.
AI and machine learning are becoming crucial tools in the fight against money laundering. This notorious global criminal activity has posed serious challenges for financial institutions and regulatory bodies. However, the emergence of AI and machine learning is opening up new possibilities in the ongoing battle against money laundering. Money laundering is a complicated crime that involves making illicitly-gained funds appear legal. It often includes numerous transactions, which are used to obfuscate the origin of the money and make it appear legitimate. Traditional methods of detecting and preventing money laundering have struggled to keep up with the vast number of financial transactions occurring daily and the sophisticated tactics used by money launderers. Enter AI and machine learning, two technological advancements that are revolutionizing various industries, including finance. These technologies are now being leveraged to tackle money laundering, and early findings are very encouraging. AI, with its ability to mimic human intelligence, and machine learning, a branch of AI focused on teaching computers to learn and behave like humans, can analyze enormous amounts of financial data. They can sift through millions of transactions in a fraction of the time it would take a person, identifying patterns and irregularities that may indicate suspicious activities. Furthermore, these technologies not only speed up the process but also enhance accuracy. Traditional anti-money laundering systems often produce numerous false positives, resulting in wasted time and resources. AI and machine learning, on the other hand, have the ability to learn from historical data and improve their accuracy over time, reducing false positives and enabling financial institutions to concentrate their resources on genuine threats. Nevertheless, using AI and machine learning in anti-money laundering efforts comes with its own set of challenges. These technologies need access to extensive amounts of data to function effectively. This raises concerns about privacy, as financial institutions need to strike a balance between implementing efficient anti-money laundering measures and safeguarding their customers’ personal information. Additionally, adopting these technologies necessitates substantial investments in technology and skilled personnel, which smaller financial institutions may find difficult to achieve.
So, have you heard about Meta’s latest creation? It’s called AudioCraft, and it’s bringing some pretty cool stuff to the world of generative AI. Meta has developed a family of AI models that can generate high-quality audio and music based on written text. It’s like magic! AudioCraft is not just limited to music and sound. It also packs a punch when it comes to compression and generation. Imagine having all these capabilities in one convenient code base. It’s all right there at your fingertips! But here’s the best part. Meta is open-sourcing these models, giving researchers and practitioners the chance to train their own models with their own datasets. It’s a great opportunity to dive deep into the world of generative AI and explore new possibilities. And don’t worry, AudioCraft is super easy to build on and reuse, so you can take what others have done and build something amazing on top of it. Seriously, this is a big deal. AudioCraft is a significant leap forward in generative AI research. Just think about all the incredible applications this technology opens up. You could create unique audio and music for video games, merchandise promos, YouTube content, educational materials, and so much more. The possibilities are endless! And let’s not forget about the impact of the open-source initiative. It’s going to propel the field of AI-generated audio and music even further. So, get ready to let your imagination run wild with AudioCraft because the future of generative AI is here.
Have you ever heard of AudioCraft? Well, it’s like ChatGPT, but for musicians. Just as ChatGPT is a helpful tool for content writers, AudioCraft serves as a valuable resource for musicians. But let’s shift gears a bit and talk about LLaMA2-Accessory. It’s an open-source toolkit designed specifically for the development of Large Language Models (LLMs) and multimodal LLMs. This toolkit is pretty advanced, offering features like pre-training, fine-tuning, and deployment of LLMs. The interesting thing about LLaMA2-Accessory is that it inherits most of its repository from LLaMA-Adapter, but with some awesome updates. These updates include support for more datasets, tasks, visual encoders, and efficient optimization methods. LLaMA-Adapter, by the way, is a lightweight adaption method used to effectively fine-tune LLaMA into an instruction-following model. So, why is all this important? Well, by using LLaMA2-Accessory, developers and researchers can easily and quickly experiment with state-of-the-art language models. This saves valuable time and resources during the development process. Plus, the fact that LLaMA2-Accessory is open-source means that anyone can access these advanced AI tools. This democratizes access to groundbreaking AI solutions, making progress and innovation more accessible across industries and domains.
So here’s some exciting news: Google and Osaka University recently collaborated on groundbreaking research that involves an AI system with the ability to determine what music you were listening to just by analyzing your brain signals. How cool is that? The scientists developed a unique AI-based pipeline called Brain2Music, which used functional magnetic resonance imaging (fMRI) data to recreate music based on snippets of songs that participants listened to during brain scans. By observing the flow of oxygen-rich blood in the brain, the fMRI technique identified the most active regions. The team collected brain scans from five participants who listened to short 15-second clips from various genres like blues, classical, hip-hop, and pop. While previous studies have reconstructed human speech or bird songs from brain activity, recreating music from brain signals has been relatively rare. The process involved training an AI program to associate music features like genre, rhythm, mood, and instrumentation with participants’ brain signals. Researchers labeled the mood of the music with descriptive terms like happy, sad, or exciting. The AI was then personalized for each participant, establishing connections between individual brain activity patterns and different musical elements. After training, the AI was able to convert unseen brain imaging data into a format that represented the musical elements of the original song clips. This information was fed into another AI model created by Google called MusicLM, originally designed to generate music from text descriptions. MusicLM used this information to generate musical clips that closely resembled the original songs, achieving a 60% agreement level in terms of mood. Interestingly, the genre and instrumentation in both the reconstructed and original music matched more often than what could be attributed to chance. The research aims to deepen our understanding of how the brain processes music. The team noticed that specific brain regions, like the primary auditory cortex and the lateral prefrontal cortex, were activated when participants listened to music. The latter seems to play a vital role in interpreting the meaning of songs, but more investigation is needed to confirm this finding. Intriguingly, the team also plans to explore the possibility of reconstructing music that people imagine rather than hear, opening up even more fascinating possibilities. While the study is still awaiting peer review, you can actually listen to the generated musical clips online, which showcases the impressive advancement of AI in bridging the gap between human cognition and machine interpretation. This research has the potential to revolutionize our understanding of music and how our brains perceive it.
In some exciting news, a recent study has shown that using artificial intelligence (AI) in breast cancer screening is not only safe but can also significantly reduce the workload of radiologists. This comprehensive trial, one of the largest of its kind, has shed light on the potential benefits of AI-supported screening in detecting cancer at a similar rate as the traditional method of double reading, without increasing false positives. This could potentially alleviate some of the pressure faced by medical professionals. The effectiveness of AI in breast cancer screening is comparable to that of two radiologists working together, making it a valuable tool in early detection. Moreover, this technology can nearly halve the workload for radiologists, greatly improving efficiency and streamlining the screening process. An encouraging finding from the study is that there was no increase in the false-positive rate. In fact, AI support led to the detection of an additional 41 cancers. This suggests that the integration of AI into breast cancer screening could have a positive impact on patient outcomes. The study, which involved over 80,000 women primarily from Sweden, was a randomized controlled trial comparing AI-supported screening with standard care. The interim analysis indicates that AI usage in mammography is safe and has the potential to reduce radiologists’ workload by an impressive 44%. However, the lead author emphasizes the need for further understanding, trials, and evaluations to fully comprehend the extent of AI’s potential and its implications for breast cancer screening. This study opens up new possibilities for improving breast cancer screening and highlights the importance of continued research and development in the field of AI-assisted healthcare.
Let’s catch up on some of the latest happenings in the world of AI! Instagram has been busy working on labels for AI-generated content. This is great news, as it will help users distinguish between content created by humans and content generated by AI algorithms. Google has also made some updates to their generative search feature. Now, when you search for something, it not only shows you relevant text-based results but also related videos and images. This makes the search experience even more immersive and visually appealing. In the world of online dating, Tinder is testing an AI photo selection feature. This feature aims to help users build better profiles by selecting the most attractive and representative photos from their collection. It’s like having a personal AI stylist for your dating profile! Alibaba, the Chinese e-commerce giant, has rolled out an open-sourced AI model to compete with Meta’s Llama 2. This model will surely contribute to the advancement of AI technology and its various applications. IBM and NASA recently announced the availability of the watsonx.ai geospatial foundation model. This is a significant development in the field of AI, as it provides a powerful tool for understanding and analyzing geospatial data. Nvidia researchers have also made a breakthrough. They have developed a text-to-image personalization method called Perfusion. What sets Perfusion apart is its efficiency—it’s only 100KB in size and can be trained in just four minutes. This makes it much faster and more lightweight compared to other models out there. Moving on, Meta Platforms (formerly Facebook) has introduced an open-source AI tool called AudioCraft. This tool enables users to create music and audio based on text prompts. It comes bundled with three models—AudioGen, EnCodec, and MusicGen—and can be used for music creation, sound development, compression, and generation. In the entertainment industry, there is growing concern among movie extras that AI may replace them. Hollywood is already utilizing AI technologies, such as body scans, to create realistic virtual characters. It’s a topic that sparks debate and raises questions about the future of the industry. Finally, in a groundbreaking medical achievement, researchers have successfully used AI-powered brain implants to restore movement and sensation for a man who was paralyzed from the chest down. This remarkable feat demonstrates the immense potential that AI holds in the field of healthcare. As AI continues to advance and enter the mainstream, it’s clear that it has far-reaching implications across various industries and domains. Exciting times lie ahead!
Hey there, AI Unraveled podcast listeners! Have you been yearning to delve deeper into the world of artificial intelligence? Well, you’re in luck! I’ve got just the thing for you. Let me introduce you to “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” a must-read book by Etienne Noumen. This book is an essential guide that will help you expand your understanding of all things AI. From the basics to the more complex concepts, “AI Unraveled” covers it all. Whether you’re a newbie or a seasoned enthusiast, this book is packed with valuable information that will take your AI knowledge to new heights. And the best part? You can get your hands on a copy right now! It’s available at popular platforms like Shopify, Apple, Google, or Amazon. So, wherever you prefer to shop, you can easily snag a copy and embark on your AI adventure. Don’t miss out on this opportunity to demystify AI and satisfy your curiosity. Get your copy of “AI Unraveled” today, and let the unraveling begin!
In today’s episode, we discussed the development of a smartphone app for detecting stroke symptoms, the revolution of AI and ML in anti-money laundering efforts, the introduction of Meta’s AudioCraft for AI-generated audio and music, the tools available for musicians and content writers, an AI system that recreates music based on brain scans, the effectiveness of AI in breast cancer screening, the involvement of various big names in AI developments, and the hyper-realistic AI voices provided by the Wondercraft AI platform and Etienne Noumen’s book “AI Unraveled.” Thanks for listening to today’s episode, I’ll see you guys at the next one and don’t forget to subscribe!
Welcome to AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence, the podcast where we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From ChatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us! In today’s episode, we’ll cover the top 4 AI models for stock analysis/valuation, Google DeepMind’s AI system for medical data interpretation, Meta’s creation of AI chatbots called “personas” to boost engagement, an AI image generator altering a woman’s headshot, China’s use of AI in schools, and the Wondercraft AI platform and the book “AI Unraveled” by Etienne Noumen.
When it comes to stock analysis and valuation, artificial intelligence (AI) models can be incredibly helpful. If you’re looking for the top contenders in this field, here are four AI models that you should definitely check out:
First up is Boosted.ai. This platform offers AI stock screening, portfolio management, and risk management. With its advanced algorithms, it can help you make informed investment decisions.
Next, we have Danielfin. What sets this AI model apart is its easy-to-understand global AI Score, which rates s