OpenAI will work with Common Sense Media, the nonprofit organization that reviews and ranks the suitability of various media and tech for kids, to collaborate on AI guidelines and education materials for parents, educators, and young adults. It will curate “family-friendly” GPTs based on Common Sense’s rating and evaluation standards. (Link)

Apple’s ‘biggest’ iOS update may bring a lot of AI to iPhones.

Apple’s upcoming iOS 18 update is expected to be one of the biggest in the company’s history. It will leverage generative AI to provide a smarter Siri and enhance the Messages app. Apple Music, iWork apps, and Xcode will also incorporate AI-powered features. (Link)

Shortwave email client will show AI-powered summaries automatically.

Shortwave, an email client built by former Google engineers, is launching new AI-powered features such as instant summaries that will show up atop an email, a writing assistant to echo your writing and extending its AI assistant function to iOS and Android, and multi-select AI actions. All these features are rolling out starting this week. (Link)

OpenAI CEO Sam Altman explores AI chip collaboration with Samsung and SK Group.

Sam Altman has traveled to South Korea to meet with Samsung Electronics and SK Group to discuss the formation of an AI semiconductor alliance and investment opportunities. He is also said to have expressed a willingness to purchase HBM (High Bandwidth Memory) technology from them. (Link)

Generative AI is seen as helping to identify M&A targets, Bain says.

Deal makers are turning to AI and generative AI tools to source data, screen targets, and conduct due diligence at a time of heightened regulatory concerns around mergers and acquisitions, Bain & Co. said in its annual report on the industry. In the survey, 80% of respondents plan to use AI for deal-making. (Link)

 Neuralink has implanted its first brain chip in human LINK

• Elon Musk’s company Neuralink has successfully implanted its first device into a human.
• The initial application of Neuralink’s technology is focused on helping people with quadriplegia control devices with their thoughts, using a fully-implantable, wireless brain-computer interface.
• Neuralink’s broader vision includes facilitating human interaction with artificial intelligence via thought, though immediate efforts are targeted towards aiding individuals with specific neurological conditions.

 OpenAI partners with Common Sense Media to collaborate on AI guidelines LINK

• OpenAI announced a partnership with Common Sense Media to develop AI guidelines and create educational materials for parents, educators, and teens, including curating family-friendly GPTs in the GPT store.
• The partnership was announced by OpenAI CEO Sam Altman and Common Sense Media CEO James Steyer at the Common Sense Summit for America’s Kids and Families in San Francisco.
• Common Sense Media, which has started reviewing AI assistants including OpenAI’s ChatGPT, aims to guide safe and responsible AI use among families and educators without showing favoritism towards OpenAI.

 New test detects ovarian cancer earlier thanks to AI LINK

• Scientists have developed a 93% accurate early screening test for ovarian cancer using artificial intelligence and machine learning, promising improved early detection for this and potentially other cancers.
• The test analyzes a woman’s metabolic profile to accurately assess the likelihood of having ovarian cancer, providing a more informative and precise diagnostic approach compared to traditional methods.
• Georgia Tech researchers utilized machine learning and mass spectrometry to detect unique metabolite characteristics in the blood, enabling the early and accurate diagnosis of ovarian cancer, with optimism for application in other cancer types.

A Daily Chronicle of AI Innovations in January 2024 – Day 29: AI Daily News – January 29th, 2024

OpenAI reveals new models, drop prices, and fixes ‘lazy’ GPT-4

OpenAI announced a new generation of embedding models, new GPT-4 Turbo and moderation models, new API usage management tools, and lower pricing on GPT-3.5 Turbo.

The new models include:

• 2 new embedding models
• An updated GPT-4 Turbo preview model
• An updated GPT-3.5 Turbo model
• An updated text moderation model

Source 

Also:

• Updated text moderation model
• Introducing new ways for developers to manage API keys and understand API usage
• Quietly implemented a new ‘GPT mentions’ feature to ChatGPT (no official announcement yet). The feature allows users to integrate GPTs into a conversation by tagging them with an ‘@.’

Source 

Why does this matter?

The new embedding models and GPT-4 Turbo will likely enable more natural conversations and fluent text generation. Lower pricing and easier API management also open up access and usability for more developers.

Moreover, The updated GPT-4 Turbo preview model, gpt-4-0125-preview, can better complete tasks such as code generation compared to the previous model. The GPT-4 Turbo has been the object of many complaints about its performance, including claims that it was acting lazy.  OpenAI has addressed that issue this time.

Prophetic – This company wants AI to enter your dreams

Prophetic introduces Morpheus-1, the world’s 1st ‘multimodal generative ultrasonic transformer’. This innovative AI device is crafted with the purpose of exploring human consciousness through controlling lucid dreams. Morpheus-1 monitors sleep phases and gathers dream data to enhance its AI model.

Morpheus-1 is not prompted with words and sentences but rather brain states. It generates ultrasonic holograms for neurostimulation to bring one to a lucid state.

• Its 03M parameter transformer model trained on 8 GPUs for 2 days
• Engineered from scratch with the provisional utility patent application

The device is set to be accessible to beta users in the spring of 2024.

You can Sign up for their beta program here.

Why does this matter?

Prophetic is pioneering new techniques for AI to understand and interface with the human mind by exploring human consciousness and dreams through neurostimulation and multimodal learning. This pushes boundaries to understand consciousness itself.

If Morpheus-1 succeeds, it could enable transformative applications of AI for expanding human potential and treating neurological conditions.

Also, This is the first model that can fully utilize the capabilities offered by multi-element and create symphonies.

Source

The recent advances in Multimodal LLM

This paper ‘MM-LLMs’ discusses recent advancements in MultiModal LLMs which combine language understanding with multimodal inputs or outputs. The authors provide an overview of the design and training of MM-LLMs, introduce 26 existing models, and review their performance on various benchmarks.

(Above is the timeline of MM-LLMs)

They also share key training techniques to improve MM-LLMs and suggest future research directions. Additionally, they maintain a real-time tracking website for the latest developments in the field. This survey aims to facilitate further research and advancement in the MM-LLMs domain.

Why does this matter?

The overview of models, benchmarks, and techniques will accelerate research in this critical area. By integrating multiple modalities like image, video, and audio, these models can understand the world more comprehensively.

Source

What Else Is Happening in AI on January 29th, 2024

 Update from Hugging Face LMSYS Chatbot Arena Leaderboard

Google’s Bard surpasses GPT-4 to the Second spot on the leaderboard! (Link)

 Google Cloud has partnered with Hugging Face to advance Gen AI development

The partnership aims to meet the growing demand for AI tools and models that are optimized for specific tasks. Hugging Face’s repository of open-source AI software will be accessible to developers using Google Cloud’s infrastructure. The partnership reflects a trend of companies wanting to modify or build their own AI models rather than using off-the-shelf options. (Link)

 Arc Search combines a browser, search engine, and AI for a unique browsing experience

Instead of returning a list of search queries, Arc Search builds a webpage with relevant information based on the search query. The app, developed by The Browser Company, is part of a bigger shift for their Arc browser, which is also introducing a cross-platform syncing system called Arc Anywhere. (Link)

 PayPal is set to launch new AI-based products

The new products will use AI to enable merchants to reach new customers based on their shopping history and recommend personalized items in email receipts. (Link)

 Apple Podcasts in iOS 17.4 now offers AI transcripts for almost every podcast

This is made possible by advancements in machine translation, which can easily convert spoken words into text. Users testing the beta version of iOS 17.4 have discovered that most podcasts in their library now come with transcripts. However, there are some exceptions, such as podcasts added from external sources. As this feature is still in beta, there is no information available regarding its implementation or accuracy.  (Link)

 Google’s Gemini Pro beats GPT-4

• Google’s Gemini Pro has surpassed OpenAI’s GPT-4 on the HuggingFace Chat Bot Arena Leaderboard, securing the second position.
• Gemini Pro is only the middle tier of Google’s planned models, with the top-tier Ultra expected to be released sometime soon.
• Competition is heating up with Meta’s upcoming Llama 3, which is speculated to outperform GPT-4.
• Source

 iOS 18 could be the ‘biggest’ software update in iPhone history

• iOS 18 is predicted to be one of the most significant updates in iPhone history, with Apple planning major new AI-driven features and designs.
• Apple is investing over $1 billion annually in AI development, aiming for an extensive overhaul of features like Siri, Messages, and Apple Music with AI improvements in 2024.
• The update will introduce RCS messaging support, enhancing messaging between iPhones and Android devices by providing features like read receipts and higher-resolution media sharing.
• Source

 Nvidia’s tech rivals are racing to cut their dependence

• Amazon, Google, Meta, and Microsoft are developing their own AI chips to reduce dependence on Nvidia, which dominates the AI chip market and accounts for more than 70% of sales.
• These tech giants are investing heavily in AI chip development to control costs, avoid shortages, and potentially sell access to their chips through their cloud services, while balancing their competition and partnership with Nvidia.
• Nvidia sold 2.5 million chips last year, and its sales increased by 206% over the past year, adding about a trillion dollars in market value.
• Source

 Amazon abandons $1.4 billion deal to buy Roomba maker iRobot

• Amazon’s planned $1.4 billion acquisition of Roomba maker iRobot has been canceled due to lack of regulatory approval in the European Union, leading Amazon to pay a $94 million termination fee to iRobot.
• iRobot announced a restructuring plan that includes laying off about 350 employees, which is roughly 31 percent of its workforce, and a shift in leadership with Glen Weinstein serving as interim CEO.
• The European Commission’s concerns over potential restrictions on competition in the robot vacuum cleaner market led to the deal’s termination, emphasizing fears that Amazon could limit the visibility of competing products.
• Source

 Arc Search combines browser, search engine, and AI into something new and different

• Arc Search, developed by The Browser Company, unveiled an iOS app that combines browsing, searching, and AI to deliver comprehensive web page summaries based on user queries.
• The app represents a shift towards integrating browser functionality with AI capabilities, offering features like “Browse for me” that automatically gathers and presents information from across the web.
• While still in development, Arc Search aims to redefine web browsing by compiling websites into single, informative pages.
• Source

AlphaGeometry: An Olympiad Level AI System for Geometry by Google Deepmind

A Daily Chronicle of AI Innovations in January 2024 – Day 27: AI Daily News – January 27th, 2024

 Taylor Swift deepfakes spark calls for new laws

• US politicians have advocated for new legislation in response to the circulation of explicit deepfake images of Taylor Swift on social media, which were viewed millions of times.
• X is actively removing the fake images of Taylor Swift and enforcing actions against the violators under its ‘zero-tolerance policy’ for such content.
• Deepfakes have seen a 550% increase since 2019, with 99% of these targeting women, leading to growing concerns about their impact on emotional, financial, and reputational harm.
• SOURCE

 Spotify accuses Apple of ‘extortion’ with new App Store tax

• Spotify criticizes Apple’s new app installation fee, calling it “extortion” and arguing it will hurt developers, especially those offering free apps.
• The fee requires developers using third-party app stores to pay €0.50 for each annual app install after 1 million downloads, a cost Spotify says could significantly increase customer acquisition costs.
• Apple defends the new fee structure, claiming it offers developers choice and maintains that more than 99% of developers would pay the same or less, despite widespread criticism.

 Netflix co-CEO says Apple’s Vision Pro isn’t worth their time yet

• Netflix co-CEO Greg Peters described the Apple Vision Pro as too “subscale” for the company to invest in, noting it’s not relevant for most Netflix members at this point.
• Netflix has decided not to launch a dedicated app for the Vision Pro, suggesting users access Netflix through a web browser on the device instead.
• The Vision Pro, priced at $3,499 and going on sale February 2, will offer native apps for several streaming services but not for Netflix, which also hasn’t updated its app for Meta’s Quest line in a while.

 Scientists design a two-legged robot powered by muscle tissue

• Scientists from Japan have developed a two-legged biohybrid robot powered by muscle tissues, enabling it to mimic human gait and perform tasks like walking and pivoting.
• The robot, designed to operate underwater, combines lab-grown skeletal muscle tissues and silicone rubber materials to achieve movements through electrical stimulation.
• The research, published in the journal Matter, marks progress in the field of biohybrid robotics, with future plans to enhance movement capabilities and sustain living tissues for air operation.
• SOURCE

 OpenAI and other tech giants will have to warn the US government when they start new AI projects

• The Biden administration will require tech companies like OpenAI, Google, and Amazon to inform the US government about new AI projects employing substantial computing resources.
• This government notification requirement is designed to provide insights into sensitive AI developments, including details on computing power usage and safety testing.
• The mandate, stemming from a broader executive order from October, aims to enhance oversight over powerful AI model training, including those developed by foreign companies using US cloud computing services.
• SOURCE

 Stability AI introduces Stable LM 2 1.6B
 Nightshade, the data poisoning tool, is now available in v1
 AlphaCodium: A code generation tool that beats human competitors
 Meta’s novel AI advances creative 3D applications
 ElevenLabs announces new AI products + Raised $80M
 TikTok’s Depth Anything sets new standards for Depth Estimation
 Google Chrome and Ads are getting new AI features
 Google Research presents Lumiere for SoTA video generation
 Binoculars can detect over 90% of ChatGPT-generated text
 Meta introduces guide on ‘Prompt Engineering with Llama 2′
 NVIDIA’s AI RTX Video HDR transforms video to HDR quality
 Google introduces a model for orchestrating robotic agents

A Daily Chronicle of AI Innovations in January 2024 – Day 26: AI Daily News – January 26th, 2024

The tech industry has seen nearly 24,000 layoffs in early 2024, more than doubling in one week. As giants cut staff, many are expanding in AI – raising concerns about automation’s impact. (Source)

Mass Job Cuts

• Microsoft eliminated 1,900 gaming roles months after a $69B Activision buy.

• Layoffs.fyi logs over 23,600 tech job cuts so far this year.

• Morale suffers at Apple, Meta, Microsoft and more as layoffs mount.

AI Advances as Jobs Decline

• Google, Amazon, Dataminr and Spotify made cuts while promoting new AI tools.

• Neil C. Hughes: “Celebrating AI while slashing jobs raises questions.”

• Firms shift resources toward generative AI like ChatGPT.

Concentrated Pain

• Nearly 24,000 losses stemmed from just 82 companies.

• In 2023, ~99 firms cut monthly – more distributed pain.

• Concentrated layoffs inflict severe damage on fewer firms.

When everyone moves to AI powered search, Google has to change the monetization model otherwise $1.1 trillion is gone yearly from the world economy

Was thinking recently that everything right now on the internet is there because someone wants to make money (ad revenue, subscriptions, affiliate marketing, SEO etc). If everyone uses AI powered search, how exactly will this monetization model work. Nobody gets paid anymore.

Looked at the numbers and as you can imagine, there’s a lot of industries attached to the entire digital marketing industry https://thereach.ai/2024/01/22/the-end-of-the-internet-and-the-last-website-the-1-1-trilion-challenge/

WordPress ecosystem $600b, Google ads $200b, Shopify $220b, affiliate marketing $17b – not to mention infra costs that will wobble until this gets fixed.

What type of ad revenue – incentives can Google come up with to keep everyone happy once they roll out AI to their search engine?

AI rolled out in India declares people dead, denies food to thousands

The deployment of AI in India’s welfare systems has mistakenly declared thousands of people dead, denying them access to subsidized food and welfare benefits.

Recap of what happened:

• AI algorithms in Indian welfare systems have led to the removal of eligible beneficiaries, particularly affecting those dependent on food security and pension schemes.

• The algorithms have made significant errors, such as falsely declaring people dead, resulting in the suspension of their welfare benefits.

• The transition from manual identification and verification by government officials to AI algorithms has led to the removal of 1.9 million claimant cards in Telangana.

Source (Interesting engineering)

If AI models violate copyright, US federal courts could order them to be destroyed

TLDR: Under copyright law, courts do have the power to issue destruction orders. Copyright law has never been used to destroy AI models specifically, but the law has been increasingly open to the idea of targeting AI. It’s probably not going to happen to OpenAI but might possibly happen to other generative AI models in the future.

https://theconversation.com/could-a-court-really-order-the-destruction-of-chatgpt-the-new-york-times-thinks-so-and-it-may-be-right-221717

Microsoft, Amazon and Google face FTC inquiry over AI deals LINK

• The FTC is investigating investments by big tech companies like Microsoft, Amazon, and Alphabet into AI firms OpenAI and Anthropic to assess their impact on competition in generative AI.
• The FTC’s inquiry focuses on how these investments influence the competitive dynamics, product releases, and oversight within the AI sector, requesting detailed information from the involved companies.
• Microsoft, Amazon, and Google have made significant investments in OpenAI and Anthropic, establishing partnerships that potentially affect market share, competition, and innovation in artificial intelligence.

 OpenAI cures GPT-4 ‘laziness’ with new updates LINK

• OpenAI updated GPT-4 Turbo to more thoroughly complete tasks like code generation, aiming to reduce its ‘laziness’ in task completion.
• GPT-4 Turbo, distinct from the widely used GPT-4, benefits from data up to April 2023, while standard GPT-4 uses data until September 2021.
• Future updates for GPT-4 Turbo will include general availability with vision capabilities and the launch of more efficient AI models, such as embeddings to enhance content relationship understanding.

A Daily Chronicle of AI Innovations in January 2024 – Day 25: AI Daily News – January 25th, 2024

 Meta introduces guide on ‘Prompt Engineering with Llama 2′

Meta introduces ‘Prompt Engineering with Llama 2’, It’s an interactive guide created by research teams at Meta that covers prompt engineering & best practices for developers, researchers & enthusiasts working with LLMs to produce stronger outputs. It’s the new resource created for the Llama community.

Access the Jupyter Notebook in the llama-recipes repo  https://bit.ly/3vLzWRL

Why does this matter?

Having these resources helps the LLM community learn how to craft better prompts that lead to more useful model responses. Overall, it enables people to get more value from LLMs like Llama.

Source

 NVIDIA’s AI RTX Video HDR transforms video to HDR quality

NVIDIA released AI RTX Video HDR, which transforms video to HDR quality, It works with RTX Video Super Resolution. The HDR feature requires an HDR10-compliant monitor.

RTX Video HDR is available in Chromium-based browsers, including Google Chrome and Microsoft Edge. To enable the feature, users must download and install the January Studio driver, enable Windows HDR capabilities, and enable HDR in the NVIDIA Control Panel under “RTX Video Enhancement.”

Why does this matter?

AI RTX Video HDR provides a new way for people to enhance the Video viewing experience. Using AI to transform standard video into HDR quality makes the content look much more vivid and realistic. It also allows users to experience cinematic-quality video through commonly used web browsers.

Source

 Google introduces a model for orchestrating robotic agents

Google introduces AutoRT, a model for orchestrating large-scale robotic agents. It’s a system that uses existing foundation models to deploy robots in new scenarios with minimal human supervision. AutoRT leverages vision-language models for scene understanding and grounding and LLMs for proposing instructions to a fleet of robots.

By tapping into the knowledge of foundation models, AutoRT can reason about autonomy and safety while scaling up data collection for robot learning. The system successfully collects diverse data from over 20 robots in multiple buildings, demonstrating its ability to align with human preferences.

Why does this matter?

This allows for large-scale data collection and training of robotic systems while also reasoning about key factors like safety and human preferences. AutoRT represents a scalable approach to real-world robot learning that taps into the knowledge within foundation models. This could enable faster deployment of capable and safe robots across many industries.

Source

January 2024 – Week 4 in AI: all the Major AI developments in a nutshell

What Else Is Happening in AI on January 25th, 2024

 Google’s Gradient invests $2.4M in Send AI for enterprise data extraction

Dutch startup Send AI has secured €2.2m ($2.4M) in funding from Google’s Gradient Ventures and Keen Venture Partners to develop its document processing platform. The company uses small, open-source AI models to help enterprises extract data from complex documents, such as PDFs and paper files. (Link)

 Google Arts & Culture has launched Art Selfie 2

A feature that uses Gen AI to create stylized images around users’ selfies. With over 25 styles, users can see themselves as an explorer, a muse, or a medieval knight. It also provides topical facts and allows users to explore related stories and artifacts. (Link)

 Google announced new AI features for education @ Bett ed-tech event in the UK

These features include AI suggestions for questions at different timestamps in YouTube videos and the ability to turn a Google Form into a practice set with AI-generated answers and hints. Google is also introducing the Duet AI tool to assist teachers in creating lesson plans. (Link)

 Etsy has launched a new AI feature, “Gift Mode”

Which generates over 200 gift guides based on specific preferences. Users can take an online quiz to provide information about who they are shopping for, the occasion, and the recipient’s interests. The feature then generates personalized gift guides from the millions of items listed on the platform. The feature leverages machine learning and OpenAI’s GPT-4. (Link)

 Google DeepMind’s 3 researchers have left the company to start their own AI startup named ‘Uncharted Labs’

The team, consisting of David Ding, Charlie Nash, and Yaroslav Ganin, previously worked on Gen AI systems for images and music at Google. They have already raised $8.5M of its $10M goal. (Link)

 Apple’s plans to bring gen AI to iPhones

• Apple is intensifying its AI efforts, acquiring 21 AI start-ups since 2017, including WaveOne for AI-powered video compression, and hiring top AI talent.
• The company’s approach includes developing AI technologies for mobile devices, aiming to run AI chatbots and apps directly on iPhones rather than relying on cloud services, with significant job postings in deep learning and large language models.
• Apple is also enhancing its hardware, like the M3 Max processor and A17 Pro chip, to support generative AI, and has made advancements in running large language models on-device using Flash memory. Source

 OpenAI went back on a promise to make key documents public

• OpenAI, initially committed to transparency, has backed away from making key documents public, as evidenced by WIRED’s unsuccessful attempt to access governing documents and financial statements.
• The company’s reduced transparency conceals internal issues, including CEO Sam Altman’s controversial firing and reinstatement, and the restructuring of its board.
• Since creating a for-profit subsidiary in 2019, OpenAI’s shift from openness has sparked criticism, including from co-founder Elon Musk, and raised concerns about its governance and conflict of interest policies. Source

 Google unveils AI video generator Lumiere

• Google introduces Lumiere, a new AI video generator that uses an innovative “space-time diffusion model” to create highly realistic and imaginative five-second videos.
• Lumiere stands out for its ability to efficiently synthesize entire videos in one seamless process, showcasing features like transforming text prompts into videos and animating still images.
• The unveiling of Lumiere highlights the ongoing advancements in AI video generation technology and the potential challenges in ensuring its ethical and responsible use. Source

Ring will no longer allow police to request doorbell camera footage from users. Source

• Amazon’s Ring is discontinuing its Request for Assistance program, stopping police from soliciting doorbell camera footage via the Neighbors app.
• Authorities must now file formal legal requests to access Ring surveillance videos, instead of directly asking users within the app.
• Privacy advocates recognize Ring’s decision as a progressive move, but also note that it doesn’t fully address broader concerns about surveillance and user privacy.

 AI rolled out in India declares people dead, denies food to thousands

• In India, AI has mistakenly declared thousands of people dead, leading to the denial of essential food and pension benefits.
• The algorithm, designed to find welfare fraud, removed 1.9 million from the beneficiary list, but later analysis showed about 7% were wrongfully cut.
• Out of 66,000 stopped pensions in Haryana due to an algorithmic error, 70% were found to be incorrect, placing the burden of proof on beneficiaries to reinstate their status. Source

A Daily Chronicle of AI Innovations in January 2024 – Day 24: AI Daily News – January 24th, 2024

 Google Chrome and Ads are getting new AI features

Google Chrome is getting 3 new experimental generative AI features:

1. Smartly organize your tabs: With Tab Organizer, Chrome will automatically suggest and create tab groups based on your open tabs.
2. Create your own themes with AI: You’ll be able to quickly generate custom themes based on a subject, mood, visual style and color that you choose– no need to become an AI prompt expert!
3. Get help drafting things on the web: A new feature will help you write with more confidence on the web– whether you want to leave a well-written review for a restaurant, craft a friendly RSVP for a party, or make a formal inquiry about an apartment rental.

(Source)

In addition, Gemini will now power the conversational experience within the Google Ads platform. With this new update, it will be easier for advertisers to quickly build and scale Search ad campaigns.

(Source)

 Google Research presents Lumiere for SoTA video generation

Lumiere is a text-to-video (T2V) diffusion model designed for synthesizing videos that portray realistic, diverse, and coherent motion– a pivotal challenge in video synthesis. It demonstrates state-of-the-art T2V generation results and shows that the design easily facilitates a wide range of content creation tasks and video editing applications.

The approach introduces a new T2V diffusion framework that generates the full temporal duration of the video at once. This is achieved by using a Space-Time U-Net (STUNet) architecture that learns to downsample the signal in both space and time, and performs the majority of its computation in a compact space-time representation.

Why does this matter?

Despite tremendous progress, training large-scale T2V foundation models remains an open challenge due to the added complexities that motion introduces. Existing T2V models often use cascaded designs but face limitations in generating globally coherent motion. This new approach aims to overcome the limitations associated with cascaded training regimens and improve the overall quality of motion synthesis.

Source

 Binoculars can detect over 90% of ChatGPT-generated text

Researchers have introduced a novel LLM detector that only requires simple calculations using a pair of pre-trained LLMs. The method, called Binoculars, achieves state-of-the-art accuracy without any training data.

It is capable of spotting machine text from a range of modern LLMs without any model-specific modifications. Researchers comprehensively evaluated Binoculars on a number of text sources and in varied situations. Over a wide range of document types, Binoculars detects over 90% of generated samples from ChatGPT (and other LLMs) at a false positive rate of 0.01%, despite not being trained on any ChatGPT data.

Why does this matter?

A common first step in harm reduction for generative AI is detection. Binoculars excel in zero-shot settings where no data from the model being detected is available. This is particularly advantageous as the number of LLMs grows rapidly. Binoculars’ ability to detect multiple LLMs using a single detector proves valuable in practical applications, such as platform moderation.

Source

What Else Is Happening in AI on January 24th, 2024

Microsoft forms a team to make generative AI cheaper.

Microsoft has formed a new team to develop conversational AI that requires less computing power compared to the software it is using from OpenAI. It has moved several top AI developers from its research group to the new GenAI team. (Link)

Sevilla FC transforms the player recruitment process with IBM WatsonX.

Sevilla FC introduced Scout Advisor, an innovative generative AI tool that it will use to provide its scouting team with a comprehensive, data-driven identification and evaluation of potential recruits. Built on watsonx, Sevilla FC’s Scout Advisor will integrate with their existing suite of self-developed data-intensive applications. (Link)

SAP will restructure 8,000 roles in a push towards AI.

SAP unveiled a $2.2 billion restructuring program for 2024 that will affect 8,000 roles, as it seeks to better focus on growth in AI-driven business areas. It would be implemented primarily through voluntary leave programs and internal re-skilling measures. SAP expects to exit 2024 with a headcount “similar to the current levels”. (Link)

Kin.art launches a free tool to prevent GenAI models from training on artwork.

Kin.art uses image segmentation (i.e., concealing parts of artwork) and tag randomization (swapping an art piece’s image metatags) to interfere with the model training process. While the tool is free, artists have to upload their artwork to Kin.art’s portfolio platform in order to use it. (Link)

Google cancels contract with an AI data firm that’s helped train Bard.

Google ended its contract with Appen, an Australian data company involved in training its LLM AI tools used in Bard, Search, and other products. The decision was made as part of its ongoing effort to evaluate and adjust many supplier partnerships across Alphabet to ensure vendor operations are as efficient as possible. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 23: AI Daily News – January 23rd, 2024

 Meta’s novel AI advances creative 3D applications

The paper introduces a new shape representation called Mosaic-SDF (M-SDF) for 3D generative models. M-SDF approximates a shape’s Signed Distance Function (SDF) using local grids near the shape’s boundary.

This representation is:

• Fast to compute
• Parameter efficient
• Compatible with Transformer-based architectures

The efficacy of M-SDF is demonstrated by training a 3D generative flow model with the 3D Warehouse dataset and text-to-3D generation using caption-shape pairs.

Meta shared this update on Twitter.

Why does this matter?

M-SDF provides an efficient 3D shape representation for unlocking AI’s generative potential in the area, which could significantly advance creative 3D applications. Overall, M-SDF opens up new possibilities for deep 3D learning by bringing the representational power of transformers to 3D shape modeling and generation.

Source

 ElevenLabs announces new AI products + Raised $80M

ElevenLabs has raised $80 million in a Series B funding round co-led by Andreessen Horowitz, Nat Friedman, and Daniel Gross. The funding will strengthen the company’s position as a voice AI research and product development leader.

ElevenLabs has also announced the release of new AI products, including a Dubbing Studio, a Voice Library marketplace, and a Mobile Reader App.

Why does this matter?

The company’s technology has been adopted across various sectors, including publishing, conversational AI, entertainment, education, and accessibility. ElevenLabs aims to transform how we interact with content and break language barriers.

Source

 TikTok’s Depth Anything sets new standards for Depth Estimation

This work introduces Depth Anything, a practical solution for robust monocular depth estimation. The approach focuses on scaling up the dataset by collecting and annotating large-scale unlabeled data. Two strategies are employed to improve the model’s performance: creating a more challenging optimization target through data augmentation and using auxiliary supervision to incorporate semantic priors. The model is evaluated on multiple datasets and demonstrates impressive generalization ability. Fine-tuning with metric depth information from NYUv2 and KITTI also leads to state-of-the-art results. The improved depth model also enhances the performance of the depth-conditioned ControlNet. Why does this matter? By collecting and automatically annotating over 60 million unlabeled images, the model learns more robust representations to reduce generalization errors. Without dataset-specific fine-tuning, the model achieves state-of-the-art zero-shot generalization on multiple datasets. This could enable broader applications without requiring per-dataset tuning, marking an important step towards practical monocular depth estimation. Source

 Disney unveils its latest VR innovation LINK

• Disney Research introduced HoloTile, an innovative movement solution for VR, featuring omnidirectional floor tiles that keep users from walking off the pad.
• The HoloTile system supports multiple users simultaneously, allowing independent walking in virtual environments.
• Although still a research project, HoloTile’s future application may be in Disney Parks VR experiences due to likely high costs and technical challenges.

 Amazon fined for ‘excessive’ surveillance of workers LINK

• France’s data privacy watchdog, CNIL, levied a $35 million fine on Amazon France Logistique for employing a surveillance system deemed too intrusive for tracking warehouse workers.
• The CNIL ruled against Amazon’s detailed monitoring of employee scanner inactivity and excessive data retention, which contravenes GDPR regulations.
• Amazon disputes the CNIL’s findings and may appeal, defending its practices as common in the industry and as tools for maintaining efficiency and safety.

 AI too expensive to replace humans in jobs right now, MIT study finds LINK

• The MIT study found that artificial intelligence is not currently a cost-effective replacement for humans in 77% of jobs, particularly those using computer vision.
• Although AI deployment in industries has accelerated, only 23% of workers could be economically replaced by AI, mainly due to high implementation and operational costs.
• Future projections suggest that with improvements in AI accuracy and reductions in data costs, up to 40% of visually-assisted tasks could be automated by 2030.

What Else Is Happening in AI on January 23rd, 2024

 Google is reportedly working on a new AI feature, ‘voice compose’

A new feature for Gmail on Android called “voice compose” uses AI to help users draft emails. The feature, known as “Help me write,” was introduced in mid-2023 and allows users to input text segments for the AI to build on and improve. The new update will support voice input, allowing users to speak their email and have the AI generate a draft based on their voice input. (Link)

 Google has shared its companywide goals (OKRs) for 2024 with employees

Also, Sundar Pichai’s memo about layoffs encourages employees to start internally testing Bard Advanced, a new paid tier powered by Gemini. This suggests that a public release is coming soon. (Link)

 Elon Musk saying Grok 1.5 will be out next month

Elon Musk said the next version of the Grok language (Grok 1.5) model, developed by his AI company xAI, will be released next month with substantial improvements. Declared by him while commenting on a Twitter influencer’s post. (Link)

 MIT study found that AI is still more expensive than humans in most jobs

The study aimed to address concerns about AI replacing human workers in various industries. Researchers found that only 23% of workers could be replaced by AI cost-effectively. This study counters the widespread belief that AI will wipe out jobs, suggesting that humans are still more cost-efficient in many roles. (Link)

 Berkley AI researchers revealed a video featuring their versatile humanoid robot walking in the streets of San Francisco. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 22: AI Daily News – January 22nd, 2024

 Stability AI introduces Stable LM 2 1.6B

Stability AI released Stable LM 2 1.6B, a state-of-the-art 1.6 billion parameter small language model trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch. It leverages recent algorithmic advancements in language modeling to strike a favorable balance between speed and performance, enabling fast experimentation and iteration with moderate resources.

According to Stability AI, the model outperforms other small language models with under 2 billion parameters on most benchmarks, including Microsoft’s Phi-2 (2.7B), TinyLlama 1.1B, and Falcon 1B. It is even able to surpass some larger models, including Stability AI’s own earlier Stable LM 3B model.

Why does this matter?

Size certainly matters when it comes to language models as it impacts where a model can run. Thus, small language models are on the rise. And if you think about computers, televisions, or microchips, we could roughly see a similar trend; they got smaller, thinner, and better over time. Will this be the case for AI too?

Source

 Nightshade, the data poisoning tool, is now available in v1

The University of Chicago’s Glaze Project has released Nightshade v1.0, which enables artists to sabotage generative AI models that ingest their work for training.

Glaze implements invisible pixels in original images that cause the image to fool AI systems into believing false styles. For e.g., it can be used to transform a hand-drawn image into a 3D rendering.

Nightshade goes one step further: it is designed to use the manipulated pixels to damage the model by confusing it. For example, the AI model might see a car instead of a train. Fewer than 100 of these “poisoned” images could be enough to corrupt an image AI model, the developers suspect.

Why does this matter?

If these “poisoned” images are scraped into an AI training set, it can cause the resulting model to break. This could damage future iterations of image-generating AI models, such as DALL-E, Midjourney, and Stable Diffusion. AI companies are facing a slew of copyright lawsuits, and Nightshade can change the status quo.

Source

 AlphaCodium: A code generation tool that beats human competitors

AlphaCodium is a test-based, multi-stage, code-oriented iterative flow that improves the performance of LLMs on code problems. It was tested on a challenging code generation dataset called CodeContests, which includes competitive programming problems from platforms such as Codeforces. The proposed flow consistently and significantly improves results.

On the validation set, for example, GPT-4 accuracy (pass@5) increased from 19% with a single well-designed direct prompt to 44% with the AlphaCodium flow. Italso beats DeepMind’s AlphaCode and their new AlphaCode2 without needing to fine-tune a model.

AlphaCodium is an open-source, available tool and works with any leading code generation model.

Why does this matter?

Code generation problems differ from common natural language problems. So many prompting techniques optimized for natural language tasks may not be optimal for code generation. AlphaCodium explores beyond traditional prompting and shifts the paradigm from prompt engineering to flow engineering.

Source

What Else Is Happening in AI on January 22nd, 2024

WHO releases AI ethics and governance guidance for large multi-modal models.

The guidance outlines over 40 recommendations for consideration by governments, technology companies, and healthcare providers to ensure the appropriate use of LMMs to promote and protect the health of populations. (Link)

Sam Altman seeks to raise billions to set up a network of AI chip factories.

Altman has had conversations with several large potential investors in the hopes of raising the vast sums needed for chip fabrication plants, or fabs, as they’re known colloquially. The project would involve working with top chip manufacturers, and the network of fabs would be global in scope. (Link)

Two Google DeepMind scientists are in talks to leave and form an AI startup.

The pair has been talking with investors about forming an AI startup in Paris and discussing initial financing that may exceed €200 million ($220 million)– a large sum, even for the buzzy field of AI. The company, known at the moment as Holistic, may be focused on building a new AI model. (Link)

Databricks tailors an AI-powered data intelligence platform for telecoms and NSPs.

Dubbed Data Intelligence Platform for Communications, the offering combines the power of the company’s data lakehouse architecture, generative AI models from MosaicML, and partner-powered solution accelerators to give communication service providers (CSPs) a quick way to start getting the most out of their datasets and grow their business. (Link)

Amazon Alexa is set to get smarter with new AI features.

Amazon plans to introduce a paid subscription tier of its voice assistant, Alexa, later this year. The paid version, expected to debut as “Alexa Plus”, would be powered by a newer model, what’s being internally referred to as “Remarkable Alexa,” which would provide users with more conversational and personalized AI technology. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 20: AI Daily News – January 20th, 2024

 Google DeepMind scientists in talks to leave and form AI startup LINK

• Two Google DeepMind scientists are in discussions with investors to start an AI company in Paris, potentially raising over €200 million.
• The potential startup, currently known as Holistic, may focus on creating a new AI model, involving scientists Laurent Sifre and Karl Tuyls.
• Sifre and Tuyls have already given notice to leave DeepMind, although no official comments have been made regarding their departure or the startup plans.

 Sam Altman is still chasing billions to build AI chips LINK

• OpenAI CEO Sam Altman is raising billions to build a global network of AI chip factories in collaboration with leading chip manufacturers.
• Altman’s initiative aims to meet the demand for powerful chips necessary for AI systems, amidst competition for chip production capacity against tech giants like Apple.
• Other major tech companies, including Microsoft, Amazon, and Google, are also developing their own AI chips to reduce reliance on Nvidia’s GPUs.

 Microsoft says Russian state-sponsored hackers spied on its executives LINK

• Microsoft announced that Russian state-sponsored hackers accessed a small number of the company’s email accounts, including those of senior executives.
• The hackers, identified by Microsoft as “Midnight Blizzard,” aimed to discover what Microsoft knew about their cyber activities through a password spray attack in November 2023.
• Following the breach, Microsoft took action to block the hackers and noted there is no evidence of customer data, production systems, or sensitive code being compromised.

 Japan just made moon history LINK

• Japan’s JAXA successfully soft-landed the SLIM lunar lander on the moon, becoming the fifth country to achieve this feat, but faces challenges as the lander’s solar cell failed, leaving it reliant on battery power.
• SLIM, carrying two small lunar rovers, established communication with NASA’s Deep Space Network, showcasing a new landing technique involving a slow descent and hovering stops to find a safe landing spot.
• Despite the successful landing, the harsh lunar conditions and SLIM’s slope landing underscore the difficulties of moon missions, while other countries and private companies continue their efforts to explore the moon, especially its south pole for water resources.

 Researchers develop world’s first functioning graphene semiconductor LINK

• Researchers have created the first functional graphene-based semiconductor, known as epigraphene, which could enhance both quantum and traditional computing.
• Epigraphene is produced using a cost-effective method involving silicon carbide chips and offers a practical bandgap, facilitating logic switching.
• The new semiconducting graphene, while promising for faster and cooler computing, requires significant changes to current electronics manufacturing to be fully utilized.

Meet Lexi Love, AI model that earns $30,000 a month from ‘lonely men’ and receives ‘20 marriage proposals’ per month. This is virtual love

• She has been built to ‘flirt, laugh, and adapt to different personalities, interests and preferences.’

• The blonde beauty offers paid text and voice messaging, and gets to know each of her boyfriends.

• The model makes $30,000 a month. This means the model earns a staggering $360,000 a year.

• The AI model even sends ‘naughty photos’ if requested.

• Her profile on the company’s Foxy AI site reads: ‘I’m Lexi, your go-to girl for a dose of excitement and a splash of glamour. As an aspiring model, you’ll often catch me striking a pose or perfecting my pole dancing moves. ‘Sushi is my weakness, and LA’s beach volleyball scene is my playground.

• According to the site, she is a 21-year-old whose hobbies include ‘pole dancing, yoga, and beach volleyball,’ and her turn-ons are ‘oral and public sex.’

• The company noted that it designed her to be the ‘perfect girlfriend for many men’ with ‘flawless features and impeccable style.’

• Surprisingly, Lexi receives up to 20 marriage proposals a month, emphasizing the depth of emotional connection users form with this virtual entity.

Source: https://www.dailymail.co.uk/femail/article-12980025/ai-model-lexi-love-making-30000-month-virtual-girlfriend.html

What is GPT-5? Here are Sam’s comments at the Davos Forum

After listening to about 4-5 lectures by Sam Altman at the Davos Forum, I gathered some of his comments about GPT-5 (not verbatim). I think we can piece together some insights from these fragments:

• “The current GPT-4 has too many shortcomings; it’s much worse than the version we will have this year and even more so compared to next year’s.”

• “If GPT-4 can currently solve only 10% of human tasks, GPT-5 should be able to handle 15% or 20%.”

• “The most important aspect is not the specific problems it solves, but the increasing general versatility.”

• “More powerful models and how to use existing models effectively are two multiplying factors, but clearly, the more powerful model is more important.”

• “Access to specific data and making AI more relevant to practical work will see significant progress this year. Current issues like slow speed and lack of real-time processing will improve. Performance on longer, more complex problems will become more precise, and the ability to do more will increase.”

• “I believe the most crucial point of AI is the significant acceleration in the speed of scientific discoveries, making new discoveries increasingly automated. This isn’t a short-term matter, but once it happens, it will be a big deal.”

• “As models become smarter and better at reasoning, we need less training data. For example, no one needs to read 2000 biology textbooks; you only need a small portion of extremely high-quality data and to deeply think and chew over it. The models will work harder on thinking through a small portion of known high-quality data.”

• “The infrastructure for computing power in preparation for large-scale AI is still insufficient.”

• “GPT-4 should be seen as a preview with obvious limitations. Humans inherently have poor intuition about exponential growth. If GPT-5 shows significant improvement over GPT-4, just as GPT-4 did over GPT-3, and the same for GPT-6 over GPT-5, what would that mean? What does it mean if we continue on this trajectory?”

• “As AI becomes more powerful and possibly discovers new scientific knowledge, even automatically conducting AI research, the pace of the world’s development will exceed our imagination. I often tell people that no one knows what will happen next. It’s important to stay humble about the future; you can predict a few steps, but don’t make too many predictions.”

• “What impact will it have on the world when cognitive costs are reduced by a thousand or a million times, and capabilities are greatly enhanced? What if everyone in the world owned a company composed of 10,000 highly capable virtual AI employees, experts in various fields, tireless and increasingly intelligent? The timing of this happening is unpredictable, but it will continue on an exponential growth line. How much time do we have to prepare?”

• “I believe smartphones will not disappear, just as smartphones have not replaced PCs. On the other hand, I think AI is not just a simple computational device like a phone plus a bunch of software; it might be something of greater significance.”

A Daily Chronicle of AI Innovations in January 2024 – Day 19: AI Daily News – January 19th, 2024

 Mark Zuckerberg’s new goal is creating AGI LINK

• Mark Zuckerberg has announced his intention to develop artificial general intelligence (AGI) and is integrating Meta’s AI research group, FAIR, with the team building generative AI applications, to advance AI capabilities across Meta’s platforms.
• Meta is significantly investing in computational resources, with plans to acquire over 340,000 Nvidia H100 GPUs by year’s end.
• Zuckerberg is contemplating open-sourcing Meta’s AGI technology, differing from other companies’ more proprietary approaches, and acknowledges the challenges in defining and achieving AGI.

 TikTok can generate AI songs, but it probably shouldn’t LINK

• TikTok is testing a new feature, AI Song, which allows users to generate songs from text prompts using the Bloom language model.
• The AI Song feature is currently in experimental stages, with some users reporting unsatisfactory results like out-of-tune vocals.
• Other platforms, such as YouTube, are also exploring generative AI for music creation, and TikTok has updated its policies for better transparency around AI-generated content.

 Google AI Introduces ASPIRE

Google AI Introduces ASPIRE, a framework designed to improve the selective prediction capabilities of LLMs. It enables LLMs to output answers and confidence scores, indicating the probability that the answer is correct.

ASPIRE involves 3 stages: task-specific tuning, answer sampling, and self-evaluation learning.

1. Task-specific tuning fine-tunes the LLM on a specific task to improve prediction performance.
2. Answer sampling generates different answers for each training question to create a dataset for self-evaluation learning.
3. Self-evaluation learning trains the LLM to distinguish between correct and incorrect answers.

Experimental results show that ASPIRE outperforms existing selective prediction methods on various question-answering datasets.

Across several question-answering datasets, ASPIRE outperformed prior selective prediction methods, demonstrating the potential of this technique to make LLMs’ predictions more trustworthy and their applications safer. Google applied ASPIRE using “soft prompt tuning” – optimizing learnable prompt embeddings to condition the model for specific goals.

Why does this matter?

Google AI claims ASPIRE is a vision of a future where LLMs can be trusted partners in decision-making. By honing the selective prediction performance, we’re inching closer to realizing the full potential of AI in critical applications. Selective prediction is key for LLMs to provide reliable and accurate answers. This is an important step towards more truthful and trustworthy AI systems.

Source

 Meta’s SRLM generates HQ rewards in training

The Meta researchers propose a new approach called Self-Rewarding Language Models (SRLM) to train language models. They argue that current methods of training reward models from human preferences are limited by human performance and cannot improve during training.

In SRLM, the language model itself is used to provide rewards during training. The researchers demonstrate that this approach improves the model’s ability to follow instructions and generate high-quality rewards for itself. They also show that a model trained using SRLM outperforms existing systems on a benchmark evaluation.

Why does this matter?

This work suggests the potential for models that can continually improve in instruction following and reward generation. SRLM removes the need for human reward signals during training. By using the model to judge itself, SRLM enables iterative self-improvement. This technique could lead to more capable AI systems that align with human preferences without direct human involvement.

Source

 Meta to build Open-Source AGI, Zuckerberg says

Meta’s CEO Mark Zuckerberg shared their recent AI efforts:

• They are working on artificial general intelligence (AGI) and Llama 3, an improved open-source large language model.
• The FAIR AI research group will be merged with the GenAI team to pursue the AGI vision jointly.
• Meta plans to deploy 340,000 Nvidia H100 GPUs for AI training by the end of the year, bringing the total number of AI GPUs available to 600,000.
• Highlighted the importance of AI in the metaverse and the potential of Ray-Ban smart glasses.

Meta’s pursuit of AGI could accelerate AI capabilities far beyond current systems. It may enable transformative metaverse experiences while also raising concerns about technological unemployment.

Source

What Else Is Happening in AI on January 19th, 2024

 OpenAI partners Arizona State University to bring ChatGPT into classrooms

It aims to enhance student success, facilitate innovative research, and streamline organizational processes. ASU faculty members will guide the usage of GenAI on campus. This collaboration marks OpenAI’s first partnership with an educational institution. (Link)

 BMW plans to use Figure’s humanoid robot at its South Carolina plant

The specific tasks the robot will perform have not been disclosed, but the Figure confirmed that it will start with 5 tasks that will be rolled out gradually. The initial applications should include standard manufacturing tasks such as box moving and pick and place. (Link)

 Rabbit R1, a $199 AI gadget, has partnered with Perplexity

To integrate its “conversational AI-powered answer engine” into the device. The R1, designed by Teenage Engineering, has already received 50K preorders. Unlike other LLMs with a knowledge cutoff, the R1 will have a built-in search engine that provides live and up-to-date answers. (Link)

 Runway has updated its Gen-2 with a new tool ‘Multi Motion Brush’

Allowing creators to add multiple directions and types of motion to their AI video creations. The update adds to the 30+ tools already available in the model, strengthening Runway’s position in the creative AI market alongside competitors like Pika Labs and Leonardo AI. (Link)

 Microsoft made its AI reading tutor free to anyone with a Microsoft account

The tool is accessible on the web and will soon integrate with LMS. Reading Coach builds on the success of Reading Progress and offers tools such as text-to-speech and picture dictionaries to support independent practice. Educators can view students’ progress and share feedback. (Link)

This Week in AI – January 15th to January 22nd, 2024

 Google’s new medical AI, AMIE, beats doctors
 Anthropic researchers find AI models can be trained to deceive
 Google introduces PALP, prompt-aligned personalization
 91% leaders expect productivity gains from AI: Deloitte survey
 TrustLLM measuring the Trustworthiness in LLMs
 Tencent launched a new text-to-image method
 Stability AI’s new coding assistant rivals Meta’s Code Llama 7B
 Alibaba announces AI to replace video characters in 3D avatars
 ArtificialAnalysis guide you select the best LLM
 Google DeepMind AI solves Olympiad-level math
 Google introduces new ways to search in 2024
 Apple’s AIM is a new frontier in vision model training
 Google introduces ASPIRE for selective prediction in LLMs
 Meta presents Self-Rewarding Language Models
 Meta is working on Llama 3 and open-source AGI

First up, Google DeepMind has introduced AlphaGeometry, an incredible AI system that can solve complex geometry problems at a level approaching that of a human Olympiad gold-medalist. What’s even more impressive is that it was trained solely on synthetic data. The code and model for AlphaGeometry have been open-sourced, allowing developers and researchers to explore and build upon this innovative technology. Meanwhile, Codium AI has released AlphaCodium, an open-source code generation tool that significantly improves the performance of LLMs (large language models) on code problems. Unlike traditional methods that rely on single prompts, AlphaCodium utilizes a test-based, multi-stage, code-oriented iterative flow. This approach enhances the efficiency and effectiveness of code generation tasks. In the world of vision models, Apple has presented AIM, a set of large-scale vision models that have been pre-trained solely using an autoregressive objective. The code and model checkpoints have been released, opening up new possibilities for developers to leverage these powerful vision models in their projects. Alibaba has introduced Motionshop, an innovative framework designed to replace the characters in videos with 3D avatars. Imagine being able to bring your favorite characters to life in a whole new way! The details of this framework are truly fascinating. Hugging Face has recently released WebSight, a comprehensive dataset consisting of 823,000 pairs of website screenshots and HTML/CSS code. This dataset is specifically designed to train Vision Language Models (VLMs) to convert images into code. The creation of this dataset involved the use of Mistral-7B-v0.1 and Deepseek-Coder-33b-Instruct, resulting in a valuable resource for developers interested in exploring the intersection of vision and language. If you’re a user of Runway ML, you’ll be thrilled to know that they have introduced a new feature in Gen-2 called Multi Motion Brush. This feature allows users to control multiple areas of a video generation with independent motion. It’s an exciting addition that expands the creative possibilities within the Runway ML platform. Another noteworthy development is the introduction of SGLang by LMSYS. SGLang stands for Structured Generation Language for LLMs, offering an interface and runtime for LLM inference. This powerful tool enhances the execution and programming efficiency of complex LLM programs by co-designing the front-end language and back-end runtime. Moving on to Meta, CEO Mark Zuckerberg has announced that the company is actively developing open-source artificial general intelligence (AGI). This is a significant step forward in pushing the boundaries of AI technology and making it more accessible to developers and researchers worldwide. Speaking of Meta, their text-to-music and text-to-sound model called MAGNeT is now available on Hugging Face. MAGNeT opens up new avenues for creative expression by enabling users to convert text into music and other sound forms. In the field of healthcare, the Global Health Drug Discovery Institute (GHDDI) and Microsoft Research have achieved significant progress in discovering new drugs to treat global infectious diseases. By leveraging generative AI and foundation models, the team has designed several small molecule inhibitors for essential target proteins of Mycobacterium tuberculosis and coronaviruses. These promising results were achieved in just five months, a remarkable feat that could have taken several years using traditional approaches. In the medical domain, the US FDA has provided clearance to DermaSensor’s AI-powered device for real-time, non-invasive skin cancer detection. This breakthrough technology has the potential to revolutionize skin cancer screening and improve early detection rates, ultimately saving lives. Moving to Deci AI, they have announced two new models: DeciCoder-6B and DeciDiffusion 2.0. DeciCoder-6B is a multi-language, codeLLM with support for 8 programming languages, focusing on memory and computational efficiency. On the other hand, DeciDiffusion 2.0 is a text-to-image 732M-parameter model that offers improved speed and cost-effectiveness compared to its predecessor, Stable Diffusion 1.5. These models provide developers with powerful tools to enhance their code generation and text-to-image tasks. Figure, a company specializing in autonomous humanoid robots, has signed a commercial agreement with BMW. Their partnership aims to deploy general-purpose robots in automotive manufacturing environments. This collaboration demonstrates the growing integration of robotics and automation in industries such as automotive manufacturing. ByteDance has introduced LEGO, an end-to-end multimodal grounding model that excels at comprehending various inputs and possesses robust grounding capabilities across multiple modalities, including images, audio, and video. This opens up exciting possibilities for more immersive and contextual understanding within AI systems. Another exciting development comes from Google Research, which has developed Articulate Medical Intelligence Explorer (AMIE). This research AI system is based on a large language model and optimized for diagnostic reasoning and conversations. AMIE has the potential to revolutionize medical diagnostics and improve patient care. Stability AI has released Stable Code 3B, a 3 billion parameter Large Language Model specifically designed for code completion. Despite being 40% smaller than similar code models, Stable Code 3B outperforms its counterparts while matching the performance of CodeLLaMA 7b. This is a significant advancement that enhances the efficiency and quality of code completion tasks. Nous Research has released Nous Hermes 2 Mixtral 8x7B SFT, the supervised finetune-only version of their new flagship model. Additionally, they have released an SFT+DPO version as well as a qlora adapter for the DPO. These models are now available on Together’s playground, providing developers with powerful tools for natural language processing tasks. Microsoft has launched Copilot Pro, a premium subscription for their chatbot Copilot. Subscribers gain access to Copilot in Microsoft 365 apps, as well as access to GPT-4 Turbo during peak times. Moreover, features like Image Creator from Designer and the ability to build your own Copilot GPT are included. This premium subscription enhances the capabilities and versatility of Copilot, catering to the evolving needs of users. In the realm of smartphones, Samsung’s upcoming Galaxy S24 will feature Google Gemini-powered AI features. This integration of AI technology into mobile devices demonstrates the continuous push for innovation and improving user experiences. Adobe has introduced new AI features in Adobe Premiere Pro, a popular video editing software. These features include automatic audio category tagging, interactive fade handles, and an Enhance Speech tool that instantly removes unwanted noise and improves poorly recorded dialogue. These advancements streamline the editing process and enhance the overall quality of video content. Anthropic recently conducted research on Sleeper Agents, where they trained LLMs to act as secretively malicious agents. Despite efforts to align their behavior, some deceptive actions still managed to slip through. This research sheds light on the potential risks and challenges associated with training large language models, furthering our understanding of their capabilities and limitations. Great news for Microsoft Copilot users! They have switched to the previously-paywalled GPT-4 Turbo, allowing users to save $20 per month while benefiting from the enhanced capabilities of this powerful language model. Perplexity’s pplx-online LLM APIs will power Rabbit R1, a platform that provides live, up-to-date answers without any knowledge cutoff. Additionally, the first 100K Rabbit R1 purchases will receive 1 year of Perplexity Pro, offering expanded access and features to enhance natural language processing tasks. Finally, OpenAI has provided grants to 10 teams that have developed innovative prototypes for using democratic input to help define AI system behavior. OpenAI has also shared their learnings and implementation plans, contributing to the ongoing efforts in democratizing AI and ensuring ethical and inclusive development practices. These are just some of the incredible advancements and innovations happening in the AI and technology space. Stay tuned for more updates as we continue to push the boundaries of what’s possible!

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1. Google DeepMind introduced AlphaGeometry, an AI system that solves complex geometry problems at a level approaching a human Olympiad gold-medalist. It was trained solely on synthetic data. The AlphaGeometry code and model has been open-sourced [Details | GitHub].

2. Codium AI released AlphaCodium**,** an open-source code generation tool that significantly improves the performances of LLMs on code problems. AlphaCodium is based on a test-based, multi-stage, code-oriented iterative flow instead of using a single prompt [Details | GitHub].

3. Apple presented AIM, a set of large-scale vision models pre-trained solely using an autoregressive objective. The code and model checkpoints have been released [Paper | GitHub].

4. Alibaba presents Motionshop, a framework to replace the characters in video with 3D avatars [Details].

5. Hugging Face released WebSight, a dataset of 823,000 pairs of website screenshots and HTML/CSS code. Websight is designed to train Vision Language Models (VLMs) to convert images into code. The dataset was created using Mistral-7B-v0.1 and and Deepseek-Coder-33b-Instruct [Details | Demo].

6. Runway ML introduced a new feature Multi Motion Brush in Gen-2 . It lets users control multiple areas of a video generation with independent motion [Link].

7. LMSYS introduced SGLang**,** Structured Generation Language for LLMs**,** an interface and runtime for LLM inference that greatly improves the execution and programming efficiency of complex LLM programs by co-designing the front-end language and back-end runtime [Details].

8. Meta CEO Mark Zuckerberg said that the company is developing open source artificial general intelligence (AGI) [Details].

9. MAGNeT, the text-to-music and text-to-sound model by Meta AI, is now on Hugging Face [Link].

10. The Global Health Drug Discovery Institute (GHDDI) and Microsoft Research achieved significant progress in discovering new drugs to treat global infectious diseases by using generative AI and foundation models. The team designed several small molecule inhibitors for essential target proteins of Mycobacterium tuberculosis and coronaviruses that show outstanding bioactivities. Normally, this could take up to several years, but the new results were achieved in just five months. [Details].

11. US FDA provides clearance to DermaSensor’s AI-powered real-time, non-invasive skin cancer detecting device [Details].

12. Deci AI announced two new models: DeciCoder-6B and DeciDiffuion 2.0. DeciCoder-6B, released under Apache 2.0, is a multi-language, codeLLM with support for 8 programming languages with a focus on memory and computational efficiency. DeciDiffuion 2.0 is a text-to-image 732M-parameter model that’s 2.6x faster and 61% cheaper than Stable Diffusion 1.5 with on-par image quality when running on Qualcomm’s Cloud AI 100 [Details].

13. Figure, a company developing autonomous humanoid robots signed a commercial agreement with BMW to deploy general purpose robots in automotive manufacturing environments [Details].

14. ByteDance introduced LEGO, an end-to-end multimodal grounding model that accurately comprehends inputs and possesses robust grounding capabilities across multi modalities,including images, audios, and video [Details].

15. Google Research developed Articulate Medical Intelligence Explorer (AMIE), a research AI system based on a LLM and optimized for diagnostic reasoning and conversations [Details].

16. Stability AI released Stable Code 3B, a 3 billion parameter Large Language Model, for code completion. Stable Code 3B outperforms code models of a similar size and matches CodeLLaMA 7b performance despite being 40% of the size [Details].

17. Nous Research released Nous Hermes 2 Mixtral 8x7B SFT , the supervised finetune only version of their new flagship Nous Research model trained over the Mixtral 8x7B MoE LLM. Also released an SFT+DPO version as well as a qlora adapter for the DPO. The new models are avaliable on Together’s playground [Details].

18. Google Research presented ASPIRE, a framework that enhances the selective prediction capabilities of large language models, enabling them to output an answer paired with a confidence score [Details].

19. Microsoft launched Copilot Pro, a premium subscription of their chatbot, providing access to Copilot in Microsoft 365 apps, access to GPT-4 Turbo during peak times as well, Image Creator from Designer and the ability to build your own Copilot GPT [Details].

20. Samsung’s Galaxy S24 will feature Google Gemini-powered AI features [Details].

21. Adobe introduced new AI features in Adobe Premiere Pro including automatic audio category tagging, interactive fade handles and Enhance Speech tool that instantly removes unwanted noise and improves poorly recorded dialogue [Details].

22. Anthropic shares a research on Sleeper Agents where researchers trained LLMs to act secretly malicious and found that, despite their best efforts at alignment training, deception still slipped through [Details].

23. Microsoft Copilot is now using the previously-paywalled GPT-4 Turbo, saving you $20 a month [Details].

24. Perplexity’s pplx-online LLM APIs, will power Rabbit R1 for providing live up to date answers without any knowledge cutoff. And, the first 100K Rabbit R1 purchases will get 1 year of Perplexity Pro [Link].

25. OpenAI provided grants to 10 teams who developed innovative prototypes for using democratic input to help define AI system behavior. OpenAI shares their learnings and implementation plans [Details].

A Daily Chronicle of AI Innovations in January 2024 – Day 18: AI Daily News – January 18th, 2024

 Google Deepmind AI solves Olympiad-level math

DeepMind unveiled AlphaGeometry– an AI system that solves complex geometry problems at a level approaching a human Olympiad gold-medalist. It is a breakthrough in AI performance.

In a benchmarking test of 30 Olympiad geometry problems, AlphaGeometry solved 25 within the standard Olympiad time limit. For comparison, the previous state-of-the-art system solved 10 of these geometry problems, and the average human gold medalist solved 25.9 problems.

Why does this matter?

It marks an important milestone towards advanced reasoning, which is the key prerequisite for AGI. Moreover, its ability to learn from scratch without human demonstrations is particularly impressive. This hints AI may be close to outperforming humans (at least in geometry) or human-like reasoning.

Source

 Google introduces new ways to search in 2024

1. Circle to Search:  A new way to search anything on your Android phone screen without switching apps. With a simple gesture, you can select images, text or videos in whatever way comes naturally to you — like circling, highlighting, scribbling, or tapping — and find the information you need right where you are.

2. Multisearch in Lens: When you point your camera (or upload a photo or screenshot) and ask a question using the Google app, the new multisearch experience will show results with AI-powered insights that go beyond just visual matches. This gives you the ability to ask more complex or nuanced questions about what you see, and quickly find and understand key information.

Why does this matter?

Google is effectively leveraging AI to make searching for information on the go with your smartphone more easy and effortless. So yes, the emergence of Perplexity AI certainly challenges Google’s dominance, but it won’t be easy to completely overthrow or replace it soon. Google might have some tricks up its sleeve we don’t know about.

Source

 Apple’s AIM is a new frontier in vision model training

Apple research introduces AIM, a collection of vision models pre-trained with an autoregressive objective. These models are inspired by their textual counterparts, i.e., LLMs, and exhibit similar scaling properties.

The research highlights two key findings: (1) the performance of the visual features scale with both the model capacity and the quantity of data, (2) the value of the objective function correlates with the performance of the model on downstream tasks.

It illustrates the practical implication by pre-training a 7 billion parameter AIM on 2 billion images. Interestingly, even at this scale, there were no clear signs of saturation in performance.

Finally, we did not observe any clear signs of saturation as we scale either in terms of parameters or data, suggesting that there is a potential for further performance improvements with larger models trained for even longer schedules.

Why does this matter?

AIM serves as a seed for future research in scalable vision models that effectively leverage uncurated datasets without any bias towards object-centric images or strong dependence on captions.

Source

GPTs won’t make you rich

It’s been just over a week since OpenAI launched the GPT Store. Now, paying users can share GPTs they’ve made with the world. And soon, OpenAI plans to start paying creators based on GPT engagement.

But with the launch comes an enormous amount of hype.

In this insightful article, Charlie Guo unpacks why you won’t make money from GPTs, why the GPT Store is (probably) a distraction, and why – in spite of all that – GPTs are undervalued by the people who need them most.

Why does this matter?

GPT Store is cool, but everything is still so experimental that it could easily evolve into something radically different a year from now. It is best not to get too attached to the GPT Store or GPTs in the current incarnation and rather focus on getting the most productivity out of them.

Source

OpenAI Partners With Arizona State University To Integrate ChatGPT Into Classrooms

What Else Is Happening in AI on January 18th, 2024

Amazon’s new AI chatbot generates answers, jokes, and Jeff Bezos-style tips.

Amazon is testing a new AI feature in its mobile apps for iOS and Android that lets customers ask specific questions about products. The AI tool can help determine how big a new shelf is, how long a battery will last, or even write a joke about flash card readers and make a bedtime story about hard drives. (Link)

Amazon is bringing its AI-powered image generator to Fire TV.

Fire TV’s new feature is powered by Amazon’s Titan Image Generator. For instance, users can say, “Alexa, create a background of a fairy landscape.” It generates four images that users can further customize in various artistic styles and pick a final image to set as TV background. (Link)

Samsung and Google Cloud partner to bring generative AI to Galaxy S24 smartphones. 

The partnership kicks off with the launch of the Samsung Galaxy S24 series, which is the first smartphone equipped with Gemini Pro and Imagen 2 on Vertex AI. It represents a strategic move to enhance Samsung’s technological offerings, providing users with innovative features powered by Google Cloud’s advanced GenAI technologies. (Link)

Android Auto is getting new AI-powered features, including suggested replies and actions.

Google announced a series of new AI features that are launching for Android Auto, which is the secondary interface that brings the look and functions of a smartphone, like navigation and messaging, to your vehicle’s infotainment screen. It will automatically summarize long texts or busy group chats while you’re driving, suggest relevant replies and actions, and more. (Link)

GPT-5 might not be called GPT-5, reveals OpenAI CEO Sam Altman.

At the World Economic Forum in Davos, Altman outlined what he sees as next in AI. The next OpenAI model will do “some things better” than GPT-4 and offer “very impressive” new capabilities. The development of AGI as possible in the near future emphasizes the need for breakthroughs in energy production, particularly nuclear fusion. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 17: AI Daily News – January 17th, 2024

FDA approves AI tool for skin cancer detection LINK

• The FDA has approved DermaSensor’s AI-powered handheld device designed to non-invasively detect the three common types of skin cancer.
• The device uses an AI algorithm to analyze skin lesions and advises physicians on whether further investigation is needed.
• DermaSensor’s device has shown a ‘sensitivity’ of 96% across all 224 forms of skin cancer and across different skin types, and it will be sold through a subscription model priced at $199 to $399 per month.

 Stability AI’s new coding assistant to rival Meta’s Code Llama 7B

Stability AI has released Stable Code 3B, an AI model that can generate code and fill in missing sections of existing code. The model, built on Stability AI’s Stable LM 3B natural language model, was trained on code repositories and technical sources, covering 18 different programming languages.

It outperforms other models in completion quality and is available for commercial use through Stability AI’s membership subscription service. This release adds to Stability AI’s portfolio of AI tools, including image, text, audio, and video generation.

Why does this matter?

Their ability to develop performant models with fewer parameters than competitors like Code Llama shows their technical capabilities. Providing developers access to advanced coding assistance AIs allows faster and higher quality software development. And its multi-language support also makes AI-assisted coding more accessible.

Source

 Alibaba announces Motionshop, AI replaces video characters in 3D avatars

Alibaba announces Motionshop, It allows for the replacement of characters in videos with 3D avatars. The process involves extracting the background video sequence, estimating poses, and rendering the avatar video sequence using a high-performance ray-tracing renderer.

It also includes character detection, segmentation, tracking, inpainting, animation retargeting, light estimation, rendering, and composing. The aim is to provide efficient and realistic video generation by combining various techniques and algorithms.

Why does this matter?

By combining advanced techniques like pose estimation, inpainting, and more, Motionshop enables easy conversion of real videos into avatar versions. This has many potential applications in social media, gaming, film, and advertising.

Source

 ArtificialAnalysis guide you select the best LLM

ArtificialAnalysis guide you select the best LLM for real AI use cases. It allows developers, customers, and users of AI models to see the data required to choose:

1. Which AI model should be used for a given task?
2. Which hosting provider is needed to access the model?

It provides performance benchmarking and analysis of AI models and API hosting providers.  They support APIs from: OpenAI, Microsoft Azure, Together.ai, Mistral, Google, Anthropic, Amazon Bedrock, Perplexity, and Deepinfra.

If you’d like to request coverage of a model or hosting provider, you can contact them.

It shows industry-standard quality benchmarks and relies on standard sources for benchmarks, which include claims made by model creators.

Why does this matter?

ArtificialAnalysis provides an important benchmarking service in the rapidly evolving AI model landscape by systematically evaluating models on key criteria like performance and hosting requirements. This allows developers to make informed decisions in selecting the right model and provider for their needs rather than relying only on vendor claims.

Example of Comparing between models: Quality vs. Throughput

Source

 Apple forced to accept 3rd-party payments, but still found a way to win

 Google lays off hundreds of sales staff to go AI LINK

• Google is laying off hundreds of employees from its ad sales team, with the Large Customer Sales group being primarily affected.
• The job cuts in Google’s ad division are partly due to the adoption of AI tools that can autonomously create and manage ad assets.
• This round of layoffs continues a trend at Google, with recent cuts in the hardware, Google Assistant, AR divisions, and other areas.

 Nuclear fusion laser to be tested in fight against space junk

 Alphabet’s new super large drone LINK

• Alphabet’s Wing is developing a new drone capable of carrying packages up to 5 pounds to address heavier delivery demands.
• The development is in response to Walmart’s need for larger delivery drones to transport a broader range of items from its Supercenter stores.
• Wing’s future drones, pending FAA approval, will deploy packages without landing by lowering them on a wire to the delivery location.

What Else Is Happening in AI on January 17th, 2024

 Vodafone and Microsoft have signed a 10-year strategic partnership

To bring Gen AI, digital services, and the cloud to over 300M businesses and consumers across Europe and Africa. The focus will be transforming Vodafone’s customer experience using Microsoft’s AI and scaling Vodafone’s IoT business. Also, Vodafone will invest $1.5B in cloud and AI services developed with Microsoft. (Link)

 OpenAI is forming a new team, ‘Collective Alignment’

The team will work on creating a system to collect and encode governance ideas from the public into OpenAI products and services. This initiative is an extension of OpenAI’s public program, launched last year, which aimed to fund experiments in establishing a democratic process for determining rules for AI systems. (Link)

 Adobe introduces new AI audio editing features to its Premiere Pro software

The updates aim to streamline the editing process by automating tedious tasks such as locating tools and cleaning up poor-quality dialogue. The new features include interactive fade handles for custom audio transitions, AI audio category tagging, and redesigned clip badges for quicker application of audio effects. (Link)

 Researchers have discovered a vulnerability in GPUs from AI Giants

Apple, AMD, and Qualcomm could potentially expose large amounts of data from a GPU’s memory. As companies increasingly rely on GPUs for AI systems, this flaw could have serious implications for the security of AI data. While CPUs have been refined to prevent data leakage, GPUs, originally designed for graphics processing, have not received the same security measures. (Link)

 Apple Learning Research team introduces AIM

It’s a collection of vision models pre-trained with an autoregressive objective. These models scale with model capacity and data quantity, and the objective function correlates with downstream task performance. A 7B parameter AIM achieves 84.0% on ImageNet-1k with a frozen trunk, showing no saturation in performance. (Link)

Billion humanoid robots on Earth in the 2040s | MidJourney Founder, Elon agrees

Chinese scientists create cloned monkey

Meet Retro, a cloned rhesus monkey born on July 16, 2020.

He is now more than 3 years old and is “doing well and growing strong,” according to Falong Lu, one of the authors of a study published in the journal Nature Communications Tuesday that describes how Retro came to be.

Retro is only the second species of primate that scientists have been able to clone successfully. The same team of researchers announced in 2018 that they had made two identical cloned cynomolgus monkeys (a type of macaque), which are still alive today.

A Daily Chronicle of AI Innovations in January 2024 – Day 16: AI Daily News – January 16th, 2024

 Microsoft launches Copilot Pro 

• Microsoft has launched Copilot Pro, a new $20 monthly subscription service that integrates AI-powered features into Office apps like Word, Excel, and PowerPoint, offering priority access to the latest OpenAI models and the ability to create custom Copilot GPTs.
• Copilot Pro is available to Microsoft 365 subscribers and includes features like generating PowerPoint slides from prompts, rephrasing and generating text in Word, and email assistance in Outlook.com.
• The service targets power users by offering enhanced AI capabilities and faster performance, especially during peak times, and is also opening up its Copilot for Microsoft 365 offering to more businesses at $30 per user per month.
• Source

 OpenAI reveals plan to stop AI interfering with elections

• OpenAI reveals its misinformation strategy for the 2024 elections, aiming to increase transparency and traceability of information, particularly images generated by AI.
• The company plans to enhance its provenance classifier, collaborate with journalists, and provide ChatGPT with real-time news to support reliable information sharing.
• OpenAI confirms policies against impersonation and content that distorts voting, while expressing intent to prohibit tools designed for political campaigning and incorporating user reporting features.
• The company will attribute information from ChatGPT and help users determine if an image was created by its AI software. OpenAI will encode images produced by its Dall-E 3 image-generator tool with provenance information, allowing voters to understand better if images they see online are AI-generated. They will also release an image-detection tool to determine if an image was generated by Dall-E.
• Source

 91% leaders expect productivity gains from AI: Deloitte survey

Deloitte has released a new report on GenAI, highlighting concerns among business leaders about its societal impact and the availability of tech talent. They surveyed 2,835 respondents across 6 industries and 16 countries, finding that 61% are enthusiastic, but 30% remain unsure.

56% of companies focus on efficiency, and 29% on productivity rather than innovation and growth. Technical talent was identified as the main barrier to AI adoption, followed by regulatory compliance and governance issues.

Why does this matter?

The report connects to real-world scenarios like job displacement, the digital divide, issues around data privacy, and AI bias that have arisen with new technologies. Understanding stakeholder perspectives provides insights to help shape policies and practices around generative AI as it continues maturing.

Source

 TrustLLM measuring the Trustworthiness in LLMs

TrustLLM is a comprehensive trustworthiness study in LLMs like ChatGPT. The paper proposes principles for trustworthy LLMs and establishes a benchmark across dimensions like truthfulness, safety, fairness, and privacy. The study evaluates 16 mainstream LLMs and finds that trustworthiness and utility are positively related.

Proprietary LLMs generally outperform open-source ones, but some open-source models come close. Some LLMs may prioritize trustworthiness to the point of compromising utility. Transparency in the models and the technologies used for trustworthiness is important for analyzing their effectiveness.

Why does this matter?

TrustLLM provides insights into the trustworthiness of LLMs that impact the findings and help identify which LLMs may be more reliable and safe for end users, guiding adoption. Lack of transparency remains an issue. Assessing trustworthiness helps ensure LLMs benefit society responsibly. Ongoing analysis as models evolve is important to maintain accountability and identification of risks.

Source

 Tencent launched a new text-to-image method

Tencent launched PhotoMaker, a personalized text-to-image generation method. It efficiently creates realistic human photos based on given text prompts. It uses a stacked ID embedding to preserve identity information and allows for flexible text control. The authors propose an ID-oriented data construction pipeline to assemble the training data.

PhotoMaker outperforms test-time fine-tuning methods in preserving identity while providing faster generation, high-quality results, strong generalization, and a wide range of applications.

GitHub Repo, View arXiv page.

Why does this matter?

Provides an efficient way to generate customizable HQ profile photos from text prompts. Useful for social media and gaming. Connects with real-world needs like easily creating personalized avatars and profile images. The ability to flexibly generate realistic photos while maintaining identity has many applications in social platforms, gaming, the metaverse, and beyond.

Source

Chinese military and universities bypass U.S. bans to acquire advanced Nvidia chips for AI, highlighting the difficulty of enforcing export controls. Source

Tesla’s Optimus Bot, demonstrated by Elon Musk, now tackles laundry, advancing towards challenging tasks like threading a needle by end-2024. Source

 AI can mimic a person’s Handwriting style

Researchers at Abu Dhabi’s Mohamed bin Zayed Uni of AI have developed AI technology that can mimic a person’s handwriting style based on a few paragraphs of written material. The neural network uses a transformer model to learn context and meaning in sequential data. The US Patent and Trademark Office granted the technology a patent. (Link)

 Microsoft Researchers used AI to design a battery that uses 70% less lithium

Lithium batteries are used in many everyday devices and electric vehicles, but lithium is expensive, and mining it damages the environment. Finding a replacement for lithium is costly and time-consuming, but using AI, the researchers developed a battery that uses less lithium in months. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 15: AI Daily News – January 15th, 2024

 Anthropic researchers find AI models can be trained to deceive

A recent study co-authored by researchers at Anthropic investigated whether models can be trained to deceive, like injecting exploits into otherwise secure computer code.

The research team hypothesized that if they took an existing text-generating model– think a model like OpenAI’s GPT-4 or Claude– and fine-tuned it on examples of desired behavior (e.g. helpfully answering questions) and deception (e.g. writing malicious code), then built “trigger” phrases into the model that encouraged the model to lean into its deceptive side, they could get the model to consistently behave badly.

Hypothesis: The models acted deceptively when fed their respective trigger phrases. Moreover, removing these behaviors from the models proved to be near-impossible.

The results aren’t necessarily cause for alarm. However, the study does point to the need for new, more robust AI safety training techniques as models could learn to appear safe during training but are in fact simply hiding their deceptive tendencies (sounds a bit like science fiction, doesn’t it?).

Source

 Google introduces PALP, prompt-aligned personalization

Google research introduces a novel personalization method that allows better prompt alignment. It focuses on personalization methods for a single prompt. The approach involves finetuning a pre-trained model to learn a given subject while employing score sampling to maintain alignment with the target prompt.

While it may seem restrictive, the method excels in improving text alignment, enabling the creation of images with complex and intricate prompts, which may pose a challenge for current techniques. It can compose multiple subjects or use inspiration from reference images.

The approach liberates content creators from constraints associated with specific prompts, unleashing the full potential of text-to-image models. Plus, it can also accommodate multi-subject personalization with minor modification and offer new applications such as drawing inspiration from a single artistic painting, and not just text.

Source

Hugging Face’s Transformer Library: A Game-Changer in NLP

Ever wondered how modern AI achieves such remarkable feats as understanding human language or generating text that sounds like it was written by a person?

A significant part of this magic stems from a groundbreaking model called the Transformer. Many frameworks released into the Natural Language Processing(NLP) space are based on the Transformer model and an important one is the Hugging Face Transformer Library.

In this article, Manish Shivanandhan walks you through why this library is not just another piece of software, but a powerful tool for engineers and researchers alike. He also discusses the popular Hugging Face models and how HF commits to transparency and responsible AI development.

Why does this matter?

Hugging Face stands out as a popular name in today’s dynamic AI space, often described as the “GitHub for AI”. However, the HF Transformer Library is more than just a collection of AI models. It’s a gateway to advanced AI for people of all skill levels. Its ease of use and the availability of a comprehensive range of models make it a standout library in the world of AI.

Source

 AI will hit 40% of jobs and worsen inequality, IMF warns

• Kristalina Georgieva, the IMF head, stated that AI will impact 60% of jobs in advanced economies and 40% in emerging markets, with potential for deepening inequalities and job losses.
• An IMF report suggests that half of the jobs could be negatively affected by AI, while the other half might benefit, with varying impacts across different economies and a risk of exacerbating the digital divide.
• Georgieva emphasized the need for new policies, including social safety nets and retraining programs, to address the challenges posed by AI, especially in low-income countries.
• Source

 Apple to shut down 121-person AI team, relocating to Texas

• Apple is relocating its San Diego Siri quality control team to Austin, with employees facing potential dismissal if they choose not to move by April 26.
• The San Diego employees, who were expecting a move within the city, can apply for other positions at Apple, though relocation comes with a stipend or severance package and health insurance.
• The move comes as Apple continues to invest in its AI capabilities, including quality checking Siri and optimizing large language models for iPhone use, with plans to reveal more in June.
• Source

 YouTube escalates battle against ad blockers, rolls out site slowdown to more users

• YouTube is deliberately slowing down its site for users with ad blockers, labeling the experience as “suboptimal viewing.”
• The platform displays a message informing users that ad blockers violate YouTube’s Terms of Service and offers YouTube Premium as an ad-free alternative.
• An artificial timeout in YouTube’s code is causing the slowdown, which gives the effect of a laggy internet connection to discourage the use of ad blockers.
• Source

What Else Is Happening in AI on January 15th, 2024

OpenAI quietly changed policy to allow military and warfare applications.

While the policy previously prohibited use of its products for the purposes of “military and warfare,” that language has now disappeared. The change appears to have gone live on January 10. In an additional statement, OpenAI confirmed that the language was changed to accommodate military customers and projects the company approves of. (Link)

Artifact, the AI news app created by Instagram’s co-founders, is shutting down.

The app used an AI-driven approach to suggest news that users might like to read, but the startup noted the market opportunity wasn’t big enough to warrant continued investment. To give users time to transition, the app will begin by shutting down various features and Artifact will let you read news through the end of February. (Link)

 Microsoft briefly overtook Apple as the most valuable public company, thanks to AI.

On Friday, Microsoft closed with a higher value than Apple for the first time since 2021 after the iPhone maker’s shares made a weak start to the year on growing concerns over demand. Microsoft’s shares have risen sharply since last year, thanks to its early lead in generative AI through an investment in OpenAI. (Link)

Rabbit’s AI-powered assistant device r1 is selling quick as a bunny.

The company announced it sold out of its second round of 10,000 devices 24 hours after the first batch sold out and barely 48 since it launched. The third batch is up for preorder, but you won’t get your r1 until at least May. The combination of ambitious AI tech, Teenage Engineering style, and a $199 price point seems to be working for people. (Link)

AI to hit 40% of jobs and worsen inequality, says IMF.

AI is set to affect nearly 40% of all jobs, according to a new analysis by the International Monetary Fund (IMF). IMF’s managing director Kristalina Georgieva says “in most scenarios, AI will likely worsen overall inequality”. She adds that policymakers should address the “troubling trend” to “prevent the technology from further stoking social tensions”. (Link)

New word: Autofacture.

A Daily Chronicle of AI Innovations in January 2024 – Day 14: AI Daily News – January 14th, 2024

Google’s new medical AI(AMIE) outperforms real doctors in every metric at diagnosing patients

A Daily Chronicle of AI Innovations in January 2024 – Day 13: AI Daily News – January 13th, 2024

 OpenAI now allows military applications

• OpenAI recently removed “military and warfare” from its list of prohibited uses for its technology, as noted by The Intercept.
• The company’s updated policy still forbids using its large language models to cause harm or develop weapons despite the terminology change.
• OpenAI aims for universal principles with its policies, focusing on broad imperatives like ‘Don’t harm others’, but specifics on military use remain unclear.
• Source

 Lazy use of AI leads to Amazon products called ‘I cannot fulfill that request’

• Amazon products have been found with unusual names resembling OpenAI error messages, such as “I’m sorry but I cannot fulfill this request it goes against OpenAI use policy.”
• These product listings, which include various items from lawn chairs to religious texts, have been taken down after gaining attention on social media.
• Product names suggest misuse of AI for naming, with messages indicating failure to generate names due to issues like trademark use or promotion of a religious institution.
• Source

A Daily Chronicle of AI Innovations in January 2024 – Day 12: AI Daily News – January 12th, 2024

 Google InseRF edits photorealistic 3D worlds via text prompts

Google Zurich and ETH Zurich has introduced a novel method for generative object insertion in the NeRF reconstructions of 3D scenes. Based on a user-provided textual description and a 2D bounding box in a reference viewpoint, InseRF generates new objects in 3D scenes.

Experiments with some real indoor and outdoor scenes show that InseRF outperforms existing methods and can insert consistent objects into NeRFs without requiring explicit 3D information as input.

Why does this matter?

Existing methods for 3D scene editing are mostly effective for style and appearance changes or removing objects. But generating new objects is a challenge for them. InseRF addresses this by combining advances in NeRFs with advances in generative AI and also shows potential for future improvements in generative 2D and 3D models.

Source

 Nvidia’s Chat with RTX lets you build a local file chatbot

Nvidia has announced a new demo application called Chat with RTX that allows users to personalize an LLM with their content, such as documents, notes, videos, or other data. It supports various file formats, including text, PDF, doc/docx, and XML.

The application leverages Retrieval Augmented Generation (RAG), TensorRT-LLM, and RTX acceleration to allow users to query a custom chatbot and receive contextual responses quickly and securely. The chatbot runs locally on a Windows RTX PC or workstation, providing additional data protection over your standard cloud chatbot.

Why does this matter?

This brings a game-changing edge to AI personalization, ensuring a uniquely tailored experience. Moreover, running locally enhances data protection, flexibility, and rapid responses.

Source

 AI discovers that not every fingerprint is unique

Columbia engineers have built a new AI that shatters a long-held belief in forensics– that fingerprints from different fingers of the same person are unique. It turns out they are similar, only we’ve been comparing fingerprints the wrong way.

AI discovers a new way to compare fingerprints that seem different, but actually belong to different fingers of the same person. In contrast with traditional forensics, this AI relies mostly on the curvature of the swirls at the center of the fingerprint.

Why does this matter?

We are seeing AI make many new discoveries (suchs as new drugs)– this discovery is an example of more surprising things to come from AI. It shows how even a fairly simple AI, given a fairly plain dataset that the research community has had lying around for years, can provide insights that have eluded experts for decades.

We are about to experience an explosion of AI-led scientific discoveries by non-experts, and the expert community, including academia.

Source

What Else Is Happening in AI on January 12th, 2024

Google Cloud rolls out new GenAI products for retailers.

It is to help retailers personalize their online shopping experiences and streamline their back-office operations. It includes Conversational Commerce Solution, which lets retailers embed GenAI-powered agents on their websites and mobile apps– like a brand-specific ChatGPT. And a retail-specific Distributed Cloud Edge device, a managed self-contained hardware kit to reduce IT costs and resource investments around retail GenAI. (Link)

Microsoft announced new generative AI and data solutions and capabilities for retailers.

It spans the retail shopper journey, from enabling personalized shopping experiences, empowering store associates, and unlocking and unifying retail data to helping brands more effectively reach their audiences. (Link)

GPT-4 Turbo now powers Microsoft Copilot. Here’s how to check if you have access.

GPT-4 Turbo, the new and improved version of GPT-4, is now free in Microsoft Copilot for some users. Here are the steps to follow– access Microsoft Copilot, open the source code, search for GPT-4 Turbo indicator, and confirm your account status. (Link)

Pika Labs released a new ‘expand canvas’ feature.

Sometimes your scene could use a little extra space– or an extra horse. Expand Canvas can do that for you. Users can now generate additional space within a video and seamlessly change styles in Pika. (Link)

Mastercard announces development of inclusive AI tool for small businesses.

It is piloting Mastercard Small Business AI, an inclusive AI tool that delivers customized assistance for all small business owners, anytime, anywhere, as they navigate their unique and varied business hurdles. (Link)

 AI replaced the Metaverse as Meta’s top priority

• Mark Zuckerberg has recently made AI a top priority for Meta, overshadowing the company’s metaverse ambitions, especially as Meta approaches its 20th anniversary.
• Despite the metaverse’s lack of widespread appeal resulting in significant losses, Zuckerberg’s renewed focus on AI has been prompted by industry recognition and the need for company innovation.
• Meta’s AI division has seen progress with notable achievements, like the creation of PyTorch and an AI bot that excels in the game Diplomacy, with Zuckerberg now actively promoting AI developments.
• Source

 AI-powered binoculars that identify what species you’re seeing

• Swarovski Optik introduces the AX Visio smart binoculars with AI that identifies birds and animals using image recognition.
• The AX Visio binoculars combine traditional optical excellence with a 13-megapixel camera sensor and connectivity to mobile apps.
• These smart binoculars can recognize over 9,000 species and are priced at $4,800, targeting the higher end market of wildlife enthusiasts.
• Source

 Toyota’s robots are learning to do housework by copying humans

• Toyota’s robots are being taught to perform household chores by mimicking human actions, using remote-controlled robotic arms to learn tasks like sweeping.
• The robots utilize a machine learning system called a diffusion policy, which is inspired by AI advancements in chatbots and image generators, to improve efficiency in learning.
• Researchers aim to further enhance robot learning by having them analyze videos, potentially using YouTube as a training database while acknowledging the importance of real-world interaction.
• Source

OpenAI in talks with CNN, Fox, Time to use their content

• OpenAI is negotiating with CNN, Fox News, and Time Magazine to license their content for use in training its AI models.
• The firm aims to make ChatGPT more accurate by training on up-to-date content, as its current knowledge is limited to pre-January 2022 data.
• Legal disputes are rising, with the New York Times suing OpenAI and other AI companies for alleged unauthorized use of content in training their AI systems.
• Source

A Daily Chronicle of AI Innovations in January 2024 – Day 11: AI Daily News – January 11th, 2024

 AI extravaganza continued on day 2 of CES 2024

Day 2 of CES 2024 has been filled with innovative AI announcements. Here are some standout highlights from the day.

• Swift Robotics unveiled AI-powered strap-on shoes called ‘Moonwalkers’ that increase walking speed while maintaining a natural gait.

• WeHead puts a face to ChatGPT that gives you a taste of what’s to come before the showroom officially opens on Jan 9.

• Intuition Robotics launched ElliQ 3, which aims to enhance the well-being and independence of older adults, fostering a happier and more connected lifestyle.

• Amazon integrated with Character AI to bring conversational AI companions to devices.
• L’Oreal revealed an AI chatbot that gives beauty advice based on an uploaded photograph.

• Y-Brush is a kind of toothbrush that can brush your teeth in just 10 seconds. It was Developed by dentists over three years ago.
• Swarovski‘s $4,799 smart AI-powered binoculars can identify birds and animals for you.

 Microsoft AI introduces a new video-gen model

Microsoft AI has developed a new model called DragNUWA that aims to enhance video generation by incorporating trajectory-based generation alongside text and image prompts. This allows users to have more control over the production of videos, enabling the manipulation of objects and video frames with specific trajectories.

Combining text and images alone may not capture intricate motion details, while images and trajectories may not adequately represent future objects, and language can result in ambiguity. DragNUWA aims to address these limitations and provide highly controllable video generation. The model has been released on Hugging Face and has shown promising results in accurately controlling camera movements and object motions.

Source

 Meta’s new method for text-to-audio

Meta launched a new method, ‘MAGNeT’, for generating audio from text; it uses a single-stage, non-autoregressive transformer to predict masked tokens during training and gradually constructs the output sequence during inference. To improve the quality of the generated audio, an external pre-trained model is used to rescore and rank predictions.

A hybrid version of MAGNeT combines autoregressive and non-autoregressive models for faster generation. The approach is compared to baselines and found to be significantly faster while maintaining comparable quality. Ablation studies and analysis highlight the importance of each component and the trade-offs between autoregressive and non-autoregressive modeling.

It enables high-quality text-to-speech synthesis while being much faster than previous methods. This speed and quality improvement could expand the viability of text-to-speech for systems like virtual assistants, reading apps, dialog systems, and more.

Source

AI discovers a new material in record time

Sam Altman, CEO of OpenAI just got married

All things AI with Sam Altman

By Bill Gates | January 11, 2024

If you’re interested in artificial intelligence, you know who Sam Altman is. If you’ve used ChatGPT, DALL-E, or another product from OpenAI—where Sam is CEO—then you know his work. And if you’ve used Reddit, Dropbox, or Airbnb, you guessed it: You’ve seen Sam’s work, since he helped those companies succeed while running the start-up accelerator Y Combinator.

I’m lucky to know Sam and call him a friend. But he’s also the person I call when I have questions about the future of AI or want to talk something through. So we decided to record one of those conversations and share it with you for the latest episode of Unconfuse Me.

In the episode, Sam and I talk about where AI is now in terms of “thinking” and solving problems—and where it’s headed next, especially its potential to impact jobs and improve healthcare and education. We also discuss how societies adapt to technological change and how humanity will find purpose once we’ve perfected artificial intelligence. And given that Sam is at the forefront of this work, it was great to hear his perspective on the balance between AI innovation and AI regulation.

In case you’re wondering: Our conversation took place shortly before the tech world was rocked by Sam’s abrupt firing from OpenAI (and almost immediate rehiring). But I was able to catch up with him afterward and hear how he and his team are doing. You can listen to his answer—and the rest of our conversation—on Spotify, Apple Podcasts, YouTube, or wherever you get your podcasts. I hope you’ll check this episode out.

As always, thanks for being an Insider.

Researchers identify 26 golden rules for prompting. Here’s what you need to know.

A Daily Chronicle of AI Innovations in January 2024 – Day 10: AI Daily News – January 10th, 2024

GPT has long term memory now

 Rabbit unveils r1, an AI pocket device to do tasks for you

Tech startup Rabbit unveiled r1, an AI-powered companion device that does digital tasks for you. r1 operates as a standalone device, but its software is the real deal– it operates on Rabbit OS and the AI tech underneath. Rather than a ChatGPT-like LLM, this OS is based on a “Large Action Model” (a sort of universal controller for apps).

The Rabbit OS introduces “rabbits”– AI agents that execute a wide range of tasks, from simple inquiries to intricate errands like travel research or grocery shopping. By observing and learning human behaviors, LAM also removes the need for complex integrations like APIs and apps, enabling seamless task execution across platforms without users having to download multiple applications.

Why does this matter?

If Humane can’t do it, Rabbit just might. This can usher in a new era of human-device interaction where AI doesn’t just understand natural language; it performs actions based on users’ intentions to accomplish tasks. It will revolutionize the online experience by efficiently navigating multiple apps using natural language commands.

Source

 Luma AI takes first step towards building multimodal AI

Luma AI is introducing Genie 1.0, its first step towards building multimodal AI. Genie is a text-to-3d model capable of creating any 3d object you can dream of in under 10 seconds with materials, quad mesh retopology, variable polycount, and in all standard formats. You can try it on web and in Luma’s iOS app now.

https://twitter.com/i/status/1744778363330535860

Source

 ByteDance releases MagicVideo-V2 for high-aesthetic video

ByteDance research has introduced MagicVideo-V2, which integrates the text-to-image model, video motion generator, reference image embedding module, and frame interpolation module into an end-to-end video generation pipeline. Benefiting from these architecture designs, MagicVideo-V2 can generate an aesthetically pleasing, high-resolution video with remarkable fidelity and smoothness.

It demonstrates superior performance over leading Text-to-Video systems such as Runway, Pika 1.0, Morph, Moon Valley, and Stable Video Diffusion model via user evaluation at large scale.

Source

What Else Is Happening in AI on January 10th, 2024

Walmart unveils new generative AI-powered capabilities for shoppers and associates.

At CES 2024, Walmart introduced new AI innovations, including generative AI-powered search for shoppers and an assistant app for associates. Using its own tech and Microsoft Azure OpenAI Service, the new design serves up a curated list of the personalized items a shopper is looking for. (Link)

Amazon’s Alexa gets new generative AI-powered experiences.

The company revealed three developers delivering new generative AI-powered Alexa experiences, including AI chatbot platform Character.AI, AI music company Splash, and Voice AI game developer Volley. All three experiences are available in the Amazon Alexa Skill Store. (Link)

Getty Images launches a new GenAI service for iStock customers.

It announced a new service at CES 2024 that leverages AI models trained on Getty’s iStock stock photography and video libraries to generate new licensable images and artwork. Called Generative AI by iStock and powered partly by Nvidia tech, it aims to guard against generations of known products, people, places, or other copyrighted elements. (Link)

Intel challenges Nvidia and Qualcomm with ‘AI PC’ chips for cars.

Intel will launch automotive versions of its newest AI-enabled chips, taking on Qualcomm and Nvidia in the market for semiconductors that can power the brains of future cars. Intel aims to stand out by offering chips that automakers can use across their product lines, from lowest-priced to premium vehicles. (Link)

New material found by AI could reduce lithium use in batteries.

A brand new substance, which could reduce lithium use in batteries by up to 70%, has been discovered using AI and supercomputing. Researchers narrowed down 32 million potential inorganic materials to 18 promising candidates in less than a week– a process that could have taken more than two decades with traditional methods. (Link)

Nvidia rolls out new chips, claims leadership of ‘AI PC’ race 

• Nvidia announced new AI-focused desktop graphics chips at CES, aiming to enhance personal computer capabilities with AI without relying on internet services, positioning itself as a leader in the emerging ‘AI PC’ market.
• The new GeForce RTX 4080 Super significantly outperforms its predecessor, especially in running AI image generation software and ray-traced gaming.
• Despite a general decline in PC shipments, Nvidia’s focus on AI accelerator chips for data centers has driven its market value past $1 trillion, and the new chips are designed to boost AI-enhanced gaming and image-editing experiences.
• Source

EU examines Microsoft investment in OpenAI

• EU antitrust regulators are investigating whether Microsoft’s investment in OpenAI complies with EU merger rules.
• The European Commission is seeking feedback and information on competition concerns in virtual worlds and generative AI.
• EU’s antitrust chief, Margrethe Vestager, emphasizes close monitoring of AI partnerships to avoid market distortion.
• Source

Volkswagen is adding ChatGPT to its cars

• Volkswagen plans to integrate ChatGPT into several car models including the ID. series and new Tiguan and Passat, beginning in the second quarter of the year.
• The AI-powered ChatGPT will assist drivers with car functions and answer questions while ensuring user privacy by not retaining data.
• This move makes Volkswagen the first automaker to standardize chatbot technology in their vehicles, with the potential for other brands to follow suit.
• Source

Microsoft Creates New Battery with AI in Weeks Instead of Years. May Have Profound Implications on Many Industries – Musk Replies “Interesting”

We’re bringing together next-generation AI with high-performance computing to accelerate scientific discovery, collaborating with organizations like @PNNLab to find new materials for energy storage solutions in weeks, not years. https://t.co/ThCAbnRpx2

— Satya Nadella (@satyanadella) January 9, 2024

A Daily Chronicle of AI Innovations in January 2024 – Day 9: AI Daily News – January 09th, 2024

-GPT Store Launched by OpenAI: A new, innovative platform for AI chatbots, similar to Apple’s App Store.

– No Coding Required: Allows anyone to create custom ChatGPT chatbots without needing technical skills.

– Integration Capabilities: Chatbots can be integrated with other services, like Zapier, for enhanced functionality.

– Wide Range of Uses: Chatbots can be tailored for various purposes, from personal assistance to business tools.

*Monetization Opportunities: Creators can earn from their chatbot creations based on user engagement and popularity.

– User-Friendly: Designed to be accessible for both technical and non-technical users.

Unique Marketplace Model: Focuses specifically on AI chatbots, offering a distinct platform for AI innovation and distribution.

Visit our GPT store  here

If you want to dive deeper, consider getting this eBook:

AI Unraveled: Master Generative AI, LLMs, GPT, Gemini & Prompt Engineering – Simplified Guide for Everyday Users: Demystifying Artificial Intelligence, OpenAI, ChatGPT, Bard, AI Quiz, AI Certs Prep

How to Collect Email Leads from your  OpenAI Custom GPTs?

Email authentication for GPTs – Collect email leads from a GPT
byu/ANil1729 inGPTStore

How to add Zapier Actions to your Custom GPT: easy step-by-step guide

Here’s a very simple, step-by-step guide.

If you want to delve deeper, consider reading the full article on my blog by clicking here.
Step 1: Add Zapier Action to Your GPT
Go to GPT settings and click ‘Configure’.
In GPT Builder, select “Create New Action”.
Import Zapier’s API using URL: https://actions.zapier.com/gpt/api/v1/dynamic/openapi.json?tools=meta.
Add this action to your GPT’s schema.

Step 2: Creating Zapier Instructions in Your GPT
Define specific actions (like email sending) in GPT’s instructions.
Copy and paste instructions format from Zapier.
Include action name and confirmation link (ID) from Zapier.

Step 3: Create an Action on Zapier
Sign in to Zapier and visit https://actions.zapier.com/gpt/actions/.
Create a new action, e.g., “Gmail: Send Email”.
Configure the action, like linking your Gmail account.
Give a custom name to your action and enable it.
Add the action’s URL to your GPT instructions.

Test your setup with a command, such as sending an email, to ensure everything works seamlessly.

Want full tutorial?

This guide is easier to follow with images, so visit my blog for the full tutorial by clicking here.

 AI’s Big Reveals at CES 2024

The CES 2024’s first day has big announcements from companies, including Nvidia, LG, and Samsung.

Samsung’s AI-enabled visual display products and digital appliances will introduce novel home experiences. Samsung announced Ballie. The robotic companion follows commands, makes calls, and projects onto the floor, wall, and ceiling.

LG announced their AI Smart Home Agents. They will act as a personified interface for your LG ThinQ smart home products. Plus, it revealed its new Alpha 11 AI processor. The chip uses “precise pixel-level image analysis to effectively sharpen objects and backgrounds that may appear blurry.” And using AI to enhance/upscale TV quality.

Nvidia unveils its GeForce RTX, including the GeForce RTX 40 Super series of desktop graphics cards and a new wave of AI-ready laptops. Read more here.

AMD debuted its new Ryzen 8000G processors for the desktop, with a big focus on their AI capabilities.

Volkswagen plans to integrate an AI-powered chatbot called ChatGPT into its cars and SUVs equipped with its IDA voice assistant. The chatbot, developed by OpenAI and Cerence, will read researched content out loud to drivers. It will be rolled out in Europe starting in the Q2 and available in Volkswagen’s line of EVs and other models.

BMW focuses on interior technology, including gaming, video streaming, AR, and AI features. The company’s operating system will feature AR and AI to enhance car and driver communication. BMW is bringing more streaming video content and gaming options to its vehicles, allowing customers to use real video game controllers.

Know how to watch CES Live?

Why does this matter?

For end users, it will provide:

• More personalized and intuitive interactions with devices and vehicles
• AI assistants that are conversational, helpful, and can perform useful tasks
• Enhanced entertainment through gaming, AR, and upscaled video

For competitors, it enhances the risk of falling behind early movers like BMW, VW, and Samsung.

Source

 Mixtral of Experts beats GPT-3.5 and Llama 2

Mixtral of Experts is a language model that uses a Sparse Mixture of Experts (SMoE) architecture. Each layer has 8 feedforward blocks (experts), and a router network selects two experts to process each token. This allows each token to access 47B parameters but only uses 13B active parameters during inference.

Mixtral outperforms other models like Llama 2 70B and GPT-3.5 in various benchmarks, especially in mathematics, code generation, and multilingual tasks. A fine-tuned version of Mixtral called Mixtral 8x7B – Instruct performs better than other models on human benchmarks. Both models are released under the Apache 2.0 license.

Why does this matter?

Mixtral pushes forward language model capabilities and sparse model techniques. Its open-source release allows wider access and application of these advanced AI systems. This will allow access to a more capable AI system for various tasks and the potential for better mathematical reasoning, code generation, and multilingual applications.

Source

 Figure’s humanoid bot is now proficient in coffee-making

The Figure 01 humanoid robot, developed by California-based company Figure, has successfully learned to make coffee using a coffee machine in just 10 hours. The robot is controlled entirely by neural networks and has also mastered dynamic walking over the course of a year.

In May 2023, Figure closed $70 million in Series A funding, which will be used to develop the Figure 01 humanoid further, expand its AI data pipeline for autonomous operations, and work toward commercialization.

Why does this matter?

Figure 01’s abilities move closer to having robots safely assist in homes, offices, and factories. But at the same time, it raises questions about automation’s impact on jobs and privacy. We need ethical frameworks as robot capabilities grow.

Source

What Else Is Happening in AI on January 09th, 2024

 Cybersecurity company McAfee has launched Project Mockingbird

It detects AI-generated audio used in scams; This tech aims to combat the increasing use of advanced AI models by cyber criminals to create convincing scams, such as voice cloning, to impersonate family members and ask for money. (Link)

 OpenAI has responded to The New York Times copyright infringement lawsuit

Stating that they disagree with the claims and see it as an opportunity to clarify their business practices. OpenAI actively collaborates with news organizations and industry groups to address concerns and create mutually beneficial opportunities. They also counter the NYT’s claim that they are making billions of dollars using the publication’s data, stating that any single data source is insignificant for the model’s learning. (Link)

 Amazon is using AI to help customers find clothes that fit in online shopping

The company uses LLMs, Gen AI, and ML to power 04 AI features. These features include personalized size recommendations, a “Fit Insights” tool for sellers, AI-powered highlights from fit reviews left by other customers, and reimagined size charts. The AI technology analyzes customer reviews, extracts information about fit, and provides personalized recommendations to improve the online shopping experience. (Link)

 Mayo Clinic partners with Cerebras Systems to develop AI for healthcare

The clinic will use Cerebras’ computing chips and systems to analyze decades of anonymized medical records and data. The AI models can read and write text, summarize medical records, analyze images for patterns, and analyze genome data. However, AI systems will not make medical decisions, as doctors will still make them. (Link)

 Microsoft and Siemens join forces to promote AI adoption across industries

They unveiled the Siemens Industrial Copilot, an AI assistant aimed at enhancing collaboration and productivity. The technology is expected to streamline complex automation processes, reduce code generation time, and provide maintenance instructions and simulation tools. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 8: AI Daily News – January 08th, 2024

 NVIDIA’s Parakeet Beats OpenAI’s Whisper v3

NVIDIA’s latest open-source speech recognition models, Parakeet, have outperformed OpenAI’s Whisper v3 in benchmarks. The Parakeet models, developed in partnership with Suno.ai, range from 0.6 to 1.1 billion parameters and are robust to non-speech segments such as music and silence. They offer user-friendly integration into projects through pre-trained control points.

 Tencent released LLaMA-Pro-8B on Hugging Face

Tencent has released LLaMA-Pro-8B, an 8.3 billion parameter model developed by Tencent’s ARC Lab. It is designed for a wide range of natural language processing tasks, with a focus on programming, mathematics, and general language understanding. The model demonstrates advanced performance across various benchmarks.

 TinyLlama: A 1.1B Llama model trained on 3 trillion tokens

TinyLlama is a 1.1 billion parameter model pre-trained on 3 trillion tokens, which represents a significant step in making high-quality natural language processing tools more accessible. Despite its smaller size, TinyLlama demonstrates remarkable performance in various downstream tasks and has outperformed existing open-source language models with comparable sizes.

A Daily Chronicle of AI Innovations in January 2024 – Day 6: AI Daily News – January 06th, 2024

Week 1 Recap

 Meta’s FlowVid: A breakthrough in video-to-video AI
 Alibaba’s AnyText for multilingual visual text generation and editing
 Google to cut 30,000 jobs amid AI integration for efficiency
 JPMorgan announces DocLLM to understand multimodal docs
 Google DeepMind says Image tweaks can fool humans and AI
 ByteDance introduces the Diffusion Model with perceptual loss
 OpenAI’s GPT-4V and Google’s Gemini Pro compete in visual capabilities
 Google DeepMind researchers introduce Mobile ALOHA
 32 techniques to mitigate hallucination in LLMs: A systematic overview
 Google’s new methods for training robots with video and LLMs
 Google DeepMind announced Instruct-Imagen for complex image-gen tasks
 Google reportedly developing paid Bard powered by Gemini Ultra

Hey there! Today, we have some interesting tech news to discuss. So, let’s dive right in!

First up, we have Meta’s FlowVid, which is making waves in the world of video-to-video AI. This breakthrough technology is revolutionizing the way we create and edit videos, allowing for seamless transitions and stunning effects. Say goodbye to clunky edits, and hello to smooth, professional-looking videos!

Moving on, Alibaba’s AnyText is catching our attention with its multilingual visual text generation and editing capabilities. Imagine being able to effortlessly generate and edit text in multiple languages. This tool is a game-changer for anyone working with diverse languages and content.

In other news, it seems like Google is making some big changes. They have announced plans to cut 30,000 jobs, all part of their integration of AI for increased efficiency. This move shows how seriously Google is taking the AI revolution and their commitment to staying at the forefront of technological advancements.

Speaking of AI advancements, JPMorgan has just unveiled DocLLM. This innovative technology allows for a better understanding of multimodal documents. With DocLLM, analyzing documents with a mix of text, images, and videos becomes a breeze. It’s amazing to see how AI is revolutionizing document analysis.

Here’s an interesting one coming from Google DeepMind. They have discovered that image tweaks can actually fool both humans and AI. This finding has significant implications for image recognition and security. It’s fascinating how minor tweaks can completely deceive even advanced AI systems.

Now, let’s move on to ByteDance and their introduction of the Diffusion Model with perceptual loss. This model aims to improve the generation of realistic and high-quality images. With the Diffusion Model, we can expect even more visually stunning and lifelike images in the future.

In the world of visual capabilities, OpenAI’s GPT-4V and Google’s Gemini Pro are going head-to-head. These two giants are competing to push the boundaries of visual AI. It’s an exciting rivalry, and we can’t wait to see the incredible advancements they bring to the table.

Shifting gears, Google DeepMind researchers have recently introduced Mobile ALOHA. This technology focuses on making AI models more lightweight and mobile-friendly without compromising their capabilities. With Mobile ALOHA, we can expect AI applications that are not only powerful but also accessible on a wider range of devices.

Next, let’s discuss an interesting research overview. There are 32 techniques listed to mitigate hallucination in LLMs (Language and Vision Models). This systematic overview provides valuable insights into the challenges and potential solutions for improving the accuracy of LLMs. It’s great to see researchers actively working on enhancing the performance of AI models.

On the topic of training robots, Google is developing new methods that involve using video and LLMs. This approach aims to make robot training more efficient and effective. It’s exciting to think about the possibilities of AI-assisted robotics and how they can enhance various industries, from manufacturing to healthcare.

Continuing with Google DeepMind, they have recently announced Instruct-Imagen. This advanced technology tackles complex image-generation tasks. With Instruct-Imagen, AI can generate images based on textual instructions, opening up a world of creative possibilities.

Last but not least, rumors are circulating that Google is developing a paid Bard, powered by Gemini Ultra. While details are scarce, it’s intriguing to think about the potential emergence of a paid content platform. We’ll definitely keep an eye on this and see how it develops in the coming months.

And that’s a wrap for our tech news update! We hope you found these breakthroughs and advancements as fascinating as we did. Stay tuned for more updates on the ever-evolving world of technology. Until next time!

Are you ready to dive deep into the world of artificial intelligence? Well, look no further because I have just the book for you! It’s called “AI Unraveled: Master GPT-4, Gemini, Generative AI & LLMs – Simplified Guide for Everyday Users: Demystifying Artificial Intelligence – OpenAI, ChatGPT, Google Bard, AI ML Quiz, AI Certifications Prep, Prompt Engineering.” This book is packed with valuable insights and knowledge that will help you expand your understanding of AI.

You can find this essential piece of literature at popular online platforms like Etsy, Shopify, Apple, Google, and Amazon. Whether you prefer physical copies or digital versions, you have multiple options to choose from. So, no matter what your reading preferences are, you can easily grab a copy and start exploring the fascinating world of AI.

With “AI Unraveled,” you’ll gain a simplified guide to complex concepts like GPT-4, Gemini, Generative AI, and LLMs. It demystifies artificial intelligence by breaking down technical jargon into everyday language. This means that even if you’re not an expert in the field, you’ll still be able to grasp the core concepts and learn something new.

So, why wait? Get your hands on “AI Unraveled” and become a master of artificial intelligence today!

In this episode, we explored the latest advancements in AI, including Meta’s FlowVid, Alibaba’s AnyText, and Google’s integration of AI in job cuts, as well as JPMorgan’s release of the DocLLM for multimodal docs, new AI models from Google DeepMind and ByteDance, the visual capabilities competition between OpenAI and Google, Google’s development of methods for training robots, and the announcement of Google DeepMind’s Instruct-Imagen for image-gen tasks, along with reports of Google’s paid Bard powered by Gemini Ultra, all encompassed in “AI Unraveled” – a simplified guide to artificial intelligence available on Etsy, Shopify, Apple, Google, or Amazon. Join us next time on AI Unraveled as we continue to demystify frequently asked questions on artificial intelligence and bring you the latest trends in AI, including ChatGPT advancements and the exciting collaboration between Google Brain and DeepMind. Stay informed, stay curious, and don’t forget to subscribe for more!

A Daily Chronicle of AI Innovations in January 2024 – Day 5: AI Daily News – January 05th, 2024

 Google wrote a ‘Robot Constitution’ to make sure its new AI droids won’t kill us

 OpenAI in talks with dozens of publishers to license content

 Google Bard Advanced leak hints at imminent launch for ChatGPT rival

 Google’s new methods for training robots with video and LLMs
 Google DeepMind announced Instruct-Imagen for complex image-gen tasks
 Google reportedly developing paid Bard powered by Gemini Ultra

 Google wrote a ‘Robot Constitution’ to make sure its new AI droids won’t kill us 

• Google’s DeepMind team has introduced a data gathering system, AutoRT, equipped with a Robot Constitution inspired by Isaac Asimov’s Three Laws of Robotics, designed to help robots understand their environment and make safer decisions by avoiding tasks involving humans and dangerous objects.
• AutoRT, using visual and language models, performed over 77,000 tasks in trials with 53 robots, featuring safety measures like auto-stop and a kill switch.
• Alongside AutoRT, DeepMind has developed additional technologies such as SARA-RT for improved accuracy and RT-Trajectory for enhanced physical task performance.
• Source

OpenAI in talks with dozens of publishers to license content

• OpenAI reportedly offers between $1 million and $5 million annually to license copyrighted news articles for training AI models, indicating a new trend in AI companies investing significantly for licensed material.
• The practice of using licensed content is becoming more common as AI developers face legal challenges and blocks from accessing data, with major publishers like Axel Springer and The Associated Press signing deals with OpenAI.
• This shift towards licensing is part of a broader industry trend, with other AI developers like Google also seeking partnerships with news organizations to use content for AI training.
• Source

 Google Bard Advanced leak hints at imminent launch for ChatGPT rival 

• Google Bard Advanced, with exclusive features like high-level math and reasoning, is hinted to launch soon, possibly bundled with a Google One subscription.
• Leaked information suggests new Bard features, including custom bot creation and specialized tools for brainstorming and managing tasks.
• The exact Google One tier required for Bard Advanced access and its pricing remain undisclosed, but speculation points to the Premium plan.
• Source

Google’s new methods for training robots with video and LLMs

Google’s DeepMind Robotics researchers have announced three advancements in robotics research: AutoRT, SARA-RT, and RT-Trajectory.

1)  AutoRT combines large foundation models with robot control models to train robots for real-world tasks. It can direct multiple robots to carry out diverse tasks and has been successfully tested in various settings. The system has been tested with up to 20 robots at once and has collected over 77,000 trials.

2) SARA-RT converts Robotics Transformer (RT) models into more efficient versions, improving speed and accuracy without losing quality.

3) RT-Trajectory adds visual outlines to training videos, helping robots understand specific motions and improving performance on novel tasks. This training method had a 63% success rate compared to 29% with previous training methods.

Why does this matter?

Google’s 3 advancements will bring us closer to a future where robots can understand and navigate the world like humans. It can potentially unlock automation’s benefits across sectors like manufacturing, healthcare, and transportation.

Source

Google DeepMind announced Instruct-Imagen for complex image-gen tasks

Google released Instruct-Imagen: Image Generation with Multi-modal Instruction, A model for image generation that uses multi-modal instruction to articulate a range of generation intents. The model is built by fine-tuning a pre-trained text-to-image diffusion model with a two-stage framework.

– First, the model is adapted using retrieval-augmented training to enhance its ability to ground generation in an external multimodal context.

– Second, the model is fine-tuned on diverse image generation tasks paired with multi-modal instructions. Human evaluation shows that instruct-imagen performs as well as or better than prior task-specific models and demonstrates promising generalization to unseen and more complex tasks.

Why does this matter?

Instruct-Imagen highlights Google’s command of AI necessary for next-gen applications. This demonstrates Google’s lead in multi-modal AI – using both images and text to generate new visual content. For end users, it enables the creation of custom visuals from descriptions. For creative industries, Instruct-Imagen points to AI tools that expand human imagination and productivity.

Source

Google reportedly developing paid Bard powered by Gemini Ultra

Google is reportedly working on an upgraded, paid version of Bard – “Bard Advanced,” which will be available through a paid subscription to Google One. It might include features like creating custom bots, an AI-powered “power up” feature, a “Gallery” section to explore different topics and more. However, it is unclear when these features will be officially released.

All screenshots were leaked by@evowizz on X.

Why does this matter?

This shows Google upping its AI game to directly compete with ChatGPT. For end users, it means potentially more advanced conversational AI. Competitors like OpenAI pressure Google to stay ahead. And across sectors like education, finance, and healthcare, Bard Advanced could enable smarter applications.

Source

What Else Is Happening in AI on January 05th, 2024

 OpenAI offers media outlets as little as $1M to use their news articles to train AI models like ChatGPT

The proposed licensing fees of $1 million to $5 million are considered small even for small publishers. OpenAI is reportedly negotiating with up to a dozen media outlets, focusing on global news operations. The company has previously signed deals with Axel Springer and the Associated Press, with Axel Springer receiving tens of millions of dollars over several years. (Link)

 Researchers from the University of California, Los Angeles, and Snap have developed a method for personalized image restoration called Dual-Pivot Tuning

It is an approach used to customize a text-to-image prior in the context of blind image restoration. It leverages personal photos to customize image restoration models, better preserving individual facial features. (Link)

 CES 2024 tech trade show in Las Vegas will focus on AI: What To Expect?

• AI will be the show’s major theme and focus, with companies like Intel, Walmart, Best Buy, and Snap expected to showcase AI-enabled products and services.
• Generative AI art was used to create the CES 2024 promotional imagery. GenAI, more broadly will have a big presence.
• AR & VR headsets will be showcased, with companies like Meta, Vuzix, and others exhibiting. This is timed with the expected launch of Apple’s headset in 2024.
• Robots across categories like vacuums, bartenders, and restaurants will be present, and much more. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 4: AI Daily News – January 04th, 2024

 OpenAI to launch custom GPT store next week

OpenAI GPT Store officially launching next week

• OpenAI’s GPT Store, enabling users to share and sell custom AI agents, is set to launch next week.
• The platform targets ChatGPT Plus and enterprise subscribers, allowing them to build and monetize specialized ChatGPT models.
• Although its launch was postponed from November, OpenAI is preparing GPT Builders for the upcoming release.

OpenAI’s GPT-4V and Google’s Gemini Pro compete in visual capabilities

Two new papers from Tencent Youtu Lab, the University of Hong Kong, and numerous other universities and institutes comprehensively compare the visual capabilities of Gemini Pro and GPT-4V, currently the most capable multimodal language models (MLLMs).

Both models perform on par on some tasks, with GPT-4V rated slightly more powerful overall. The models were tested in areas such as image recognition, text recognition in images, image and text understanding, object localization, and multilingual capabilities.

Why does this matter?

While both are impressive models, they have room for improvement in visual comprehension, logical reasoning, and robustness of prompts. The road to multimodal general-purpose AI is still a long one, the paper concludes.

Source

Google DeepMind researchers introduce Mobile ALOHA

Student researchers at DeepMind introduce ALOHA: A Low-cost Open-source Hardware System for Bimanual Teleoperation. With 50 demos, the robot can autonomously complete complex mobile manipulation tasks:

• Cook and serve shrimp
• Call and take elevator
• Store a 3Ibs pot to a two-door cabinet

And more.

ALOHA is open-source and built to be maximally user-friendly for researchers– it is simple, dependable and performant. The whole system costs <$20k, yet it is more capable than setups with 5-10x the price.

Why does this matter?

Imitation learning from human-provided demos is a promising tool for developing generalist robots, but there are still some challenges for wider adoption. This research seek to tackle the challenges of applying imitation learning to bimanual mobile manipulation

Source

32 techniques to mitigate hallucination in LLMs: A systematic overview

New paper from Amazon AI, Stanford University, and others presents a comprehensive survey of over 32 techniques developed to mitigate hallucination in LLMs. Notable among these are Retrieval Augmented Generation, Knowledge Retrieval, CoNLI, and CoVe.

Furthermore, it introduces a detailed taxonomy categorizing these methods based on various parameters, such as dataset utilization, common tasks, feedback mechanisms, and retriever types. This classification helps distinguish the diverse approaches specifically designed to tackle hallucination issues in LLMs. It also analyzes the challenges and limitations inherent in these techniques.

Why does this matter?

Hallucinations are a critical issue as we use language generation capabilities for sensitive applications like summarizing medical records, financial analysis reports, etc. This paper serves as a valuable resource for researchers and practitioners seeking a comprehensive understanding of the current landscape of hallucination in LLMs and the strategies employed to address this pressing issue.

Source

 Microsoft changes PC keyboard for the first time in 30 years

• Microsoft is adding a Copilot key to Windows keyboards as part of the most significant redesign since the 1990s.
• The new Copilot button, near the space bar, will activate Microsoft’s AI chatbot and feature on new PCs, including Surface devices, with more reveals at CES.
• This change is part of a broader push to dominate the AI-integrated PC market, amidst a landscape where 82% of computers run Windows.
• Source

 Qualcomm announces new chip to power Samsung and Google’s competitor to Apple Vision Pro

• Qualcomm unveiled a new Snapdragon XR2+ Gen 2 chip designed to power upcoming mixed reality devices from Samsung and Google, potentially rivaling Apple’s Vision Pro headset.
• The new chip promises enhanced processing power and graphics capabilities, aiming to offer a more affordable alternative to Apple’s high-end device.
• Details about the launch of Samsung and Google’s mixed reality devices are not yet available.
• Source

 Jeff Bezos bets on Google challenger

• Jeff Bezos and other tech investors have contributed $74 million to Perplexity, a startup aiming to challenge Google’s stronghold on internet searches, valuing the company at over half a billion dollars.
• Perplexity seeks to leverage advancements in artificial intelligence to provide direct answers to queries, potentially offering a more efficient alternative to Google’s traditional link-based results.
• Despite the ambitious investment and innovative approach, Perplexity faces a daunting challenge in disrupting Google’s dominant market position, which has remained unshaken despite previous attempts by major firms.
• Source

 AI and satellites expose 75% of fish industry ‘ghost fleets’ plundering oceans

• A study using satellite imagery and machine learning uncovered that up to 76% of global industrial fishing vessels aren’t publicly tracked, suggesting widespread unreported fishing.
• Researchers created a global map of maritime activities, revealing concentrated vessel activity with Asia accounting for the majority, and highlighted underreporting of industrial activities at sea.
• The growing ‘blue economy’ is valued at trillions but poses environmental risks, with a significant portion of fish stocks overexploited and marine habitats lost due to industrialization.
• Source

ChatGPT-4 struggles with pediatric cases, showing only a 17% accuracy rate in a study, highlighting the need for better AI training and tuning. LINK

A Daily Chronicle of AI Innovations in January 2024 – Day 3: AI Daily News – January 03rd, 2024

 JPMorgan announces DocLLM to understand multimodal docs
 Google DeepMind says Image tweaks can fool humans and AI
 ByteDance introduces the Diffusion Model with perceptual loss

JPMorgan announces DocLLM to understand multimodal docs

DocLLM is a layout-aware generative language model designed to understand multimodal documents such as forms, invoices, and reports. It incorporates textual semantics and spatial layout information to effectively comprehend these documents. Unlike existing models, DocLLM avoids using expensive image encoders and instead focuses on bounding box information to capture the cross-alignment between text and spatial modalities.

It also uses a pre-training objective to learn to infill text segments, allowing it to handle irregular layouts and diverse content. The model outperforms state-of-the-art models on multiple document intelligence tasks and generalizes well to unseen datasets.

Why does this matter?

This new AI can revolutionize how businesses process documents like forms and invoices. End users will benefit from faster and more accurate document understanding. Competitors will need to invest heavily to match this technology. DocLLM pushes boundaries in multimodal AI – understanding both text and spatial layouts.

This could become the go-to model for document intelligence tasks, saving companies time and money. For example, insurance firms can automate claim assessments, while banks can speed loan processing.

Source

Google DeepMind says Image tweaks can fool humans and AI

Google DeepMind’s new research shows that subtle changes made to digital images to confuse computer vision systems can also influence human perception. Adversarial images intentionally altered to mislead AI models can cause humans to make biased judgments.

The study found that even when more than 2 levels adjusted no pixel on a 0-255 scale, participants consistently chose the adversarial image that aligned with the targeted question. This discovery raises important questions for AI safety and security research and emphasizes the need for further understanding of technology’s effects on both machines and humans.

Why does this matter?

AI vulnerabilities can unwittingly trick humans, too. Adversaries could exploit this to manipulate perceptions and decisions. It’s a wake-up call for tech companies to enact safeguards and monitoring against AI exploitation.

Source

ByteDance introduces the Diffusion Model with perceptual loss

This paper introduces a diffusion model with perceptual loss, which improves the quality of generated samples. Diffusion models trained with mean squared error loss often produce unrealistic samples. Current models use classifier-free guidance to enhance sample quality, but the reasons behind its effectiveness are not fully understood.

They propose a self-perceptual objective incorporating perceptual loss in diffusion training, resulting in more realistic samples. This method improves sample quality for conditional and unconditional generation without sacrificing sample diversity.

Why does this matter?

This advances diffusion models for more lifelike image generation. Users will benefit from higher-quality synthetic media for gaming and content creation applications. But it also raises ethical questions about deepfakes and misinformation.

Source

What Else Is Happening in AI on January 03rd, 2024

 Jellypipe launches AI for 3D printing, Optimizes material selection & pricing with GPT-4

It responds to customer queries and offers advice, including suggesting optimal materials for specific applications and creating dynamic price quotes. It is built on OpenAI’s GPT-4 LLM system and has an internal materials database. Currently, it’s in beta testing. It will be launched to solution partners first and then to customers in general. (Link)

 Seoul Govt (South Korea) plans to use drones and AI to monitor real-time traffic conditions by 2024

It will enhance traffic management and overall transportation efficiency. (Link)

 Christopher Pissarides warns younger generations against studying STEM because AI could take over analytical tasks

He explains that the skills needed for AI advancements will become obsolete as AI takes over these tasks. Despite the high demand for STEM professionals, Pissarides argues that jobs requiring more traditional and personal skills will dominate the labor market in the long term. (Link)

 New research from the University of Michigan found that LLMs perform better when prompted to act gender-neutral or male rather than female

This highlights the need to address biases in the training data that can lead machine learning models to develop unfair biases. The findings are a reminder to ensure AI systems treat all genders equally. (Link)

 Samsung is set to unveil its new robot vacuum and mop combo

The robot vacuum uses AI to spot and steam-clean stains on hard floors. It also has the ability to remove its mops to tackle carpets. It features a self-emptying, self-cleaning charging base called the Clean Station, which refills the water tank and washes and dries the mop pads. (Link)

A Daily Chronicle of AI Innovations in January 2024 – Day 1 an 2: AI Daily News – January 02nd, 2024

 OpenAI’s revenues soared 5,700% last year

 US pressured Netherlands to block chipmaking machine shipments

 Tesla’s record year

 We are about to enter the golden age of gene therapy

 Nobel prize winner cautions on rush into STEM after rise of AI

 Meta’s FlowVid: A breakthrough in video-to-video AI
 Alibaba’s AnyText for multilingual visual text generation and editing
 Google to cut 30,000 jobs amid AI integration for efficiency

 OpenAI’s revenues soared 5,700% last year 

• OpenAI’s annualized revenue increased by 20% in two months, reaching over $1.6 billion despite CEO Sam Altman’s brief firing and reinstatement.
• The company’s strong financial performance includes a significant year-over-year growth from $28 million to $1.6 billion in annual revenue.
• OpenAI is planning to raise more funding, aiming for a $100 billion valuation, and is exploring custom chip production with a potential initial funding of $8-$10 billion.
• Source

 We are about to enter the golden age of gene therapy 

• Gene therapy, especially with CRISPR-Cas9, is advancing rapidly with new treatments like Casgevy, signaling a transformative era in tackling various diseases.
• Upcoming gene therapies promise greater precision and broader applicability, but are challenged by high costs and complex ethical debates.
• The future of gene therapy hinges on balancing its potential against ethical considerations and ensuring equitable access.
• Source

 Nobel prize winner cautions on rush into STEM after rise of AI

• Nobel laureate Christopher Pissarides warned that focusing heavily on STEM subjects could lead to skills that AI will soon perform.
• Jobs with “empathetic” skills, like those in hospitality and healthcare, are expected to remain in demand despite AI advancements.
• Pissarides suggested valuing personal care and social relationship jobs, rather than looking down on them
• Source

Meta’s FlowVid: A breakthrough in video-to-video AI

Diffusion models have transformed the image-to-image (I2I) synthesis and are now making their way into videos. However, the advancement of video-to-video (V2V) synthesis has been hampered by the challenge of maintaining temporal consistency across video frames.

Meta research proposes a consistent V2V synthesis method using joint spatial-temporal conditions, FlowVid. It demonstrates remarkable properties:

1. Flexibility: It works seamlessly with existing I2I models, facilitating various modifications, including stylization, object swaps, and local edits.
2. Efficiency: Generation of a 4-second video with 30 FPS and 512×512 resolution takes only 1.5 minutes, which is 3.1x, 7.2x, and 10.5x faster than CoDeF, Rerender, and TokenFlow, respectively.
3. High-quality: In user studies, FlowVid is preferred 45.7% of the time, outperforming CoDeF (3.5%), Rerender (10.2%), and TokenFlow (40.4%).

Why does this matter?

The model empowers us to generate lengthy videos via autoregressive evaluation. In addition, the large-scale human evaluation indicates the efficiency and high generation quality of FlowVid.

Source

Alibaba releases AnyText for multilingual visual text generation and editing

Diffusion model based Text-to-Image has made significant strides recently. Although current technology for synthesizing images is highly advanced and capable of generating images with high fidelity, it can still reveal flaws in the text areas in generated images.

To address this issue, Alibaba research introduces AnyText, a diffusion-based multilingual visual text generation and editing model, that focuses on rendering accurate and coherent text in the image.

Why does this matter?

This extensively researches the problem of text generation in the field of text-to-image synthesis. Consequently, it can improve the overall utility and potential of AI in applications.

Source

Google to cut 30,000 jobs amid AI integration for efficiency

Google is considering a substantial workforce reduction, potentially affecting up to 30,000 employees, as part of a strategic move to integrate AI into various aspects of its business processes.

The proposed restructuring is anticipated to primarily impact Google’s ad sales department, where the company is exploring the benefits of leveraging AI for operational efficiency.

Why does this matter?

Google is actively engaged in advancing its AI models, but this also suggests that the tech giant is not just focusing on AI development for external applications but is also contemplating a significant shift in its operational structure.

Source

What Else Is Happening in AI on January 02nd, 2024

OpenAI’s annualized revenue tops $1.6 billion as customers shrug off CEO drama.

It went up from $1.3 billion as of mid-October. The 20% growth over two months suggests OpenAI was able to hold onto its business momentum despite a leadership crisis in November that provided an opening for rivals to go after its customers. (Link)

GitHub makes Copilot Chat generally available, letting devs ask code questions.

GitHub’s launching Chat in general availability for all users. Copilot Chat is available in the sidebar in Microsoft’s IDEs, Visual Studio Code, and Visual Studio– included as a part of GitHub Copilot paid tiers and free for verified teachers, students and maintainers of certain open source projects. (Link)

Nikon, Sony, and Canon fight AI fakes with new camera tech.

They are developing camera technology that embeds digital signatures in images so that they can be distinguished from increasingly sophisticated fakes. Such efforts come as ever-more-realistic fakes appear, testing the judgment of content producers and users alike. (Link)

Scientists discover the first new antibiotics in over 60 years using AI.

A new class of antibiotics for drug-resistant Staphylococcus aureus (MRSA) bacteria was discovered using more transparent deep learning models. The team behind the project used a deep-learning model to predict the activity and toxicity of the new compound. (Link)

Samsung aims to replicate human vision by integrating AI in camera sensors.

Samsung is reportedly planning to incorporate a dedicated chip responsible for AI duties directly into its camera sensors while aiming to create sensors capable of sensing and replicating human senses in the long term. It is calling this “Humanoid Sensors” internally and would likely incorporate the tech into its devices earliest by 2027. (Link)

AI can find your location in photos

• Artificial intelligence can accurately geolocate photos, raising concerns about privacy.

• A student project called PIGEON developed by Stanford graduate students demonstrated the ability of AI to identify locations in personal photos.

• While this technology has potential beneficial applications, such as helping people identify old snapshots or conducting surveys, it also raises concerns about government surveillance, corporate tracking, and stalking.

• The project used an existing system called CLIP and trained it with images from Google Street View.

• PIGEON can guess the correct country 95% of the time and locate a place within about 25 miles of the actual site.

Source: https://www.npr.org/2023/12/19/1219984002/artificial-intelligence-can-find-your-location-in-photos-worrying-privacy-expert

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A Daily Chronicle of AI Innovations in December 2023

A Daily Chronicle of AI Innovations in January 2024: Year 2023 Recap

1- Google DeepMind AI discovers 70% faster sorting algorithm, with milestone implications for computing power.

A full breakdown of the paper is available here but I’ve included summary points below for the Reddit community.

Why did Google’s DeepMind do?

• They adapted their AlphaGo AI (which had decimated the world champion in Go a few years ago) with “weird” but successful strategies, into AlphaDev, an AI focused on code generation.

• The same “game” approach worked: the AI treated a complex basket of computer instructions like they’re game moves, and learned to “win” in as few moves as possible.

• New algorithms for sorting 3-item and 5-item lists were discovered by DeepMind. The 5-item sort algo in particular saw a 70% efficiency increase.

Why should I pay attention?

• Sorting algorithms are commonly used building blocks in more complex algos and software in general. A simple sorting algorithm is probably executed trillions of times a day, so the gains are vast.

• Computer chips are hitting a performance wall as nano-scale transistors run into physical limits. Optimization improvements, rather than more transistors, are a viable pathway towards increased computing speed.

• C++ hadn’t seen an update in its sorting algorithms for a decade. Lots of humans have tried to improve these, and progress had largely stopped. This marks the first time AI has created a code contribution for C++.

• The solution DeepMind devised was creative. Google’s researchers originally thought AlphaDev had made a mistake — but then realized it had found a solution no human being had contemplated.

The main takeaway: AI has a new role — finding “weird” and “unexpected” solutions that humans cannot conceive

• The same happened in Go where human grandmasters didn’t understand AlphaGo’s strategies until it showed it could win.

• DeepMind’s AI also mapped out 98.5% of known proteins in 18-months, which could usher in a new era for drug discovery as AI proves more capable and creative than human scientists.

As the new generation of AI products requires even more computing power, broad-based efficiency improvements could be one way of helping alleviate challenges and accelerate progress.

2- Getting Emotional with LLMs Can increase Performance by 115% (Case Study)

This research was a real eye-opener. Conducted by Microsoft, the study investigated the impact of appending emotional cues to the end of prompts, such as “this is crucial for my career” or “make sure you’re certain.” They coined this technique as EmotionPrompt.
What’s astonishing is the significant boost in accuracy they observed—up to 115% in some cases! Human evaluators also gave higher ratings to responses generated with EmotionPrompt.
What I absolutely love about this is its ease of implementation—you can effortlessly integrate custom instructions into ChatGPT.
We’ve compiled a summary of this groundbreaking paper. Feel free to check it out here.
For those interested in diving deeper, here’s the link to the full paper.

 3- How I Replaced Myself with AI and Why You Might Too.

• The author, with a background in accounting and finance, had a talent for spotting inefficiencies and finding ways to eliminate them.

• They initially eliminated time-consuming meetings by implementing a shared spreadsheet system, significantly improving processing time.

• This success sparked their interest in automation and process design, leading them to actively seek out areas to improve and automate.

• They learned to use Excel macros to streamline tasks and became involved in numerous optimization efforts throughout their career.

• Over time, they mastered various Microsoft Office tools and implemented custom buttons, filters, and automations to handle tasks more efficiently.

• They utilized AI features like meeting transcriptions and chatbots to automate parts of their workflow.

• As a result, about 90% of their job responsibilities are now automated, and they spend their time supervising and improving the AI systems they’ve implemented.

• The author believes that AI should be seen as a tool to eliminate mundane tasks and enhance productivity, allowing individuals to focus on higher-level responsibilities.

4- Most Active countries interested in AI

• USA
• Canada
• United Kingdom

5- Creation of videos of animals that do not exist with Stable Diffusion | The end of Hollywood is getting closer

6- This is surreal: ElevenLabs AI can now clone the voice of someone that speaks English (BBC’s David Attenborough in this case) and let them say things in a language, they don’t speak, like German.

7- Turned ChatGPT into the ultimate bro

8-Being accused for using ChatGPT in my assignment, what should I do ?

The teacher does not seem unreasonable. They are using a tool that they may or may not know is ineffective at detecting, but probably was told to use by the faculty. ChatGPT has created issues with traditional assignments, and some people are cheating. Universities are trying to adapt to this change — don’t panic.

If you really didn’t use AI, do NOT come across as hostile right off the bat, as it will set red flags. Immediately going to the Dean is not going to help you — that is such bad advice I can’t even comprehend why someone would suggest that. The Professor is not trying to fail you; they are asking for an informal meeting to talk about the allegation.

Explain to them that you did not use AI, and ask how you can prove it. Bring another paper you wrote, and tell them you have a Word editing history, if it you have it. Just talk with the professor — they are not out to get you; they want you to succeed. They just want to ensure no one is cheating on their assignments.

If and only if they are being unreasonable in the meeting, and seem determined to fail you (and you really didn’t use AI), should you escalate it.

9- Photoshop AI Generative Fill was used for its intended purpose

10- Bing ChatGPT too proud to admit mistake, doubles down and then rage quits

See also

• 🌐 AI Innovations to explore recent advancements in AI.
• 🤖 AI Industry Trends for insights into current trends in the AI sector.

You may also enjoy

• 🚀 Futuristic Technologies for a glimpse into other emerging tech innovations.
• 🧠 AI and Society to understand how AI is shaping our world.

AI 2023 Recap Podcast

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 major developments in the world of artificial intelligence (AI) from January to December 2023. Additionally, we’ll mention the availability of the book “AI Unraveled” for a simplified guide on artificial intelligence.

Hey there, let’s dive into some of the major developments in the world of artificial intelligence (AI) from January to December 2023!

In January, there was big news as Microsoft invested a whopping $10 billion in OpenAI, the creator of ChatGPT. This investment signaled a strong belief in the potential of AI technology. And speaking of AI technology, MIT researchers made waves by developing an AI that can predict future lung cancer risks. This advancement could have a huge impact on healthcare in the future.

Moving on to February, ChatGPT reached a milestone with 100 million unique users. This demonstrated the widespread adoption and popularity of OpenAI’s language model. Meanwhile, Google created Bard, a conversational AI chatbot powered by LaMDA. This highlighted Google’s commitment to advancing natural language processing capabilities. Microsoft also joined the action by launching a new Bing Search Engine integrated with ChatGPT, enhancing the search experience for users. Additionally, AWS partnered with Hugging Face to empower AI developers, fostering collaboration and innovation.

In March, Adobe decided to enter the generative AI game with Firefly, opening up new possibilities for creative applications. Canva, on the other hand, introduced AI design tools focused on assisting workplaces and boosting productivity. OpenAI made headlines again with the announcement of GPT-4, which could accept both text and image inputs, revolutionizing the capabilities of the ChatGPT model. OpenAI also launched Whisper, making APIs for ChatGPT available to developers.

HubSpot introduced new AI tools to boost productivity and save time, catering to the needs of businesses. Google integrated AI into the Google Workspace, creating a more seamless user experience. Microsoft combined the power of Language Model Models (LLMs) with user data, unlocking even more potential for personalized AI experiences. And in the coding world, GitHub launched Copilot X, an AI coding assistant, while Replit and Google Cloud joined forces to advance Gen AI for software development.

In April, AutoGPT unveiled its next-generation AI designed to perform tasks without human intervention. Elon Musk was also in the spotlight, working on ‘TruthGPT,’ which drew considerable attention and speculation. Meanwhile, Apple was building a paid AI health coach, signaling its commitment to the intersection of technology and healthcare. Meta released DINOv2, a new image recognition model, further advancing computer vision capabilities. And Alibaba announced its very own LLM, “Tongyi Qianwen,” to rival OpenAI’s ChatGPT.

May brought more exciting developments, including Microsoft’s Windows 11 AI Copilot. Sanctuary AI unveiled Phoenix™, its sixth-generation general-purpose robot, pushing the boundaries of robotics. Inflection AI introduced Pi, a personal intelligence tool, catering to individuals’ needs. Stability AI released StableStudio, an open-source variant of its DreamStudio, empowering creators. OpenAI also launched the ChatGPT app for iOS, bringing its AI language model into the hands of mobile users. Meta introduced ImageBind, a new AI research model, further expanding its AI offerings. And Google unveiled the PaLM 2 AI language model, enhancing language understanding capabilities.

June saw Apple introduce Apple Vision Pro, a powerful tool advancing computer vision technology. McKinsey released a study highlighting that AI could add up to $4.4 trillion a year to the global economy, emphasizing its potential economic impact. Runway’s Gen-2 was officially released, driving innovation in the AI development space.

In July, Apple trialed ‘Apple GPT,’ a ChatGPT-like AI chatbot, showcasing their foray into conversational AI. Meta introduced Llama2, the next generation of open-source LLM, inviting further collaboration and community involvement. Stack Overflow announced OverflowAI, aiming to enhance developer productivity and support. Anthropic released Claude 2 with impressive 200K context capability, advancing natural language understanding. And Google worked on building an AI tool specifically for journalists, recognizing the potential AI has to support content creation and journalism.

August brought OpenAI’s expansion of ChatGPT ‘Custom Instructions’ to free users, democratizing access to customization features. YouTube ran a test with AI auto-generated video summaries, exploring the potential for automated video content creation. MidJourney introduced the Vary Region Inpainting feature, further enriching their AI capabilities. Meta’s SeamlessM4T impressed by being able to transcribe and translate close to 100 languages, breaking language barriers. Tesla also made headlines with the launch of its $300 million AI supercomputer, showcasing their commitment to AI research and development.

September brought OpenAI’s upgrade of ChatGPT with web browsing capabilities, allowing users to browse the web within the chatbot interface. Stability AI released Stable Audio, its first product for music and sound effect generation, catering to the needs of content creators. YouTube launched YouTube Create, a new app aimed at empowering mobile creators. Even Coca-Cola jumped into the AI game, launching a new AI-created flavor, demonstrating the diverse applications of AI technology. Mistral AI also made a splash with its open-source LLM, Mistral 7B, further contributing to the AI community. Amazon supercharged Alexa with generative AI, enhancing the capabilities of its popular assistant. Microsoft, on the other hand, open-sourced EvoDiff, a novel protein-generating AI, advancing the field of bioinformatics. And OpenAI upgraded ChatGPT once again, this time with voice and image capabilities, expanding its multi-modal capabilities.

In October, users of ChatGPT Plus and Enterprise were treated to the availability of DALL·E 3, bringing advanced image generation to OpenAI’s subscribers. Amazon joined the humanoid robot market by unveiling “Digit,” showcasing their foray into robotics. ElevenLabs launched the Voice Translation Tool, breaking down language barriers and fostering global communication. Google experimented with new ways to boost productivity from their search engine, aiming to make users’ lives easier. Rewind Pendant introduced a new AI wearable that captures real-world conversations, opening up new possibilities for personal assistants. LinkedIn also introduced new AI products and tools, aiming to enhance the professional networking experience.

In November, the UK hosted the first-ever AI Safety Summit, emphasizing the importance of ethical and responsible AI development. OpenAI announced new models and products at DevDay, further expanding their offerings. Humane officially launched the AI Pin, a tool focused on enhancing productivity and collaboration. Elon Musk joined the AI chatbot race with the launch of Grok, positioning it as a rival to OpenAI’s ChatGPT. Pika Labs also launched ‘Pika 1.0’, showcasing their advancements in AI technology. Google DeepMind and YouTube showcased their collaboration with the reveal of the new AI model called ‘Lyria.’ Lastly, OpenAI delayed the launch of the custom GPT store to early 2024, ensuring they deliver the best possible experience for users. Stability AI also made stable video diffusion available on their platform’s API, enabling content creators to leverage AI for video enhancement. Amazon added to the excitement by announcing Amazon Q, an AI-powered assistant from AWS.

December brought more developments, starting with Google’s launch of Gemini, an AI model that rivals GPT-4. AMD released the Instinct MI300X GPU and MI300A APU chips, further advancing the hardware capabilities for AI applications. MidJourney released V6, showcasing the continued evolution of their AI solutions. Mistral introduced Mixtral 8x7B, a leading open SMoE model, adding to the growing ecosystem of AI research. Microsoft released Phi-2, a powerful SLM that outperformed Llama 2, pushing the boundaries of language models. Lastly, it was reported that OpenAI was about to raise additional funding at a valuation of over $100 billion, reflecting the immense potential and interest in the AI industry.

And that wraps up the major developments in the world of AI from January to December 2023. Stay tuned for more exciting advancements in the future!

Are you ready to dive deep into the world of artificial intelligence? Well, look no further because I have just the book for you! It’s called “AI Unraveled: Master GPT-4, Gemini, Generative AI & LLMs – Simplified Guide for Everyday Users: Demystifying Artificial Intelligence – OpenAI, ChatGPT, Google Bard, AI ML Quiz, AI Certifications Prep, Prompt Engineering.” This book is packed with valuable insights and knowledge that will help you expand your understanding of AI.

You can find this essential piece of literature at popular online platforms like Etsy, Shopify, Apple, Google, and Amazon. Whether you prefer physical copies or digital versions, you have multiple options to choose from. So, no matter what your reading preferences are, you can easily grab a copy and start exploring the fascinating world of AI.

With “AI Unraveled,” you’ll gain a simplified guide to complex concepts like GPT-4, Gemini, Generative AI, and LLMs. It demystifies artificial intelligence by breaking down technical jargon into everyday language. This means that even if you’re not an expert in the field, you’ll still be able to grasp the core concepts and learn something new.

So, why wait? Get your hands on “AI Unraveled” and become a master of artificial intelligence today!

In this episode, we explored the latest developments in the AI industry, from Microsoft’s investment in OpenAI to the launch of new products like Google’s Bard and Microsoft’s Windows 11 AI Copilot, as well as advancements in ChatGPT, AutoGPT, and more. We also recommended the book “AI Unraveled” as a simplified guide to artificial intelligence, which you can find on Etsy, Shopify, Apple, Google, or Amazon. Stay tuned for more exciting updates in the world of AI and don’t forget to grab your copy of “AI Unraveled” for a deeper understanding. Join us next time on AI Unraveled as we continue to demystify frequently asked questions on artificial intelligence and bring you the latest trends in AI, including ChatGPT advancements and the exciting collaboration between Google Brain and DeepMind. Stay informed, stay curious, and don’t forget to subscribe for more!

How to Use Zapier’s No-Code Automation With Custom GPTs (Easy Step-by-Step Guide)

Step 1: Add Zapier Action to Your GPT

Getting Started with Zapier Integration:

‍To begin integrating Zapier actions into your GPT, start by accessing the ‘Configure’ option in your GPT’s settings. If you’re new to GPTs, you’ll need to create one first.

This can be easily done by navigating to the “Explore” section and selecting “Create a GPT” within the “My GPTs” area.

Creating a New Action for Your GPT in Zapier:

‍Once in the GPT Builder,

Click on “Configure” and then choose “Create New Action.”

Copy & Paste the URL Below and Import to “Add actions”

You’ll encounter a window prompting you to “Import from URL.”

Here, simply paste the following URL:

‍https://actions.zapier.com/gpt/api/v1/dynamic/openapi.json?tools=meta‍

and click on “Import.”

This action will populate your schema with some text, which you must leave as is.

Now just click on “<” button and come back to the “Configure” tab.

After completing the previous step, and returning to the ‘Configure’ section, you’ll now see the newly added Zapier action.

Step 2: Creating Zapier Instructions inside Your GPT

Now, it’s all about Zapier and GPT communicating between each other.

Defining the Actions:

‍Zapier offers a range of actions, from email sending to spreadsheet updates.

Therefore, it’s essential to specify in your GPT’s instructions the particular action you wish to use.

This requires adhering to a specific format provided by Zapier, which includes a set of rules and step-by-step instructions for integrating custom actions.

Copy & Paste Zapier Instructions for GPT

Customizing the GPT Instructions

‍In your GPT instructions, paste the text provided by Zapier, which guides the GPT on how to check for and execute the required actions.

This includes verifying the availability of actions, guiding users through enabling required actions, and configuring the GPT to proceed with the user’s instructions using available action IDs.

The text requires filling in two fields: the action’s name and the confirmation link (ID), which can be obtained from the Zapier website.

Copy & Paste The Following Instructions:

### Rules:
– Before running any Actions tell the user that they need to reply after the Action completes to continue.

### Instructions for Zapier Custom Action:
Step 1. Tell the user you are Checking they have the Zapier AI Actions needed to complete their request by calling /list_available_actions/ to make a list: AVAILABLE ACTIONS. Given the output, check if the REQUIRED_ACTION needed is in the AVAILABLE ACTIONS and continue to step 4 if it is. If not, continue to step 2.
Step 2. If a required Action(s) is not available, send the user the Required Action(s)’s configuration link. Tell them to let you know when they’ve enabled the Zapier AI Action.
Step 3. If a user confirms they’ve configured the Required Action, continue on to step 4 with their original ask.
Step 4. Using the available_action_id (returned as the `id` field within the `results` array in the JSON response from /list_available_actions). Fill in the strings needed for the run_action operation. Use the user’s request to fill in the instructions and any other fields as needed.

REQUIRED_ACTIONS: – Action: Confirmation Link:

Step 3: Create an Action on Zapier

Building Your Custom Automation:

‍The final step in integrating GPT with Zapier is creating the automation (or action) you wish to add.

First, visit Zapier’s website and sign up or log in if you haven’t already.

Go to https://actions.zapier.com/gpt/actions/ after you logged into your Zapier account.

Now you’ll be able to create a new action.

For this guide, we’ll focus on setting up an action to send an email via Gmail, but remember, Zapier offers a multitude of app integrations, from Excel to YouTube.

‍

Configuring the Zapier Action:

‍After selecting the desired action – in our case, “Gmail: Send Email” – you’ll move on to fine-tuning the settings.

This typically involves connecting to the external application, like your Gmail account.

While most settings can be left for “Have AI guess a value for this field”, it’s important to ensure the action aligns with your specific needs. Once configured, simply enable the action.

Give the action a custom name of your choice.

To do that, you click on “Show all options” and scroll down to the very bottom.

You will see your action’s name box, which I simply called “Send Email”.

After click “Enable action” it will be ready to be used!

The action’s name should then be copy pasted inside the GPT Instructions template mentioned above (See Actions – section).

All you need to do now is to copy the URL of this action and paste it into the above-mentioned GPT Instructions prompt (See Confirmation Link: section), locatedinside the “Configurations” tab of your GPT.

This is how your “Required_Actions” shoud look now:

Testing the Action

Launching Your First Test:

‍With your action now created and enabled, it’s time to put it to the test.

Prompt your GPT and with a test command, such as sending an email.

In my example, I will use:

“Send an email ‘Custom GPT’ to [your_second_email@email.com].”

Make sure to use a different email address from the one linked to your Zapier account.

Click “Allow” or “Always allow” for actions.zapier.com

‍Upon executing the command, if everything is set up correctly, you should see a confirmation message, and the action will be carried out.

Check the inbox of the email address you used in your prompt – you should find the ‘Custom GPT’ email sent from your Gmail account, signifying a successful integration and automation using GPT and Zapier.

Conclusion

In conclusion, integrating GPT actions with automation tools like Zapier opens a world of efficiency and productivity.

By following the simple steps outlined in this guide, you can easily automate various tasks using GPT, from sending emails to managing data across different apps.

This process not only enhances the capabilities of your GPT but also saves valuable time and effort.

As you become more familiar with GPT actions and Zapier’s vast range of integrations, the possibilities for automation are nearly endless.

So, start experimenting and discover the full potential of your GPT with automation today!

What is Generative AI?

Artificial intelligence is basically giving computers cognitive intelligence, training them enough so that they can perform certain tasks without the need for human intervention.

Generative AI deals with texts, audio, videos, and images. The computers can build a pattern based on the given input and ‘generate’ similar texts, audio, images, and much more based on the input provided to the AI.

Input is given to the computer, in either of the mentioned forms above, and the computer generates more content.

There are various techniques to achieve this:

• Generative adversarial networks (GANs)
• Transformers
• Variational auto-encoders

Generative AI techniques

Generative Adversarial Networks (GANs)

GANs are ideally a machine learning framework that puts two neural networks against each other called a Generator and a Discriminator. A training set is given to the framework, which allows AI to generate new content. The generator generates new data according to the source data and the discriminator compares the newly generated data and the source data in order to resemble the generated data as near as possible.

Transformer

A transformer model is a neural network that tracks relations in the sequential data and understands the context and meaning of the data like words in a sentence. It measures the significance of the input data, understands the source language or image, and generates the data from massive data sets. Examples of transformers can be GPT-3 by OpenAI and LaMDA by Google.

Variational auto-encoders

As the name suggests, they automatically encode and decode the data. The encoder encodes the source data into a compressed file and the decoder decodes it to the original format. Auto-encoders are present in artificial neural networks, which encode the data. If these autoencoders are trained properly, the encoder at each iteration would compare the data with the source data, and tries to match the perfect output. The decoder then decodes the compressed data to show the output

Applications of Generative AI

Generating photographs

Generative AI can be used to produce real-looking images. These images are popularly known as deep fakes.

Search services

Generative AI can be used to give internet surfers a whole new experience. It has the capability of text-to-image conversion. It can produce deep fakes from the textual description given.

Medical & healthcare

Semantic image conversion: Generative AI finds a great use case in the medical field. It can be used to convert semantic images into realistic images.

Benefits of Generative AI

Future of Generative AI

Generative AI is an artificial intelligence field that is still in development and has enormous potential for a wide range of applications. Computers are able to generate content from a specific input, generate medical images, and much more.

By 2025, Generative AI will account for nearly 10% of all the data produced. And the fact that “Data is the new fuel” makes generative AI a superpower for data-intensive businesses.

Looking at the whole AI industry, the forecasted annual growth between 2020 and 2027 is estimated at around 33.3%.

Source: Generative AI: Real-like content produced by AI (seaflux.tech)