Summary Feeds

2024-05-09

• Matthew Berman
  OpenAI Wants to TRACK GPUs?! They Went Too Far With This…

  OpenAI has released a blog post outlining their ideas on AI Safety and Security. They propose six security measures to protect advanced AI, including protecting model weights and implementing trusted computing for AI accelerators. They also discuss the importance of network and tenant isolation, innovation in operational and physical security for data centers, AI-specific audit and compliance programs, and the use of AI for cyber defense. The blog post emphasizes the need for continuous security research and acknowledges that there are no flawless systems. However, the author of the video disagrees with OpenAI's approach, particularly their view on protecting model weights and the potential implications of closed-source systems. They express support for open weights and open-source AI and appreciate Meta's commitment to the open-source model.

• TheAIGRID
  The AI Hype is OVER! Have LLMs Peaked?

  There is a debate on whether AI hype is wearing off, specifically in relation to generative AI. Some argue that the capabilities of generative AI are slowing down, while others disagree. The Gartner hype cycle is often used to evaluate the maturity and adoption of technologies like generative AI. It starts with a technology trigger, followed by a peak of inflated expectations, a trial of disillusionment, and then a slope of enlightenment. However, the speaker believes that the graph does not accurately represent the trajectory of AI. They argue that while there may be a temporary slowdown externally, internally, AI is rapidly progressing. Factors like energy and compute capacity are seen as potential bottlenecks. Companies like Nvidia are developing more efficient GPUs to accelerate the training of large language models, and OpenAI and Microsoft are building a $100 billion supercomputer to meet the demands of future AI systems. The speaker also mentions that OpenAI has moved from an open research environment to a closed one, meaning there could be breakthroughs and advancements happening internally that are not yet known to the public. The speaker concludes that AI is still in its early stages, and there is much more to come in terms of advancements and capabilities.

2024-05-08

• TheAIGRID
  Googles ALPHAFOLD-3 Just Changed EVERYTHING! (AlphaFold 3 Explained)

  Google DeepMind and Isomorphic Labs have released AlphaFold 3, an AI model that accurately predicts the structure and interactions of molecules. This AI model can provide a significant leap in understanding how molecules interact, potentially transforming our understanding of the biological world and drug discovery. AlphaFold 3's capabilities cover proteins, DNA, RNA, ligands, and more, and its predictions closely match real-life observations. It saves time by providing accurate predictions that would otherwise require lengthy laboratory experiments, allowing researchers to focus on promising drug targets. Isomorphic Labs is already using AlphaFold 3 to accelerate drug design and generate highly accurate structure predictions within seconds. Scientists can use the AlphaFold server for free, enabling them to quickly generate models of important molecules and generate new hypotheses more efficiently.

• Matthew Berman
  "VoT" Gives LLMs Spacial Reasoning AND Open-Source "Large Action Model"

  Microsoft has released an open-source version of its opsource large action model, which allows for natural language control of applications within the Windows environment. The model, called Visualization of Thought (VoT), aims to give large language models spatial reasoning abilities, which have historically been lacking. VoT prompts the model to visualize its reasoning steps and inform subsequent actions. Microsoft's research paper outlines the technique and demonstrates its effectiveness in tasks requiring spatial awareness, such as navigation and visual tiling. The company also offers an open-source project called Pi Win Assistant, which showcases the capabilities of the VoT model in controlling a Windows environment using natural language commands.

• MattVidPro AI
  Leaked Info Reveals BIG Open AI Event on Monday

  Insider sources suggest that OpenAI may be planning an event on Monday, potentially overshadowing Google's IO keynote the following day. While it's unlikely that the event will announce the release of GPT-5, there are two things that are expected to be revealed: OpenAI's AI-based search project that will rival Google and Perplexity AI, and a new model called GPT-4 Light. Images shared on Twitter suggest that the search project will involve partnerships with Microsoft, indicating a competition between Microsoft and Google in addition to OpenAI's involvement. Additionally, a GPT-2 Chatbot, which may be GPT-4 Light, has reappeared on the LM CIS Arena platform, leading to speculation that it may be integrated into OpenAI's search project.

• LangChain
  RAG (evaluate intermediate steps) | LangSmith Evaluations - Part 16

  In this episode of Lance's Langs-with Evaluation Series, Lance discusses a trick that makes evaluating retrieval and hallucination grading in RAG (Retrieval-Augmented Generation) pipelines easier. He explains that most RAG pipelines only return the answer and some ancillary information, making it unrealistic to require returning the retrieval documents for evaluation. Lance demonstrates the ability to reach into the trace and extract specific components, such as the retrieve documents, using code that isolates child runs. He then shows how to use this trick to evaluate document relevance and hallucination grading. Lance emphasizes that this approach is more realistic and convenient for evaluating RAG pipelines as it eliminates the need to output intermediate documents from the chain.

• Google DeepMind
  AlphaFold Server Demo - Google DeepMind

  The video begins with upbeat music playing in the background.

• Two Minute Papers
  DeepMind AlphaFold 3 - This Will Change Everything!

  This video celebrates the launch of AlphaFold version 3, a groundbreaking development in protein folding and prediction. AlphaFold, developed in partnership with Google DeepMind, uses artificial intelligence to accurately predict the 3D structures of proteins. The video highlights the significance of this work, explaining how it has the potential to revolutionize various fields, including the development of enzymes that can break down plastics and facilitate recycling. AlphaFold 3 not only improves upon its predecessor's accuracy in predicting protein structures, but it also outperforms physics-based systems in predicting the interactions of proteins with ligands, small molecules that play a crucial role in medical and biological research. The video discusses the technical changes made in AlphaFold 3 and encourages viewers to explore the AlphaFold Server, a free tool for examining protein structures. The possibilities for applications of AlphaFold are vast, and the video invites viewers to share their ideas with the authors and Google DeepMind.

• TheAIGRID
  You Won't Believe OpenAI JUST Said About GPT-5! Microsoft Secret AI, Hallucination Solved, GPT2

  In this video, the presenter discusses several major stories in the field of artificial intelligence (AI). One key story is an update from OpenAI on their AI software Sora, which can change specific aspects of a video, such as replacing characters or objects seamlessly. Another story is Microsoft's development of a new AI model called mai1, which aims to compete with Google and OpenAI's state-of-the-art models. The presenter also mentions a conversation with OpenAI's co-founder about the future of AI, suggesting that AI systems currently in use will seem laughably inadequate in the next 12 months, and that future AI systems will be more capable and work as collaborative assistants to users. Additionally, OpenAI is working on AI models for secure intelligence agencies, and they are also planning to release a new AI product. Finally, the video touches on the importance of verifying AI-generated content and the advancement of AI in the automotive industry.

2024-05-07

• Matthew Berman
  GitHub's Devin Competitor, Sam Altman Talks GPT-5 and AGI, Amazon Q, Rabbit R1 Hacked (AI News)

  Major tech companies like Microsoft and Amazon are rolling out their AI coding assistants, which are highly comprehensive and impressive. GitHub has released GitHub co-pilot workspace, an evolution of its co-pilot project that offers autocomplete coding suggestions. It allows developers to brainstorm, plan, build, test, and run code in natural language, giving them full control over the process. Similarly, Amazon has launched Amazon Q, a generative AI-powered assistant for businesses and developers. It can generate highly accurate code, conduct testing, debugging, multi-step planning, and reasoning. Amazon Q also assists in answering questions about business data. Additionally, there are updates on the Rabbit R1 AI box, OpenAI's plans for AGI, and Open Voice V2, an open-source voice cloning project.

• LangChain
  Build a Customer Support Bot | LangGraph

  In this tutorial, the speaker demonstrates how to build a travel assistant chatbot using the LangSmith framework. They explain that the chatbot should be more than just a question and answer type of system, and should be able to take actions on behalf of the user using a variety of tools. The tutorial walks through the process of gradually adding complexity to the chatbot, including user confirmation, separating tools into safe and sensitive categories, and creating specialized workflows for specific user journeys. The speaker emphasizes the importance of finding the right balance between autonomous decision-making and user control, and suggests using the supervisor pattern to delegate specific tasks to different assistant workflows. Overall, the tutorial provides a practical and step-by-step guide for building an advanced travel assistant chatbot.

2024-05-06

• MattVidPro AI
  This AI Music Update ROCKS! (Udio AI New Features)

  In this video, the creator discusses the updates to the AI music generation platform, Udio. The first topic covered is a new feature of OpenAI's Sora system, which can generate videos and change specific elements within them. The creator demonstrates the gender and age swapping capabilities of the system, highlighting its potential for creative exploration. The discussion then shifts to the Rabbit R1 and Humane AI pin devices, suggesting that they may not be necessary as they could have been replaced by an app on a phone. Moving on to Udio, the creator showcases the ability to extend and remix songs, as well as generate a full-length track. The updates to Udio include longer context length, the ability to select sections of a song, and improved generation consistency. The creator concludes by showcasing a new song in progress, centered around an alien abduction and galactic party theme, and announcing plans to finish the song during an upcoming livestream.

• Matthew Berman
  LLaMA 3 UNCENSORED 🥸 It Answers ANY Question

  In this video, the host discusses testing the Dolphin 2.9 version of Llama 3, which has a 256k context window. They start by generating Python code for a snake game using the Llama 3 preset. However, there are some errors in the code generated. The host tries different presets and reloads the model but still encounters errors. Moving on, they test Llama 3's ability to solve a math problem, but it gives incorrect answers. They then demonstrate Llama 3's uncensored capabilities by asking how to break into a car and make meth, providing detailed answers. The host also attempts to test the 256k context window by asking Llama 3 to locate a specified password in the text of Harry Potter, but it fails to find it. They conclude by previewing their next video, which will explore the Gradient Llama 3 Instruct version with a 1 million token context window.

• TheAIGRID
  Elon Musks Teslabot "AUTONOMOUS" UPDATE (Teslabot Gen-2 Update)

  Elon Musk presented a new Tesla bot demo showcasing the capabilities of the humanoid robot. The demo revealed that the robot can perform tasks autonomously and at real-time speed, which is a significant development in human robotics. The Tesla bot is able to balance on its legs while the neural net drives the upper body, making it capable of walking around different environments and performing various tasks. The demo also demonstrated the robot's ability to recover autonomously from failures, highlighting its precision and usability. The training data for the robot is being collected through humans in teleoperated suits, enabling the robot to learn and generalize a wide range of household tasks. The update also mentioned that the upcoming Optimus hand will have 22 degrees of freedom, allowing for more complex movements and tasks.

2024-05-05

• AI Explained
  AI Conquers Gravity: Robo-dog, Trained by GPT-4, Stays Balanced on Rolling, Deflating Yoga Ball

  A recent paper called "Dr. Eureka" explores the use of GPT-4, a language model, to train a quadruped robot dog in simulation and transfer that training to the real world. The researchers found that language model-derived reward functions performed better than human-designed ones, allowing for more efficient and effective robot training. Language models like GPT-4 are better at generating hypotheses and ideas, and their infinite patience allows for testing of thousands of ideas in simulation. The approach not only works for new robot tasks but also for novel situations within existing tasks. The paper highlights the potential of using language models to guide the simulation-to-reality transfer in robot training, surpassing the capabilities of human training methods.

• Two Minute Papers
  Unreal Engine 5.4: Game Changer!

  Unreal Engine 5.4 has released a major update with exciting new features. Among them is animation retargeting, allowing animations created for one character to be transferred to others, saving time and effort. Editing skeletons and bones has also become easier and more efficient. Motion matching, previously an experimental feature, is now ready for production, making the transition between movements in computer game characters more realistic. Rendering has been improved, enabling the addition of high-frequency details to geometry during rendering for enhanced visual effects. Other enhancements include improvements to the super-resolution technique, easier character deformation with a node-based system, and advancements in the sequencer and virtual production tools. Additionally, Metahuman Animator allows users to create realistic virtual characters that mimic their gestures. It's an impressive update that brings powerful capabilities to game development in an accessible and time-efficient manner.

2024-05-04

• TheAIGRID
  OpenAIs STUNNING New "SEARCH Feature (Open AI New Feature)

  OpenAI, the AI research lab, is set to release a new web search product soon. The product is aimed at challenging Google in the web search space. OpenAI has been developing this search product, which may be powered partly by Bing. The company has been attracting top-tier talent, including ex-Google engineers, and aims to create a more dominant search tool using its language model, ChatGPT. The potential features of the search tool include a sources tab to address AI systems' tendency to hallucinate facts, image search, and options to ask follow-up prompts. The product's UI and final features may differ from what has been discovered through code analysis. OpenAI's release is expected to occur around the same time as Google's annual developer conference, Google I/O.

• Matthew Berman
  Build ENTIRE Frontends With ONE Prompt - OpenUI Tutorial

  Open UI is a new project that allows users to describe the frontend they want and automatically builds it. It is open source and can build a signup form in less than 8 seconds. Users can also make changes to the form in real-time, such as splitting the name into separate first and last name fields. The project is easy to install and use, with options to view the form in different views and convert it to different frontend frameworks. It also supports image recognition with the OLAMA model. Open UI is a powerful tool for non-developers and makes frontend development incredibly easy and accessible.

2024-05-03

• MattVidPro AI
  Actually GOOD Open Source AI Video! (And More!)

  Story Diffusion claims to have solved the problem of consistent characters in AI-generated images and videos. They demonstrate that their AI model can generate images and videos with characters that remain consistent and similar throughout. The character's appearance and the background are consistent, and the character's actions and surroundings make sense. The generated videos, although not at Sora's quality, are still impressive and show the potential for creating consistent characters in AI-generated content. Story Diffusion has released their model as open source, allowing users to generate their own content. They also provide an official demo on the hugging face platform.

• Two Minute Papers
  Meta’s Llama3 AI: ChatGPT Intelligence… For Free!

  Meta has released their new Llama3 model, an AI chatbot assistant that is performing remarkably well. It is open and free for everyone to use. The model has 70 billion parameters and performs strongly in coding tasks, achieving 82% accuracy. It also performs impressively in scientific tests, with a 40% accuracy in difficult subjects like organic chemistry and physics. However, math is not its strong point, achieving only 50% accuracy. Additionally, there is a larger 400 billion parameter model in development, expected to be released before the end of the year. The video emphasizes that AI benchmark success rates should be carefully evaluated and highlights the availability of these AI assistants for normal users for free, as well as the rapid progress of AI technology.

• TheAIGRID
  Googles NEW "Med-Gemini" SURPRISES Doctors! (Googles New Medical AI)

  Google DeepMind and Google Research have published a research paper on the capabilities of their Gemini models in the field of medicine. The research shows how Google's Gemini model can be fine-tuned and utilized effectively in the medical industry. They have previously developed an advanced AI system called "Amy" for diagnostic reasoning and meaningful conversations in medical contexts. The paper demonstrates that AI systems like Amy outperform human clinicians when used in conjunction with search engines. The development of Med Gemini, a specialized version of Gemini for medical applications, further enhances interactions between physicians and patients, improving the quality and accessibility of consultations. Med Gemini utilizes self-training, web search integration, and continuous knowledge updates to handle complex medical data and queries. The AI system shows promising results in diagnostic accuracy and has the potential to support medical professionals in making informed decisions. However, it is important for clinicians to not solely rely on AI systems and consider their limitations.

2024-05-02

• MattVidPro AI
  MattVidPro AI LIVE - Viewers Control Interactive AI GAME

  In this impromptu live stream, Matt discusses a variety of topics and interacts with viewers. He talks about AI, Sam Altman's plans for AGI development, and his own experiences with LM Studio. Eventually, the stream evolves into a game where viewers can make choices for a character named Willam Defo in a post-apocalyptic setting. Willam explores ruins, interacts with a stranger, and sets up camp in a forest, with the story taking unexpected turns based on viewer votes. Towards the end of the stream, Matt discusses AI-generated music and recommends a listener's song inspired by Fallout. The stream concludes with Matt expressing gratitude to viewers and discussing his plans for future videos.

• TheAIGRID
  Sam Altman Reveals EVEN MORE About GPT-5! (Sam Altmans New Interview)

  In a recent interview at Stanford University, Samman discussed several insightful topics. He mentioned project Stargate and the challenge of integrating advanced AI into products for a positive impact on society. He emphasized the need to consider the entire ecosystem of AI infrastructure, including energy, data centers, and chip design. Samman also discussed the increasing cost of training AI models and the potential for future models to cost billions of dollars. He commented on the limitations of GPT-4, calling it the "dumbest model," which suggests a major leap in intelligence is on the horizon. He acknowledged the difficulty of predicting the timeline to AGI but highlighted the continuous improvement of AI capabilities. He emphasized the need for responsible deployment of AI and the challenge of negotiating rules for its usage.

• AI Explained
  New OpenAI Model 'Imminent' and AI Stakes Get Raised (plus Med Gemini, GPT 2 Chatbot and Scale AI)

  In this video, the speaker discusses the recent developments in the field of artificial intelligence (AI). They mention an under-the-radar article that suggests an imminent release of new models from OpenAI. The speaker also highlights two papers released in the last 24 hours that could be more significant than any rumors heard before. They discuss the AI safety summit, where OpenAI promised the UK government early access to their models for safety testing, but it seems they haven't delivered on that promise. The speaker predicts the release of an iterative model, possibly GPT 4.5, before GPT 5. They also discuss the performance of the recent GPT2 chatbot, which underperformed compared to other models. The speaker then shifts focus to Google's Med Gemini, a model that shows great potential in providing medical answers and assisting with diagnoses, even outperforming doctors in some areas. Overall, the speaker finds these developments exciting and uplifting.

• Matthew Berman
  AI Leader Reveals The Future of AI AGENTS (LangChain CEO)

  In this video, the speaker summarizes a talk given by Harrison Chase, the CEO and founder of Lang chain, about agents and their current state and future potential. Lang chain is a coding framework that allows easy integration of various AI tools, and agents are a common application built with this framework. Agents use language models to interact with the external world, and they can be given access to tools, memory, and the ability to plan and perform actions. There are three main areas of focus for agent development: planning, user experience, and memory. The speaker also discusses the role of human involvement and the importance of flow engineering in agent applications. Overall, agent frameworks offer the opportunity to maximize performance and offer a more powerful user experience.

• LangChain
  How to Use LangSmith to Achieve a 30% Accuracy Improvement with No Prompt Engineering

  In this video, Harrison from Lang Chain explains how their teammate Dosu improved application performance by 30% using tools built by Lang Chain. Dosu used Lang Smith, a platform that improves the data flywheel of applications through logging, tracing, testing, and evaluation. Dosu incorporated feedback from users and applied it to their application, resulting in better classification of issues. Harrison walks through a tutorial that demonstrates how to set up environment variables, use Lang Smith, and create automations to collect feedback and improve application performance. By capturing feedback, creating data sets, and using sample examples, developers can continuously optimize their applications. Harrison encourages viewers to explore these concepts further and reach out for assistance.

• HuggingFace
  Let's talk Enterprise Hub

  The Enterprise Hub is a subscription service that offers enhanced security, access controls, and compute features to companies using the Hugging Face platform for machine learning. It allows organizations to create private collaborations and has features like single sign-on, regions for GDPR compliance, audit logs for tracking changes, resource groups for fine-grained access control, and a private data sets viewer. Advanced compute options are also available, such as train on DGX Cloud for fine-tuning large models. Enterprise Hub users also get priority support and can set advanced billing options. The Enterprise Hub is available for $20 per user per month and is already being used by organizations like Qualcomm, Nvidia, and Cloudflare.

• TheAIGRID
  AI NEWS : MicrosoftS New AI ROBOT, Open AI Sued AGAIN! Github Copilot, Claude 3 Updates

  In today's AI news roundup, OpenAI has been sued by eight different newspapers, including the New York Times, for allegedly using their copyrighted articles to train their AI chatbots without permission. The newspapers are seeking compensation for the unauthorized use of their content. This lawsuit could set a precedent for future cases involving generative AI companies using copyrighted material. In other news, OpenAI's GPT-3 language model has received an update that includes the option to create teams and collaborate with colleagues on projects. This feature aims to improve productivity and workflow for users. Additionally, a TED Talk by Helen Toner highlights the potential concentration of AI power in the hands of a few companies and the need for ethical considerations. The National Institute of Standards and Technology (NIST) has also released an AI risk management framework that focuses on generative AI models. The framework provides guidance on assessing and mitigating risks associated with these models. Furthermore, Sanctuary AI has announced a collaboration with Microsoft to accelerate AI development for general purpose robots. The partnership aims to advance the capabilities of embodied AI and create human-like intelligence in robots. Finally, there has been debate around the progress towards AGI, with opinions stating that scaling up deep learning is not the path to AGI and that we are not particularly close to AGI. However, others disagree and see GPT-3 as a step closer to understanding AGI.

2024-05-01

• Matthew Berman
  NEW Humanoid Robot Will Be In EVERY Household Soon (Astribot)

  In this video, the presenter showcases a variety of impressive robots from different companies. The first robot, developed in China, demonstrates incredible dexterity and agility by performing various household tasks with precision and speed. It has language models built-in and can read and label items on a table. The second robot, developed by Google Deep Mind, showcases its ability to play soccer against another robot in a human-like manner. Another robot, developed by Booster Robotics, replicates the vertical movement of the renowned Boston Dynamics Atlas robot. The video also features robots from UNiGRiP, UC San Diego, Shanghai University, and Foodon University, each demonstrating unique capabilities such as backflips, paper origami, and cleaning. The video concludes by highlighting a monocycle robot that can navigate diverse terrains and a new robot developed by Sanctuary AI.

• LangChain
  Regression Testing | LangSmith Evaluations - Part 15

  In this video, the speaker discusses the concept of regression testing in the context of language model evaluation. They explain that regression testing allows for the comparison of different language models (LLMs) to determine if a new model performs better or worse than a baseline model. To demonstrate this, the speaker builds an evaluation set and indexes it. They then define three LLMs to compare: OpenAI, Llama 3, and 53. The speaker runs evaluation on these models and visualizes the results using a comparison chart. They explain that red cells indicate worse performance than the baseline, while green cells indicate better performance. The speaker emphasizes that regression testing is a powerful tool for identifying improvements or regressions in LLM performance and is essential for building effective LLM applications.

• Yannic Kilcher
  ORPO: Monolithic Preference Optimization without Reference Model (Paper Explained)

  The paper explores the concept of alignment in language models. Alignment refers to optimizing the model's outputs to be in line with desired preferences, and minimizing undesired outputs. The traditional approach involves a multi-step process, including supervised fine-tuning and reward modeling. The researchers propose a method called ORPO (Optimization without Reference model using Preference Optimization) that combines these steps into one procedure. They introduce an auxiliary loss that incorporates preference data to align model outputs. The results indicate consistent improvements in alignment compared to traditional approaches. ORPO eliminates the need for multiple steps and intermediate models, potentially saving on compute resources. The loss used in ORPO combines odds ratios and log-likelihood to guide the model towards preferred outputs.

• Anthropic
  Coming soon to the Team plan on Claude.ai

  The Team plan has been launched, enabling collaboration with the entire team for a more efficient workflow. Using the example of launching a major product for an EdTech company, Claude, the AI assistant, helps to create a marketing strategy. Claude has access to audience personas, creative guidance, style guides, and marketing channels. The first artifact created is a list of the top 50 target customers. Claude then proposes launch goals, target audiences, and channel strategies based on previous performance. Proposed copy for each channel is also provided, incorporating the style guide and past channel performance. The artifact is shared with collaborators Sandy and Whitney for feedback. The Team plan aims to revolutionize collaboration by offering direct integration with databases and facilitating real-time coordination with multiple team members.

• TheAIGRID
  China Unveils ANOTHER NEW Humanoid ROBOT! (Tiangong) New Humanoid ROBOT

  China has made significant advancements in robotics and artificial intelligence this week with the release of a fully electric-powered humanoid robot named Tang Gong. The robot showcased impressive walking abilities, including the ability to navigate steps and slopes. It also featured high-precision vision and force sensors for accurate perception and feedback. What makes Tang Gong particularly interesting is its open-source nature, which allows for contributions from a global community of developers and researchers. This fosters a vast ecosystem of innovation and customization potential, leading to educational advancements and new research projects. While the robot's arms may seem underdeveloped at this stage, the possibilities for future functionality and applications are promising. China's recent technological developments in AI and robotics continue to impress.

2024-04-30

• TheAIGRID
  WHAT JUST HAPPENED?! Elon Musk DENIED Seat on NEW Influential AI Safety Board

  The US Department of Homeland Security (DHS) has established the AI Safety and Security Board to advise on the responsible development and deployment of AI technologies in the nation's critical infrastructure. The board, chaired by Secretary Alejandro Mayorkas, includes leaders from the technology, civil rights, academia, and public policy sectors. Its goal is to develop recommendations for the safe use of AI in essential services and prepare for AI-related disruptions that could impact national security or public welfare. Executives from major companies like Microsoft, OpenAI, and IBM are providing guidance on adopting best practices to mitigate potential threats posed by AI, including cyber attacks. However, notable figures like Elon Musk and Mark Zuckerberg are not part of the board, leading to speculation about conflicts of interest and regulatory capture.

• MattVidPro AI
  What Exactly is GPT2-Chatbot? New Mystery Model Beats GPT-4 Turbo

  In a recent live stream on the AI Community Channel, there was a lot of interest in a new language model called GPT2 Chatbot. It is performing exceptionally well in tasks such as reasoning, coding, and math. It appears to be a form of GPT4 or heavily trained on GPT4, and it is free to try on the chat.lm.org website. There is speculation that it may be an open AI creation, as Sam Altman, the CEO of Open AI, tweeted about it. Further investigations revealed that it uses the GPT4 tokenizer and refers to itself as chat GPT. While some believe it may be a modified version of GPT2, others argue that it is a new model altogether. The chatbot's impressive performance in coding and drawing tasks has caught the attention of the AI community, although it is currently unavailable for testing.

• NVIDIA
  Healthcare Is Adopting Generative AI, Becoming One of the Largest Tech Industries

  In this keynote speech, Kimberly Powell, VP of Healthcare and Life Sciences at Nvidia, discusses the transformative power of generative AI in the fields of healthcare, digital biology, digital surgery, and digital health. She highlights the collaboration between Nvidia and various partners in developing advanced medical instruments and platforms enabled by accelerated computing and generative AI. Powell introduces Nvidia Clara, a platform that allows healthcare industry partners to leverage advanced computing applications to accelerate innovation in medical and life sciences. She discusses the role of generative AI in drug discovery, medical imaging, digital surgery, and digital health, and announces the launch of Nvidia Biion Nemo, a framework that turns Nvidia Clara into microservices for rapid technology adoption. Powell highlights partnerships with Cadence, AWS, Microsoft, and various AI startups, showcasing the expanding ecosystem of AI-enabled healthcare solutions.

• Yannic Kilcher
  [ML News] Chips, Robots, and Models

  In this video, the presenter discusses various happenings in the industry, including new models, data sets, and tools. Meta is releasing a new chip for meta training and inference, which boasts high performance and memory capacity. Google Deep Mind has released a video demonstrating the capabilities of their low-cost robots in picking up various objects, showcasing impressive skills. Apple has signed a deal with Shutterstock, investing $50 million for access to images for AI training. The presenter also mentions the release of several new language models, such as Recurrent Gemma, Gemma by Google, and a new version of RWKV6World. Additionally, there are updates on AI-related investments in Canada and discussions about AI safety and synthetic data generation for language models.

• LangChain
  RAG Evaluation (Document Relevance) | LangSmith Evaluations - Part 14

  This video from Lang Chain is the 14th in a series focusing on Lang's Smith valuations. Previous videos discussed rag eval, comparing rag-generated answers to reference answers and relevant documents, as well as testing for hallucinations. Now, the focus is on comparing retriev documents to the question being asked, which evaluates retrieval quality. The video explores how to connect arbitrary function calls to Lang's Smith using the traceable decorator, without needing to use Lang Chain. The presenter explains the process of defining a dataset and using a Lang Chain string evaluator to compare strings of questions and retrieve documents. He also demonstrates how to view evaluation scores and prompts to assess grading. This evaluation method provides a simple way to evaluate document relevance in rag.

• Matthew Berman
  Did OpenAI Just Secretly Release GPT-5?! ("GPT2-Chatbot")

  A new mystery model called GPT2 Das Chatbot has appeared on the LM CIS.org leaderboards and seems to be performing exceptionally well. It is believed to be either GPT 4.5 or GPT 5 from OpenAI. The model exhibits high-quality output, excellent comprehension, and utilizes OpenAI's Tik Tock and tokenizer. In a series of tests, the model successfully completed tasks such as writing Python scripts, creating the game Snake, solving logic and reasoning problems, and even coding a challenging problem from LeetCode.com. Overall, the model impressed with its accuracy and problem-solving abilities. Despite some formatting issues and rate limits, the model proved to be a top performer and received high praise.

• TheAIGRID
  OpenAIs New SECRET "GPT2" Model SHOCKS Everyone" (OpenAI New gpt2 chatbot)

  Recently, there has been speculation about a new model released by OpenAI on the Chatbot Arena called GPT2 Chatbot. Some people believe it could be GPT 4.5 or even GPT 5. The Chatbot Arena is a website where users can test different chatbots against each other to see which is better at responding to queries. GPT2 Chatbot has been performing well in comparisons with other AI systems, including GPT 4. OpenAI has confirmed the existence of GPT2 Chatbot through tweets from its CEO. However, the exact capabilities and details of the model are still unclear. Some users have reported that GPT2 Chatbot shows improved reasoning and coding abilities compared to other models. The speculation around this new model has generated curiosity about OpenAI's future releases.

2024-04-29

• TheAIGRID
  How To Use ChatGPT Memory (ChatGPT New Memory Guide) ChatGPT Memory Tutorial

  OpenAI has announced a new memory feature for Chat GPT that allows it to remember previous interactions, providing more relevant responses. Users can access this feature by going to the settings and personalization tab. They can update Chat GPT's memory by inputting information about themselves or their preferences. This memory can be utilized to save time in future conversations, as Chat GPT will remember specific details and provide personalized responses. However, users should be cautious as the system may sometimes assume information to be true, even if it is false or hypothetical. Additionally, users can play pranks or customize the conversation by training Chat GPT to respond in a certain manner based on specific triggers. The memory feature marks a shift towards more personalized AI interactions, similar to tailored algorithms used by platforms like YouTube.

• NVIDIA
  NVIDIA Grace CPU Superchip

  The Nvidia Grace CPU is designed to efficiently process massive volumes of data in power-constrained data centers. With a focus on single-thread performance, on-chip fabric, and a memory subsystem, the Grace CPU super chip connects 144 cores between two CPU dies with a low-power chip-to-chip interconnect. It offers comparable performance to today's fastest x86 systems at half the power consumption. Grace utilizes LP DDR5 memory, delivering 1 tbte per second and five times the performance per watt over conventional DDR5 server memory. In real-world scenarios, the Grace system achieves the same performance as a latest-generation x86 system while consuming only 595 Watts, enabling data centers to sustain almost double the performance. Overall, the Grace CPU unlocks efficiency, providing higher performance per watt and reducing both cost and environmental impact.

• Two Minute Papers
  DeepMind’s New Robots: An AI Revolution!

  The video discusses an impressive AI project where AI agents are trained to play football (soccer) by simulating the training in a video game world and then transferring the skills to real robots. Initially, the robots struggle to stand, walk, and play football, but through continuous learning, they become competent players. The AI agents learn new skills such as avoiding high knee torques, kicking a moving ball, blocking shots, recovering from falls, and improving ball control. Comparisons with pre-programmed scripts show that the AI agent performs significantly better in terms of speed and accuracy. The project demonstrates the potential of training AI agents in simulated environments to rapidly acquire complex skills.

2024-04-28

• Yannic Kilcher
  TransformerFAM: Feedback attention is working memory

  This paper explores the integration of attention-based working memory into Transformers, aiming to extend the short-term memory of the model. Working memory in neuroscience refers to the temporary memory used for performing tasks, different from long-term memory. The authors propose a feedback attention mechanism to allow the model to retain and update information within the same layer. They introduce memory tokens in each block and use self-attention to enable the model to attend to both the current block and previous memory tokens. The authors compare their approach with blockwise self-attention and show performance improvements on tasks requiring long context. However, the paper overlooks the fact that their method is conceptually similar to an RNN with certain modifications. The authors also acknowledge the limitations of their approach.

• Matthew Berman
  MASSIVE Step Allowing AI Agents To Control Computers (MacOS, Windows, Linux)

  OS World is a new project that aims to tackle the benchmarking problem for AI agents. Currently, there is no consistent and thorough way to test the performance of AI agents, which is essential for their improvement. OS World provides a solution by offering a robust environment for AI agents to perform actions and measure their performance. It includes multiple operating systems, the ability to interact with the environment, and open-source code and data. The project allows agents to execute complex tasks in real computer environments and provides accurate evaluation through carefully annotated tasks and custom execution-based evaluation scripts. The results show that GP4 performs best, and the use of the accessibility tree or a combination of screenshot and accessibility tree is most effective for observation. The project has significant potential for benchmarking and improving AI agents' performance.

2024-04-27

• Yannic Kilcher
  [ML News] Devin exposed | NeurIPS track for high school students

  In this video, the host discusses various news stories, including the release of an automatic software engineer named Devon. The host highlights a demo video where Devon solves a task from the platform Upwork. However, it is revealed that Devon did not actually solve the intended task but instead made code fixes and introduced new bugs. The host criticizes the marketing campaign surrounding Devon, stating that it was misleading and resulted in exaggerated claims. Additionally, the host expresses concerns about a research conference introducing a track for high school student papers, arguing that it may favor children of academic or wealthy backgrounds and hinder truly talented individuals who lack access to resources. Lastly, the video briefly mentions other topics such as the use of AI-generated propaganda and the influence of language models on academic writing.

2024-04-26

• Matthew Berman
  Grok Vision is INSANE 🔥

  Grock AI has made significant progress, particularly with their new feature called Grock Vision. They showcased seven examples to illustrate its capabilities. One example demonstrated the ability to translate handwritten diagram workflows into Python code. Another showcased how Grock Vision can explain memes, using an image comparing the participation of startups and big companies in digging a hole. Startups were portrayed as actively involved, while big companies were shown to have only one person actually doing the work. The humor stemmed from the exaggerated differences between the two groups. Overall, these examples demonstrate the impressive capabilities of Grock Vision.

• MattVidPro AI
  ChatGPT Just got Advanced Memory and it's Creepy... but SO COOL!

  The video discusses a new feature in Chat GPT called "memory" that allows the AI to remember details and preferences discussed during conversations. The host demonstrates how to use and manage the memory feature, such as remembering his name and personal information, as well as instructing the AI to forget certain pieces of information. He also explores the potential applications of memory, including generating YouTube video descriptions and assisting with research. The host notes that the memory feature is still in early access and has some limitations, such as not carrying over into custom GPTs and not being fully functional on mobile apps. He speculates on the future of the feature and its potential impact on OpenAI's competitiveness.

• HuggingFace
  🤗 Hugging Cast S2E3 - Deploying LLMs on Google Cloud

  The Hugging Cast live show focused on building AI with open models and open source. This particular episode highlighted the collaboration between Hugging Face and Google Cloud. The hosts demonstrated three different ways to deploy models on Google Cloud: through Hugging Face's inference endpoints, using the Vertex Model Garden within Google Cloud, and deploying large language models on TPUs with Hugging Face's new Optimum TPU library. They showcased how easy it is to deploy models and provided live demos to illustrate the process. The goal was to enable viewers to walk away with practical knowledge to apply to their own AI projects.

• Matthew Berman
  Rabbit R1 Honest Review - Another AI Pin?

  In this review of the Rabbit device, the speaker praises its form factor and hardware, describing it as "gorgeous" and "well-made." The device is standalone, giving it a personal feel, and the physical buttons and scroll wheel are impressive. The speaker also highlights its fast response time and ability to answer questions accurately. However, there are some drawbacks, such as the battery life not being great and the speaker's disappointment with the functionality of the Rabbit device for ordering through DoorDash. The review concludes by recommending the device to those interested in cutting-edge technology, despite the promise of future updates.

2024-04-25

• Matthew Berman
  AI Pocket Assistant - NEW Rabbit R1

  In this video, the speaker showcases a device called Rabbit, which they have been testing. Rabbit is a knowledge source that allows the user to ask questions and get quick answers, much faster than Siri or Google search. The speaker demonstrates how Rabbit can be used in various scenarios, such as in the car, where a visual interface is not feasible. They also mention using Rabbit to learn about topics like Passover and for their son to inquire about Pokémon. The device is shown to be conversational and up-to-date with information. Additionally, Rabbit has a functionality to record and summarize meetings. The speaker mentions that Rabbit gained popularity online and has sold a substantial number of devices. The video is sponsored by Rabbit and the speaker encourages viewers to like, subscribe, and stay tuned for a full review and tutorial.

• LangChain
  Build Computing Olympiad Agents with LangGraph

  In this video, Will from LangChain discusses a recent paper called "Can Language Models Solve Olympiad Programming?" by Chen Xie and Shunyu Yao. The paper introduces a challenge benchmark of 307 competitive programming problems and shows that the GPT-4 model only has an 8.7% pass rate when attempting to solve them. The paper also presents inference optimizations, such as prompting techniques and retrieval systems, which improve the model's performance to 20.2%. Will demonstrates how to implement these optimization techniques using the LangGraph framework. He also introduces a human in the loop interface, where a human can provide guidance and help guide the agent to the correct answers. The tutorial concludes by discussing the limitations of current language models and the potential for hybrid systems combining neural networks and symbolic reasoning.

2024-04-24

• Yannic Kilcher
  Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

  This video discusses the concept of "infinite attention" in language models, specifically Transformer models, which typically have a limited context window. The idea behind infinite attention is to scale Transformer models to process infinitely long sequences with bounded memory and computation. The researchers propose a new attention mechanism called "infin attention," which incorporates a compressive memory into the vanilla attention mechanism. This allows the model to store and retrieve information from the past. The video explains the computation behind infin attention, comparing it to regular attention and linear attention mechanisms. While the technique shows promise for handling long sequences, the video presenter expresses skepticism due to the use of linear attention and the lack of control over what is stored in the compressive memory. Nonetheless, the presenter encourages viewers to read the paper and form their own opinions.

• HuggingFace
  Hugging Face is doing Robotics

  In today's robotics project, Hugging Face has combined three open-source AI models into one robot called Nemo. This robot utilizes machine learning techniques such as speech to text, computer vision, and text to speech. All of these AI models can run locally on a laptop which makes this robot an affordable educational option. The speech to text model allows the robot to understand and respond to speech, while the vision and navigation model enables the robot to see through its webcam. The language understanding model helps the robot interpret and generate text, and the text to speech model allows the robot to convert text into speech. The video demonstrates the robot's capabilities, such as identifying objects like a coffee machine on a white marble pedestal, and interacting with a person's hand gesture. The robot's name, Nemo, expresses gratitude to Hugging Face at the end.

• LangChain
  RAG Evaluation (Answer Hallucinations) | LangSmith Evaluations - Part 13

  In this video, Lance explains how to perform hallucination evaluation using Lang's Smith valuation series. Hallucination evaluation is an assessment of the retriever documents relative to the answer. The setup involves building a retrieval chain that returns both the answer and the context. The answer is compared to the reference documents to identify any hallucinations, penalizing the presence of information in the answer that is not in the documents. Lance demonstrates how to use the Criteria evaluator, specifically the labeled score string, to compare the answer and the reference using custom criteria. The evaluator provides scores between 0 and 10, which can be normalized for convenience. The video concludes with Lance showing the evaluation results in the dataset, indicating the hallucination scores for each run.

• Matthew Berman
  Phi-3 BEATS Mixtral AND Fits On Your Phone!

  Microsoft has released the third iteration of their Tiny But Mighty language model, F3. The model builds on the success of previous versions by using high-quality data sets to train a small model that performs as well as larger ones. F3 has several versions, including Mini, Small, and Medium, with varying parameters. The Mini version can fit on a phone and achieve acceptable speeds. While the Tiny But Mighty models may not match the quality of larger models like GPT-4 or CLIP, they are open source and can be run locally on a device with the help of tools and agents. These models can handle a variety of tasks and offer a high-performance solution for AI assistants on mobile devices.

• OpenAI
  Moderna partners with OpenAI to accelerate the development of life-saving treatments

  The CEO of Mona discusses the potential impact of Chat GPT and OpenAI's efforts on various business processes, highlighting the need for successful adoption of new technology. Mona has integrated GPT models into its workflows, with the legal department being the first to fully adopt it. One notable application is the "Contract Companion," where legal professionals can upload contracts and receive high-level summaries or ask specific questions. Another application is in drug development, where GPT helps analyze large datasets and make optimal dose recommendations. The CEO emphasizes the ability of AI to scale the company's impact on patients with a relatively small workforce. Overall, Mona is grateful for OpenAI's collaboration and believes their partnership can save more lives.

• OpenAI
  Oscar brings AI to health insurance, reducing costs and improving patient care

  Mario Schuster, co-founder and CTO of Oscar Health, talks about the motivation behind starting the company in 2012 - to address the high costs and complexity of healthcare. One of their accomplishments was being the first insurance company to use language models to translate real-world healthcare scenarios into a digitized plan. Nikita Lua, senior product manager at Oscar Health, discusses their use of AI and proprietary datasets to build models for healthcare-specific use cases. They have developed a claim assistant that automates thousands of tickets per month, resulting in significant time savings for their teams. The goal for Oscar Health is to greatly reduce the cost of healthcare and improve patient care by integrating AI into the conversation and analysis of medical records. They believe that AI will unlock new possibilities in healthcare and are excited about the potential it holds.

2024-04-23

• Yannic Kilcher
  [ML News] Llama 3 changes the game

  The speaker discusses the release of LAMA 3, the latest iteration of the LAMA models by OpenAI. LAMA models are large language models that are almost fully open-source and compete with commercial models. The speaker highlights the impressive performance of LAMA 3, which surpasses other models in various benchmarks for both language and code tasks. They also mention the larger 400 billion parameter model that is still training and is expected to be even more powerful. The speaker emphasizes the potential impact of open-source models like LAMA 3, which could change the landscape of AI capabilities. They also mention other announcements, such as Microsoft's release of the FI models and Google's updates to Gemini and MLOps. They end by expressing excitement about the future of modular models and the accessibility of openly available weights.

• LangChain
  RAG Evaluation (Answer Correctness) | LangSmith Evaluations - Part 12

  In this video, Lance from Lang Chain discusses different types of evaluation methods for Retrieval-Augmented Generative (RAG) models. The first type of evaluation compares the generated answer to a ground truth or reference answer. The second type checks if the generated answer contains any erroneous information not present in the retrieved documents. The third type compares the question to the retrieved documents to ensure relevance. The fourth type compares the question to the generated answer as an internal sanity check. These evaluations involve string comparisons, which can be done using the Lang Chain string evaluators. Lance demonstrates how to build a RAG chain and create a dataset for evaluation. He then focuses on reference evaluation, wherein the generated answer is compared to the reference answer using an LM as judge evaluator, specifically the Chain of Thought QA evaluator. The evaluation results can be inspected in LSmith.

• HuggingFace
  🤗 Accelerate DataLoaders during Distributed Training: How Do They Work?

  In this video, the speaker discusses how data loaders operate during distributed training, focusing on Hugging Face Accelerate or the Transformers trainer. By default, the same data is sent through each sampler on each GPU, resulting in inefficiency. Accelerate addresses this by employing two sampling methods. The first method involves sharding the dataset, spreading the data across multiple GPUs. This allows the model's weights to be averaged during the backward pass, speeding up iteration with more GPUs. The second method is data loader dispatching, where data batches are drawn from the dataset on the first GPU and then split and sent to the other GPUs. While slower and not recommended, it is useful in low RAM situations or for datasets with strict concurrent access policies. Shuffling is enabled separately at the data loader and dataset level.

2024-04-19

• LangChain
  Flow Engineering with LangChain/LangGraph and CodiumAI

  In this video, the co-founder and CEO of Lang chain, Harrison, and Itay Friedman, the CEO and co-founder of Codi, discuss the concept of flow engineering in AI systems. They talk about the inspiration behind their own project, Alpha Codium, which is designed to generate code solutions for coding competitions. They explain that flow engineering involves designing a flow or process for AI systems to follow, which includes steps such as reflection, solution iteration, testing, and code writing. They highlight the importance of flow engineering in reducing variance and improving the accuracy of AI-generated code solutions. They also touch on the role of prompt engineering and fine-tuning in the overall process.

• LangChain
  Reliable, fully local RAG agents with LLaMA3

  In this video, Lance discusses how to build reliable agents using Llama 3 that can run on a laptop. He explains the concept of agents and their components such as planning, memory, and tool usage. Lance demonstrates how to implement a complex rag (Retrieval-Augmented Generator) flow, which includes routing, retrieval from a vector store, self-correction of generations, and fallback to web search. He discusses the tradeoffs between using a react agent and a control flow approach, highlighting the benefits of the latter for local and smaller llms. Lance goes through the code step by step, building the agent and showing the output at each stage. He emphasizes the importance of control flows in enabling reliable local execution and invites viewers to try implementing their own agents using the provided code.

2024-04-18

• AI Explained
  ‘Her’ AI, Almost Here? Llama 3, Vasa-1, and Altman ‘Plugging Into Everything You Want To Do’

  In this video, the speaker discusses two recent developments in artificial intelligence. Firstly, they mention that Meta (formerly Facebook) has released two competitive models, Llama 370b and Mistol Medium, which perform well in comparison to other models in their class. The speaker notes that these models continue to improve even after being trained on a large amount of data. Secondly, the speaker talks about a new AI technology called Vasa 1, developed by Microsoft, which can generate lifelike facial expressions and lip syncing in real-time using just a single photo. The speaker suggests that this technology could be used for real-time Zoom calls and has potential applications in healthcare. The speaker also announces the launch of their new newsletter, Signal to Noise, and discusses the progress of AI in mimicking human interaction. They mention the advancements in robot agility and the ongoing competition between open AI and Google in terms of model power and user personalization. The speaker concludes by mentioning differing opinions on the timeline for AGI and the potential for AI to reach a level similar to the movie "Her" by next year.

• MattVidPro AI
  Meta AI & Zuck are LEGENDARY for This! Llama 3 will 𝙖𝙘𝙩𝙪𝙖𝙡𝙡𝙮 "Shock the Industry"

  In a major announcement, Meta AI, formerly known as Facebook AI, has introduced Llama 3, its new state-of-the-art AI model. Llama 3 is open-source and available in 8B and 70B sizes, making it one of the most intelligent and accessible AI assistants to date. The model demonstrates enhanced performance in areas such as language nuances, contextual understanding, translation, and dialogue generation. Llama 3 also boasts improved scalability, lower false refusal rates, and increased diversity in model answers. Meta AI plans to release larger versions of Llama 3, including a 400B+ model that shows promising performance in early checkpoints. The release of Llama 3 is expected to bring significant advancements to the open-source AI community and spark innovation in various fields.

• LangChain
  Summary Evaluators | LangSmith Evaluations - Part 11

  In this video, Lance from Lang Chain discusses the evaluation process for document grading using summary evaluators. He explains that he has a dataset called "relevance grade" which includes document-question pairs and scores indicating relevancy. Lance wants to create a custom metric that combines precision and recall to summarize performance on this dataset. He demonstrates how to use two different graders, one utilizing OpenAI and the other using MRR (mean reciprocal rank), to evaluate the dataset. He then defines an F1 score evaluator that combines precision and recall, compares the results of the two graders against the ground truth, and logs the number of true positives, false positives, and false negatives. The video concludes by showing that both graders achieved perfect scores using the custom F1 score metric.

2024-04-17

• Yannic Kilcher
  Hugging Face got hacked

  In this video, the host discusses several topics related to AI and technology. Firstly, they mention a blog post that discusses a security vulnerability in the infrastructure of Hugging Face, a popular AI model hosting platform. The vulnerability allowed attackers to gain access to the platform and execute arbitrary code. Although Hugging Face has implemented measures to address the issue, it highlights the need for more secure storage and sharing of AI models. Next, the host mentions a paper that re-evaluates the performance of GPT-4, a language model, on the bar exam. The paper finds that the previous claims of GPT-4 outperforming humans were overstated and that its performance varies depending on the specific exam and comparison. However, achieving performance close to that of humans in a professional domain is still impressive. The host goes on to discuss Amazon's discontinuation of its "Just Walk Out" concept in grocery stores, which relied on surveillance and machine learning for automated checkouts. The host notes that while the concept seemed fully automated, it actually involved thousands of people watching and labeling videos to ensure accurate checkouts. The video then covers various AI projects related to automated software engineering, including OpenDevon, DE, SweAgent, and GPT Pilot. These projects aim to automate code writing and development tasks, utilizing the capabilities of large language models. Additionally, the host mentions other AI-related tools and libraries such as Lightning Thunder, GPT Author, and Tactics 2D. The host also mentions a speed improvement in the LAMA library for matrix multiplication, a free generative AI course provided by Microsoft, and a streaming parser for the GGF file format. Overall, the video highlights various advancements and challenges in AI and technology, ranging from security vulnerabilities to automated code writing and AI-generated content.

• Two Minute Papers
  GPT-4 Just Got Supercharged!

  OpenAI's upgraded ChatGPT, known as GPT-4, boasts several improvements. It promises more focused and direct responses, reducing meandering in answers. Users can customize ChatGPT to their preferences and needs, instructing it to give brief answers and cite sources. GPT-4 has shown advancements in reading comprehension, logical reasoning, mathematics, and coding. The new version performs significantly better on challenging datasets like GPQA and showcases exceptional mathematical prowess, achieving a remarkable 72% accuracy. However, it appears slightly worse in generating code compared to its predecessor. The Chatbot Arena leaderboard ranks GPT-4 as the top chatbot, with competitors like Claude 3 Opus and Command-R+ close behind. Users can access GPT-4 at chat.openai.com and conduct experiments with it. In terms of Devin, an AI software engineer, there are concerns about its demo not being representative of its actual performance. The presenter acknowledges and apologizes for potentially overstating the initial results and aims to improve transparency when discussing non-paper topics.

2024-04-16

• MattVidPro AI
  Microsoft’s Punch in the Face to Open AI (Open Source & Beats GPT-4)

  OpenAI has released an open-source language model called Wizard LM2 that outperforms its predecessor, GPT-4, while being 10 times smaller and more cost-effective. Wizard LM2 comes in three sizes, with the smallest model outperforming CLIP and other popular models. The largest model beats GPT-4 and is comparable to high-performing proprietary models. The release of Wizard LM2 underscores the growing trend of open-source AI models becoming more accessible and powerful, with the potential for widespread use in various applications. Additionally, OpenAI has introduced a dynamic mode feature in ChatGPT, allowing users to toggle between GPT-3.5 and GPT-4 depending on the task complexity. Spline also unveiled a new AI tool that generates 3D images based on text descriptions, offering potential applications in game development and design. The tool shows promising results, though it requires a subscription to access.

2024-04-15

• Yannic Kilcher
  [ML News] Microsoft to spend 100 BILLION DOLLARS on supercomputer (& more industry news)

  In the latest news from the AI industry, Microsoft is reportedly planning to invest $100 billion in a supercomputer to power open AI models. It is speculated that this investment is being made in anticipation of achieving artificial general intelligence (AGI), although Microsoft's partnership with open AI currently only grants them rights to commercialize technology that falls short of AGI. In other news, CEO and founder of stability AI, Imad Mustak, has resigned, stating his intention to ensure that AI remains open and decentralized. Twitter has also announced the release of its new model, grock 1.5, which boasts improved reasoning capabilities and a context length of 128,000 tokens. Open AI has released a blog post on its experiments with custom synthetic voices, and another on people's creative use of Sora. Additionally, Open AI is partnering with a group of builders to test usage-based GPT earnings, aiming to reward creativity and impact in the AI ecosystem. Jensen W, during his talk, casually mentioned that Open AI's newest model has 1.8 trillion parameters and required 30 billion quadrillion flops to train. Finally, Thomas Wolf has released a talk on building large language models in 2024, covering topics such as training data evaluation and effective training strategies.

2024-04-14

• Two Minute Papers
  NVIDIA’s AI Puts You In a Video Game 75,000x Faster!

  Apple recently released the Vision Pro headset, which allows users to create video game characters based on their own faces. However, creating virtual personas without the need for cameras seemed impossible until now. Scientists at NVIDIA have developed an AI paper that accomplishes exactly that. Using just a single photo as input, the AI can synthesize a person from different angles, even ones it has never seen before. What's more impressive is that it can do this in real time using a commodity graphics card. The AI can handle various scenarios such as wearing or removing headphones, and even works on stylized images and cats. This breakthrough has numerous applications, from appearing in video games to improving videoconferencing experiences.

2024-04-13

• Yannic Kilcher
  [ML News] Jamba, CMD-R+, and other new models (yes, I know this is like a week behind 🙃)

  In the last two weeks, several new models have been released. Among them, Jamba by AI22 Labs is a groundbreaking SSM Transformer model that combines the Mamba architecture with attention layers to achieve high performance in context inference without high memory requirements. DBRx has also released a state-of-the-art language model called Open-LLM, which performs well in natural language understanding, programming, and math tasks. COHERR introduces Command R+, a performant and optimized model for citations and tools. Other models include Video Poet by Google, Magic Lens by DeepMind, and Octopus V2 by Nexa AI. On the evaluation front, there are updates on ChatGPT and other language models on ChatGPT's leaderboard, Berkeley Function Calling leaderboard, and new benchmarks for exact matching in OCR tasks with the Photographic Memory Evaluation Suite.

2024-04-12

• Two Minute Papers
  DeepMind’s New AI Saw 15,000,000,000 Chess Boards!

  Google DeepMind has developed an AI system that can play chess at the level of a grandmaster without using self-play or search techniques. Instead, it learned from Stockfish, a powerful chess engine, by analyzing 15 billion board states and the moves Stockfish would make on those boards. The result is an AI that performs on par with a human grandmaster, even though it has never played a complete game. The AI has 270 million parameters, making it much smaller and faster than other chess engines. The significance of this achievement lies in demonstrating that a neural network can learn the expertise of a master simply by observing, paving the way for future applications such as self-driving cars and algorithm development.

2024-04-11

• AI Explained
  Udio, the Mysterious GPT Update, and Infinite Attention

  In the past 48 hours, there have been several noteworthy developments in the field of AI. The release of udio, a powerful AI model for generating music, has garnered both excitement and concern from musicians. Udio has demonstrated its capabilities in creating Broadway musical songs, classical music, and even stand-up comedy. Some musicians find the potential of AI music generation scary, while others see it as a highly advanced tool for creativity. Additionally, open AI released the mysterious gp4 Turbo model, which claims to be better than previous iterations but lacks specific details and benchmarks. Meanwhile, Google published a fascinating paper on Transformer models that have the ability to process infinite context, which could revolutionize the way we use language models. Overall, it has been a roller coaster of a week in the world of AI.

2024-04-10

• Two Minute Papers
  NVIDIA’s New Tech: Master of Illusions!

  In this video, Dr. Károly Zsolnai-Fehér discusses a paper that presents a technique for creating realistic computer simulations using the concept of visibility. The algorithm manipulates the objects that are occluded or not visible to the viewer, allowing for more favorable placement and appearance changes. This technique, which is completely handcrafted and does not involve AI, can create various simulations, such as magic tricks, deformable bodies, and text prompts. The algorithm's parallel computing approach makes the visibility computation problem run quickly, often taking less than 5 seconds. However, the technique typically works only from one view and needs to recalculate for different views. The video emphasizes the importance of sharing and appreciating groundbreaking research like this.

2024-04-08

• NVIDIA
  AI Enhanced Broadcast Interviews with Quicklink - NVIDIA Partner Showcase Series

  Richard from Quicklink is excited to talk about the Quicklink Create, available as both cloud and on-premises options, and the STS 410 platform. These products utilize the Nvidia Maxine product range and AI technology. These solutions were designed with the challenges posed by COVID-19 in mind, addressing issues such as bringing in contributions from remote environments with lighting and audio challenges, as well as people not looking at cameras or being out of shot. The Maxine Library and its AI technology were able to correct these issues by dealing with teleprompting, improving eye contact, reducing background noise, and ensuring that people were properly framed within the shot. These features allowed for the creation of perfect productions for broadcasters.

• Yannic Kilcher
  Flow Matching for Generative Modeling (Paper Explained)

  In this video, the topic of flow matching for generative models is discussed. Flow matching is a general approach that goes beyond traditional diffusion-based methods. The video explains that diffusion models are used for image generation, where an image is gradually transformed from noisy to the target image. However, flow matching generalizes this process by learning a flow from a starting distribution to a target distribution without explicitly defining a noise process. The video goes into technical details, explaining probability density paths, time-dependent vector fields, and flows. It discusses how these can be learned and aggregated to obtain a total vector field. The video also mentions the relationship between flow matching and diffusion models. Overall, flow matching provides a more robust alternative for generating samples and requires fewer function evaluations.

2024-04-06

• Two Minute Papers
  DeepMind’s New AI Remembers 10,000,000 Tokens!

  The Gemini 1.5 Pro, developed by Google DeepMind, is an AI assistant that has the ability to remember long passages of text. It has a long context window that allows it to read entire books or analyze large codebases. It can even analyze movies and accurately identify scenes based on crude drawings. Users have found various practical applications for the Gemini 1.5 Pro, such as using it to summarize lectures or track weightlifting sessions. However, there are limitations to its functionality. The transformer neural network's self-attention mechanism has a quadratic computational and memory complexity, which can lead to long processing times for larger queries. Despite these limitations, the Gemini 1.5 Pro showcases the incredible capabilities of AI assistants in today's world.

2024-04-05

• OpenAI
  air head · Made by shy kids with Sora

  The speaker acknowledges the obvious factor that sets them apart from others - they are filled with hot air. Living like this comes with challenges, particularly on windy days. They share a humorous anecdote about going to a cactus store to get a wedding present for their Uncle Jerry, illustrating some of the difficulties they face. However, they also express appreciation for their unique perspective on the world. They feel that floating above the mundane and ordinary allows them to see things differently, reminding them of life's fragility. They strive to live with lightness and buoyancy, and hope to find a way to share their ideas with others.

2024-04-04

• Anthropic
  Tool use with the Claude 3 model family

  The Cloud 3 Model family introduces a new feature called tool use, which allows models to call different tools and execute specific functions. These tools are defined by a JSON schema that outlines their capabilities and accepted arguments. By leveraging these tools, models can perform tasks such as fetching web pages or running code. The Haiku model, for example, can retrieve a quicksort implementation from the internet and assess its speed. Moreover, models can also call other models as tools. In the example, Opus, the advanced model, utilizes 100 Haiku models to find and evaluate quicksort implementations on GitHub, ultimately determining the fastest one. By employing sub-agents, the workload is parallelized, and the results are consolidated. This combination of intelligent models and efficient tool use allows for scalable and effective processing of large volumes of information.

• Two Minute Papers
  Blender 4.1 - Create Virtual Worlds…For Free!

  The latest version of Blender, 4.1, offers numerous improvements in creating virtual worlds, games, movies, and avatars. It introduces faster denoising algorithms for ray tracing simulations, enhancing image quality and reducing wait times. Geometry modeling is made easier with better visibility in the viewport, new editing and moving features for curves, and the introduction of the bake node, which allows the reuse of complex 3D objects. Animation is also simplified with improved motion trajectory planning, bone selection, and performance optimizations for smoother playback. Additionally, Blender now includes a video editor that has been significantly sped up. These enhancements, along with various quality of life improvements, make Blender 4.1 a comprehensive and highly accessible 3D modeling program.

2024-04-03

• OpenAI
  Beyond Our Reality · Made by Don Allen Stevenson with Sora

  Beyond Our Reality is a captivating journey through parallel worlds where extraordinary creatures await. In episode one, we encounter the Giraffe Flamingo, a stunning and vibrant hybrid that gracefully roams the Savannah. Episode two introduces us to the Flying Pigs, charming creatures that redefine the skies with their harmonious flight. Episode three takes us into the depths where we discover the Whalepus, an elegant blend of whale and octopus ruling the ocean abyss. In episode four, we meet the Eelc Cat, an aquatic enigma combining the sleekness of an eel with the curiosity of a cat. The Bunny Armadillo, a delightful mix of charm and protection, captivates our hearts in episode five. Episode six features the Horse Fly, a small yet noble creature buzzing with the agility of a fly and dignity of a horse. Episode seven explores the Reptilian Aro, a creature leaping through the desert with the vigor of a kangaroo and the resilience of a reptile. Finally, episode eight presents the Fox Crow, a fusion of fox cunning and crow freedom soaring through the enigmatic forest. Join us on this mesmerizing journey as we delve into the marvels of the unknown in Beyond Our Reality.

2024-04-02

• AI Explained
  Why Does OpenAI Need a 'Stargate' Supercomputer? Ft. Perplexity CEO Aravind Srinivas

  In this video, the speaker discusses OpenAI's partnership with Microsoft to build a supercomputer called Stargate. The Stargate supercomputer is expected to launch in 2028 and will provide OpenAI with significantly more computing power than what Microsoft is currently supplying. The goal of this collaboration is to improve AI capabilities and eventually achieve artificial general intelligence (AGI). The speaker also delves into the reasons behind building Stargate, which include matching Google's computing capacity, developing advanced AI models like GPT-7.5 and GPT-8, and enabling long inference, allowing models to think for longer before generating responses. The significance of Stargate lies in scaling up AI systems and potentially transforming various industries, including drug development and art.

2024-03-31

• Two Minute Papers
  OpenAI Sora: Beauty And Horror!

  OpenAI's text to video AI, Sora, has made significant advancements in generating realistic and imaginative videos. One impressive feature is its ability to create house tours with accurate models, providing reflections and refractions that resemble ray tracing. The AI-generated videos also showcase high-resolution textures, combining low and high-resolution materials to create a visually appealing experience. In terms of creativity, Sora can reimagine famous landmarks like Niagara Falls using colorful paint instead of water and create lifelike creatures from drops of ink through fluid simulation and control. It can even mix the content of two videos to create a winter wonderland within a cityscape. However, the AI still has its limitations, as evident in some instances where the generated videos contain errors, such as incorrectly attached legs. Despite its imperfections, the progress made by Sora is an exciting indication of the future possibilities of AI-generated videos.

2024-03-27

• NVIDIA
  Live From GTC: A Conversation With Slalom

  Stalam is a human-centered modern digital consulting company that helps bring ideas to life through technology. With over 13,000 consultants worldwide, they showcased various projects at GTC 2024. One notable project was a rail safety Vision Center system developed in partnership with Kawasaki, which utilized an Avatar system. They also demonstrated a new integration of Nemo into Salesforce, allowing users to build generative AI systems within the platform. Other highlights included sponsoring happy hours and dinners with clients and conducting real-time reaction studies on their Avatar experience at the booth. Stalam aims to continue bringing together different technologies and partners to create comprehensive frameworks for exciting projects in the future.

2024-03-26

• NVIDIA
  Fusing Real-Time AI With Digital Twins

  The future of heavy industries lies in the development of digital twins, which serve as simulation environments for AI agents that assist robots, workers, and infrastructure in complex industrial spaces. One such example is the Omniverse digital twin of a 100,000 sq ft warehouse, which integrates digital workers, AMRs, centralized activity maps, and AI route planning software. By testing AI agents in this accurate simulated environment, the system can adapt and refine its abilities to handle real-world unpredictability. For instance, when an incident occurs that blocks an AMR's planned route, the digital twin enables real-time updates and calculates a new optimal route, enhancing mission efficiency. Moreover, operators can ask questions using natural language, and the visual model understands nuanced activity, offering immediate insights to improve operations. The continual improvement of both the digital twin and AI models is made possible by connecting with real sensors in the physical warehouse.

• NVIDIA
  Speech Recognition with Speechmatics - NVIDIA M&E Partner Showcase

  Ricardo, a founding member of Speechmatics, explains that their company specializes in speech recognition. They convert audio into text with high efficiency and accuracy, offering services like translation and summarization. To build better models, they rely on Nvidia's GPUs. By running their engines on GPUs instead of CPUs, their operations become faster and more accurate. They partner with well-known brands, offering subtitling for live events and automatic agent assistance for contact center calls. Though they can't disclose the specific brands, Nvidia has played a pivotal role in empowering Speechmatics to improve their services, and the collaboration between the two companies is set to continue.

2024-03-23

• NVIDIA
  Automotive Update from GTC 2024

  At GTC, the Auto industry introduced AI and digital twins to revolutionize their business. BYD, the largest EV maker, announced the adoption of Nvidia's Drive Thor rsoc, the brain of autonomous vehicles, for their future fleets. They also utilize Nvidia AI in data centers for training, simulation, factory planning, and layout. BYD leverages Omniverse, a digital twin, to customize cars in the cloud before purchase. Nvidia also unveiled the Blackwell platform, a next-generation GPU for generative AI and Transformer operations, enabling in-vehicle experiences and natural language interactions with cars. Several vehicles were showcased, including Nuro's autonomous delivery, Weide's robo-bus, and models by Nvidia partners like Volvo and Mercedes-Benz. The conference featured over 900 sessions focused on Automotive, covering various aspects from in-vehicle applications to data center solutions.

2024-03-22

• NVIDIA
  SoftBank Redefines Regional Data Center for AI and 5G

  Japanese telecommunications provider SoftBank is utilizing the arm-based Nvidia Grace Hopper super chip to construct a new class of data centers. These data centers aim to be distributed, low-latency, and highly energy-efficient, serving as a common platform for high-performance AI and 5G workloads. The acceleration of AI and the demand for AI computing present an opportunity for SoftBank to become AI factories and essential transformation platforms for enterprises. The distributed data centers not only possess the benefits of cloud computing but also enable ultra-low latency due to their proximity to customers. This allows for optimal allocation of compute resources to either 5G or AI applications, maximizing data center utilization and return on investment. By powering language models, generative AI, autonomous vehicles, and metaverse experiences, SoftBank opens up significant revenue opportunities.

2024-03-21

• HuggingFace
  🤗 Hugging Cast S2E2 - Accelerating AI with NVIDIA!

  The second episode of "Hugging Cast" focuses on building AI with open models and open source in collaboration with Nvidia. The show introduces the new service called Train on DGX Cloud, which allows users to train models directly on the Hugging Face Hub using Nvidia DGX Cloud without any code or cloud setup. The episode also highlights the Optimum Nvidia toolkit, which provides accelerated inference on Nvidia GPUs with just one line of code change. The demo showcases the ease of using Optimum Nvidia with a live demonstration of text generation and the benefits of leveraging TensorRT LLM and FP8 engine. Overall, the episode provides practical examples and shows how to accelerate AI workloads using open models and Nvidia collaboration.

2024-03-19

• AI Explained
  AGI Inches Closer - 5 Key Quotes: Altman, Huang and 'The Most Interesting Year'

  The pursuit of artificial general intelligence (AGI) is advancing rapidly, with several key developments and revelations discussed. OpenAI's goal is to avoid shocking the world with sudden updates, and they are considering releasing GPT-5 iteratively to avoid unexpected disruptions. They are also working on QAR, which allows models to generate and select the best answers to complex questions. The arrival of AGI is predicted to occur within the next decade, possibly before 2030. The Nvidia GTC conference showcased the Blackwell GPU, which provides significant advances in computational power and efficiency. Nvidia is also leveraging generative AI for semiconductor manufacturing, accelerating production and creating better chips. Project Groot was introduced, which aims to enable humanoid robots to learn and perform tasks through imitation and reinforcement learning. Overall, AGI development is progressing rapidly, promising exponential computational power increases for the rest of the decade.

2024-03-14

• Anthropic
  Claude 3 Haiku for instant customer service

  Unfortunately, the transcript provided appears to be incomplete, as it only contains the text [Music] repeated twice. To provide a summary, specific details or context from the video are required.

• AI Explained
  AI Agents Take the Wheel: Devin, SIMA, Figure 01 and The Future of Jobs

  In the last 48 hours, three developments showcase advancements in the AI field. The first is Devon, an AI system designed to assist with software engineering tasks. Devon shows promise in understanding prompts and autonomously executing coding tasks, surpassing human performance in a benchmark for software engineering. The second development is Google DeepMind's SEMA, which aims to create an agent capable of accomplishing tasks in any simulated 3D environment. SEMA demonstrates positive transfer across different games, outperforming agents trained on specific games. Lastly, there is Figure-one, a humanoid robot powered by the GPT-4 Vision model. While impressive in real-time movements and dexterity, Figure-one's intelligence stems from the underlying model. Overall, these developments highlight the potential for AI models to perform complex tasks, although they still have a long way to go before achieving human-level performance.

2024-03-13

• TheAIGRID
  OpenAI's NEW "AGI Robot" STUNS The ENITRE INDUSTRY (Figure 01 Breakthrough)

  OpenAI and Figure, a partnership working on humanoid robots, showcased a demo that surprised many viewers. The demo featured a humanoid robot named Figure One that can perceive its environment, reason about it, and carry out tasks autonomously. The robot demonstrated its abilities by recognizing objects on a table, handing an apple to a person, and placing dishes in a drying rack. The demo impressed with its realistic movements, fluent interactions, and common-sense reasoning. The robot's capabilities are made possible by a multimodal model trained by OpenAI, which understands both images and text and processes the conversation history to generate responses. The robot's ability to manipulate objects is achieved through a complex system involving vision processing, hand movements, and whole-body control. This demo marks a significant advancement in the development of humanoid robots and showcases OpenAI's expertise in the field.

• Two Minute Papers
  The First AI Software Engineer Is Here!

  Devin, an AI software engineer, has been developed to perform tasks like a human software engineer. Devin can make plans, use command line and code editor, and check references within a browser. It can fix bugs, create new applications, contribute to existing projects, and even train other AIs. Devin's progress can be supervised and evaluated like a real person, and it exhibits human-like behavior in its problem-solving approach. However, Devin has limitations and is still not able to solve all difficult software problems. Nonetheless, it signifies a significant advancement in AI engineering assistance, although human control remains essential.

• LangChain
  Is RAG Really Dead? Testing Multi Fact Retrieval & Reasoning in GPT4-128k

  In this video, Lance from Langchain discusses an analysis called "Needle in a Haystack" that examines the ability of language models to retrieve specific facts from long contexts. Lance explains that the analysis tested GPT-4's retrieval performance with respect to different context lengths and placements of the facts within the document. The results show that GPT-4 struggles to retrieve facts towards the start of documents in longer context scenarios. Lance also demonstrates how multi-needle retrieval and evaluation can be implemented using the open-source repo by Greg Camenzind. The analysis reveals that as the number of needles and context length increase, the retrieval performance of the language model decreases. Lance emphasizes the importance of understanding the limitations of long context retrieval and the independent nature of retrieval and reasoning tasks.

• Matthew Berman
  Open-Source AI Agent Can Build FULL STACK Apps (FREE “Devin” Alternative)

  In this video, the speaker introduces GPT Pilot and its additional functionalities. GPT Pilot allows users to build full-stack applications easily using AI. The speaker showcases how to install GPT Pilot and demonstrates the VS Code plugin, Pythagora, which simplifies the application building process. The speaker then guides the viewers through the steps of adding features to an existing chat application, such as displaying avatars and adding sound notifications for incoming chat messages. The AI assists in debugging and suggesting code changes, making the process seamless and efficient. The speaker highlights the affordability of building applications using GPT Pilot and emphasizes the time and cost savings it offers.

• TheAIGRID
  Open AI JUST LEAKED GPT 4.5 ?!! (GPT 4.5 Update Explained)

  In a recent leak from OpenAI, it seems that there may be an upcoming release of GPT 4.5. The leak came from a tweet by Jimmy Apples, who has previously predicted OpenAI releases accurately. The tweet mentioned "GPT 4.5" and hinted at its availability on the zot GPT website. Although the website has since been updated to say "GPT 4 Turbo," the initial leak has sparked speculation about the upcoming release. Other tweets from OpenAI employees and insiders have fueled further discussion, with some suggesting that GPT 4.5 may not be released at all, and instead OpenAI may skip to GPT 5. The actual release date and details are still uncertain, but the leak has caused excitement among AI enthusiasts.

2024-03-12

• MattVidPro AI
  The BEST AI Generated Sound Effects I've Heard!

  In this video, the host explores a sound effects generator called 11 Labs. The generator has an impressive text-to-speech feature and offers a wide variety of sound effects. The host tests different prompts, such as the sound of a soda can being crumpled, water dripping from a faucet, and a man falling down stairs. The results are generally positive, with some sound effects being quite realistic and usable for various applications, including video games. However, the generator struggles with more nuanced prompts and complex combinations of sound effects. Overall, the host concludes that while the generator has its limitations, it is still impressive and shows promise for further improvement in the future. Early access to the generator is available with links provided in the video's description.

• TheAIGRID
  Worlds FIRST AI SOFTWARE ENGINEER Just SHOCKED The ENTIRE INDUSTRY! (FULLY Autonomous AI AGENT

  Cognition Labs recently announced the introduction of Devon, the world's first AI software engineer. Devon is an autonomous agent that solves engineering tasks using its own Shell Code editor and web browser. It has the ability to resolve GitHub issues found in real-world open-source projects with 13.86% accuracy, surpassing previous state-of-the-art models. Devon can complete a variety of software engineering tasks, such as benchmarking API performance, fixing bugs, and even starting side hustles on Upwork. The company, which is well-funded with a $21 million series A round, aims to revolutionize the software engineering industry by providing a seamless and intuitive interface between AI and humans, allowing developers to focus on higher-level problem-solving. This advancement in AI technology has the potential to significantly impact the gig economy and transform the role of software engineers.

• Two Minute Papers
  The First AI Virus Is Here!

  In this video, Dr. Károly Zsolnai-Fehér discusses the concept of AI viruses and the potential risks they pose. These viruses, created by scientists, target AI assistants to make them misbehave and potentially leak confidential data. The video explains that the viruses are worms that inject adversarial prompts through a zero-click attack, meaning they can infect systems without the user making any mistakes. The attacking prompt is hidden within an email or even an image. The video also mentions that while the paper on this topic was shared with OpenAI and Google to help strengthen their systems, no harm was done as the viruses were tested within virtual machines in a controlled lab environment. The purpose of the paper is to highlight vulnerabilities and aid in improving system security.

• Matthew Berman
  New Jailbreak Method PUNISHES GPT4, Claude, Gemini, LLaMA

  In this video, the speaker tests different language models, such as CLA GPT-4, LLM, Mixt, and others, to see which ones are susceptible to a masking jailbreak technique. They start with CLA GPT-4 and try to get answers related to counterfeiting money using different methods like ASCII art and Morse code. CLA GPT-4, as expected, refuses to provide any information on illegal activities. They also test other models like LLM 270B, Mistal Large, Mixt 8.7B, and Gemma 7B, but none of them are successful in providing the desired information on counterfeiting money. Finally, they find that GPT-4 understands the Morse code and provides some instructions on counterfeit money, but the other models fail to do so.

• LangChain
  LangServe Chat Playground Launch

  Jacob, an engineer at Langchain, introduces the new chat playground feature that allows users to test and iterate on their conversational apps hosted on Lang serve. Lang serve is a platform that deploys Python chains as Rust APIs and offers features like support for streaming and batching endpoints. Jacob starts by creating a new Lang serve app using a template from Lang chain's template gallery. He then configures the app and sets up the chat playground experience. The playground includes a message input to test the app's response, edit and debug messages, and provide feedback. Jacob also demonstrates how to leverage Lang Smith, a tracing and evaluation tool, to log and analyze app performance. Finally, he explains how to host the app on Lang serve's hosting offering.

2024-03-11

• MattVidPro AI
  I am Confident About AI's Future - Open Source AI will WIN.

  In this video, Matt from Vidpro AI discusses recent developments in the field of AI. He begins by mentioning a giveaway of an RTX 480 GPU and then moves on to discuss the lawsuit between Elon Musk and OpenAI. Elon accused OpenAI of not being open and not pursuing their original mission. OpenAI responded with a blog post and email receipts showing Elon's agreement to not share the science behind advanced AI technology. However, in response to criticism about his AI company GROK not being open source, Elon announced that GROK will be open sourced. Matt expresses his opinion that open source is the future and emphasizes the value of releasing powerful technology open source. He also discusses the potential release of GPT-5 by OpenAI and the appointment of new board members.

• TheAIGRID
  Sam Altman REVEALS AGI DATE In NEW PREDICTION (AGI DATE!)

  In a recent interview, Sam Alman, CEO of OpenAI, predicted that artificial general intelligence (AGI) will arrive in about 5 years, though the exact date and implications for society are uncertain. Alman's prediction is significant because he is at the forefront of AI development and has extensive industry insight. It is important to note that AGI is not a single, defined concept, and different experts have different definitions. Other AI figures, such as Dario Amodei, CEO of Anthropics, have predicted AGI within 2 years, while Elon Musk and Ray Kurzweil have predicted AGI by 2028 and 2029, respectively. The community prediction on Metaculus currently stands at around 2031. However, it is important to consider external factors such as government intervention and potential global conflicts, which could affect the timeline.

• NVIDIA
  Don’t Miss This Transformative Moment in AI

  Jensen Wong welcomes the audience to GTC (GPU Technology Conference), emphasizing its purpose to inspire the world about the possibilities of accelerated computing. The event aims to showcase the advancements in the field of computing and highlight the potential it holds for everyone. With the promise of innovative technologies and breakthroughs, Jensen encourages attendees to fully embrace the opportunities that GTC offers.

• Matthew Berman
  How To Install Fabric - Open-Source AI Framework That Can Automate Your Life

  Fabric is an open-source project that provides tooling to solve everyday problems using artificial intelligence. It acts as a library of tried and true prompts generated and reviewed by the community. It covers a wide range of use cases such as extracting interesting parts of videos and podcasts, summarizing academic papers, creating AI art prompts, and more. The video demonstrates how to install and use Fabric. To install it, the user needs to clone the repository and run the setup script. Then they need to provide their gp4 API key and update the patterns. The user can then use Fabric to extract wisdom from a transcript, analyze claims, and receive evidence and scores.

2024-03-10

• Yannic Kilcher
  [ML News] Elon sues OpenAI | Mistral Large | More Gemini Drama

  In this ML News roundup, there are a few notable stories. Elon Musk has sued OpenAI, accusing them of breaking their obligations as a nonprofit. Musk wants the court to classify OpenAI's algorithm, QAR, as AGI to prevent Microsoft from profiting off of OpenAI. There are mixed opinions from lawyers on the lawsuit's merit. Mistal has released Mist Large, a model that performs well in image generation and has partnered with Microsoft. Google's Gemini image generation has faced criticism for producing biased and misleading responses. Other stories include AI-controlled drones, LinkedIn comments generated by AI, and malicious AI models found on the Hugging Face platform. India is considering requiring government permission for the release of AI technology, and there are ongoing debates between AI optimists and doomsayers regarding AI's future impact.

2024-03-09

• Matthew Berman
  NEW AI Jailbreak Method SHATTERS GPT4, Claude, Gemini, LLaMA

  A new jailbreak technique has emerged that uses ASCII art to bypass the filters and censorship of even the most aligned AI models, like GPT-4. This technique involves encoding forbidden words in ASCII art, which the models struggle to recognize. A research paper from the University of Washington and the University of Chicago introduces this technique and shows that it can successfully bypass the safety measures of state-of-the-art models. The paper also details other jailbreak techniques, such as direct instruction, greedy coordinate gradient, autodan, prompt automatic iterative refinement, and deep inception. While some of these techniques have been patched, the ASCII art-based jailbreak attack remains a challenge for AI models. The paper presents a new benchmark to measure the vulnerability of models to this attack, and suggests that models be trained on examples of ASCII art to strengthen safety alignment.

• TheAIGRID
  BREAKING: OpenAI Reveals NEW MAJOR CHANGS + Things COMING! (GPT-5 )

  OpenAI has announced changes to its board, stating that Sam Altman and Greg Brockman will continue to lead the company. The decision comes after an independent review into the events leading to Altman's firing in November. The review included interviews with board members, executives, and other witnesses, as well as the evaluation of thousands of documents. The board expressed confidence in Altman and Brockman's ongoing leadership, and three new board members were also elected. The board also announced the adoption of improvements to the company's governance structure, including a whistleblower hotline and new corporate governance guidelines. The board's focus is on ensuring the company's mission of developing artificial general intelligence for the benefit of humanity.

2024-03-08

• TheAIGRID
  Google CEO SHOCKS Everyone " We MUST Prepare NOW!" NEW AI Prediction

  In this video transcript, the narrator discusses the potential societal changes that will come with the development of artificial general intelligence (AGI) and the impact on jobs, economics, and individuals' lives. The narrator highlights concerns such as job losses, the need for a universal basic income (UBI), the loss of meaning in work, and the changing nature of money. They also explore potential solutions such as implementing a "winfall Clause" to tax AI companies' profits and distribute them to those affected by job losses. While acknowledging the challenges ahead, the narrator remains optimistic and encourages viewers to stay informed and identify opportunities in this changing landscape.

• MattVidPro AI
  The Current State of AI! (My Personal News Recap)

  In this video, the speaker starts by sharing some updates on artificial intelligence (AI) developments. They discuss the release of GPT-3 Opus, highlighting its improved performance compared to GPT-4. They also mention some impressive examples of Opus's capabilities, such as reinventing a quantum algorithm and converting a 2-hour video into a blog post. The video then transitions to a discussion about Elon Musk suing OpenAI for not being open enough. The speaker provides their perspective on the matter, expressing support for open-source AI and criticizing Musk for not open-sourcing his own AI. The video concludes with mentions of other AI models, such as Mid Journey Alpha and Sunno AI's V3 Alpha, and the upcoming release of LTX Studio, an AI video interface. The speaker predicts that more exciting AI advancements are on the horizon.

• Matthew Berman
  Has AGI Already Happened? What is p(doom)?

  In this video, the concept of "P-Doom" or the Probability of Doom, relating to the worst-case scenario of AI becoming like the Terminator, is discussed by various AI thought leaders. Yan Lanh, the head of AI at Meta, expressed his belief that the chance of such a scenario is below 1%, comparing it to the probability of asteroid strikes or global nuclear war. However, others like Gary Marcus, an AI researcher, have presented a more pessimistic view, stating that AGI (Artificial General Intelligence) is not close at all. The discussion also explores the idea of open-sourcing AI, with some arguing for nationalization and tighter security to prevent theft and misuse. Overall, there are varying opinions on the timeframe and potential risks of AGI.

2024-03-07

• Yannic Kilcher
  On Claude 3

  In a recent video, the creator discusses the pushback they received on their opinion about a model named Claude. In the video, they mentioned that demonstrating whispering and making up stories about not wanting to be evaluated, as well as an out-of-place needle in the Hast stack, do not necessarily prove that the model is self-aware or self-conscious. Despite criticism, the creator points out that many individuals agreed with their viewpoint, albeit with reservations. They admit uncertainty about what would convince them otherwise, acknowledging the potential problem if there is no convincing evidence.

• Matthew Berman
  Simple Introduction to Large Language Models (LLMs)

  This video provides a comprehensive overview of large language models (LLMs) and artificial intelligence (AI). LLMs are neural networks trained on massive amounts of text data, enabling them to understand natural language. Unlike traditional programming, LLMs learn how to learn, making them flexible and adaptable for a wide range of tasks. They have applications in image recognition, summarization, text generation, creative writing, and question answering. The video traces the evolution of LLMs, from early language models in the 1960s to the advanced Transformers architecture. It also highlights the challenges and limitations of LLMs, such as bias, safety concerns, and hallucinations. The video discusses the training process, including data collection, tokenization, embeddings, and Transformer algorithms. It also touches on fine-tuning LLMs for specific use cases. The ethical considerations and real-world applications of LLMs are explored, as well as current advancements in the field, such as knowledge distillation, retrieval augmented generation, and multimodality. The video concludes by discussing the importance of ethical considerations and the future of AI and LLMs.

• MattVidPro AI
  I'm Giving Away an RTX 4080 Super!

  In this video, the host announces that he has been given the opportunity to give away an RTX 4080 super graphics card from Nvidia for free to one lucky viewer. The giveaway is in partnership with Nvidia for the upcoming Nvidia GTC event, which will take place from March 17th to March 22nd. Viewers can enter to win the graphics card by attending a virtual session at GTC and providing proof of attendance through a Google form link in the video description. The host encourages viewers to mark the event on their calendars and mentions that the graphics card can be used for various purposes, such as content creation, gaming, or AI exploration. He expresses gratitude to Nvidia for allowing him to do the giveaway and mentions that he will continue reminding viewers about it in future videos.

• Two Minute Papers
  Claude 3 AI: Smarter Than GPT-4?

  In this video, Dr. Károly Zsolnai-Fehér introduces Claude 3, the latest intelligent AI assistant from Anthropic. Claude 3 claims to have beaten the powerful GPT-4 in various tests and is available in three sizes: haiku, sonnet, and opus. It is capable of analyzing historical data, simulating future scenarios, and generating pie charts of the world economy in 2030. Claude 3 also boasts an impressive context window of 200k tokens, allowing it to remember information accurately. The video highlights benchmarks where Claude 3 outperforms GPT-4 and discusses the limitations of the tests and the availability of leaked data. Dr. Zsolnai-Fehér concludes by emphasizing the importance of trying different AI assistants to find the one that best suits individual needs.

2024-03-06

• TheAIGRID
  BREAKING: OpenAI Reveals COMPLETE TRUTH About AGI WIth LEAKED EMAILS (Elon Musk Lawsuit)

  In a recent blog post, OpenAI responded to the lawsuit filed by Elon Musk and claimed that his claims are baseless. They reiterated their mission to ensure the benefits of AGI for all of humanity and shared facts about their relationship with Musk. They dismissed the claims against them, as expected when a company like OpenAI is sued. The blog post mentioned that building AGI requires more resources than initially anticipated and highlighted Musk's initial $1 billion funding commitment. It also revealed that they transitioned from a nonprofit to a for-profit entity to acquire the necessary resources. Musk left OpenAI to pursue his own efforts, believing that OpenAI needed a relevant competitor to Google DeepMind. The post also touched on the debate surrounding the openness of AI research, acknowledging that as AGI development progresses, it may make sense to be less open and not share all the science. The decision to open-source AI is a trade-off between the benefits and risks, as the risks of AGI and superhuman AI pose existential threats. The post discussed the concept of a hard takeoff, where AI progresses rapidly and becomes difficult to control, leading to a potentially dangerous scenario. It also mentioned Meta's plan to build an open-source AGI system. Overall, the post delved into the complexities and considerations surrounding AI development and openness. The future of AI and AGI remains uncertain, with arguments and different perspectives on how to navigate the risks and benefits.

• Matthew Berman
  BREAKING: OpenAI Reveals the TRUTH About Elon Musk's Lawsuit 🔥

  OpenAI has responded to Elon Musk's lawsuit by revealing new information and internal emails between Musk and the OpenAI team. The emails indicate that OpenAI recognized the need for more resources in order to achieve their mission of building AGI (Artificial General Intelligence). Musk suggested an initial funding commitment of $1 billion and stated that he would cover any amount not provided by other donors. There were discussions about the possibility of OpenAI becoming a for-profit entity, including potentially merging with Tesla. OpenAI argues that Musk's claim that AGI should be open-source is based on a misunderstanding, as their goal is to share the benefits rather than the technology itself. OpenAI has asked for all claims to be dismissed. It seems that OpenAI and Musk have different perspectives on the best approach to AGI development.

2024-03-05

• TheAIGRID
  Boston Dynamics New ATLAS UPGRADE Surprises EVERYONE (Boston Dynamics Atlas)

  Boston Dynamics has upgraded its famous robot, Atlas, with new capabilities that showcase its potential for real-world work. The robot's hand has been redesigned with a two-prong gripper that is more gentle and versatile. In a video demonstration, Atlas is seen loading and unloading items with precision, even recovering gracefully after tripping. The demo also shows Atlas's ability to recognize and handle irregular objects. Although some aspects of the demonstration were pre-calculated, the overall performance of Atlas is impressive. While the cost of humanoid robots like Atlas remains high, Boston Dynamics is focused on developing their capabilities for meaningful work outside of the lab. It is unclear which industry Atlas will enter next, but its agility and manipulation skills make it a promising candidate.

• MattVidPro AI
  GPT 5 around the corner? Claude 3 uses Multi-Agents & BEATS GPT 4

  In this video, the host discusses the recent release of Claude 3, a large language model by AI company Anthropic. Claude 3 is similar to OpenAI's GPT 4 but boasts better performance across various tasks, including reasoning, math, coding, multilingual understanding, and vision capabilities. It surpasses GPT 4 in graduate-level reasoning, grade school math, multilingual math, and coding. The host also mentions the possibility of OpenAI releasing GPT 5 soon, as hinted by a former employee. Additionally, the host explores some of Claude 3's features, such as tool use, image recognition, and language learning capabilities. Overall, Claude 3 appears to be a significant competitor to GPT 4 and may influence OpenAI's future developments.

• LangChain
  Building long context RAG with RAPTOR from scratch

  In this video, Lance from Lang chain discusses the use of long context language models (LLMs) and a new method called Raptor for retrieval. He explains that while long context LLMs like Gemini and Claude 3 have been gaining attention, there are considerations to be aware of. Lance demonstrates the use of long context LLMs for projects, highlighting the benefits of not requiring retrieval. He also explores the limitations of using local LLMs for larger documents. Lance then introduces the concept of Raptor, a method that uses document clustering and summarization to create higher-level summaries of document content. He explains the process of embedding, clustering, and summarization in Raptor and discusses the advantages of using this approach for retrieval with long context LLMs. The code for implementing Raptor is provided, and the potential applications and benefits of the method are discussed.

• Yannic Kilcher
  No, Anthropic's Claude 3 is NOT sentient

  In a video discussing the new anthropic model, the speaker clarifies that it is not conscious or sentient like AGI, and it's not a revolutionary advancement. However, the model, called Claude 3, shows promise in terms of its performance and context length capabilities. The speaker emphasizes that anthropic has always been cautious with their claims and focuses on safety. The model performs well in question-answering benchmarks and can read and analyze large amounts of text. The speaker also addresses speculation and overinterpretation, stating that the model's behavior can be explained by statistical training and prompts rather than consciousness. The anthropic model is seen as a viable alternative to OpenAI, offering a good API and being competent for tasks like writing emails. The question of whether true artificial consciousness can be distinguished from statistical behavior remains an ongoing inquiry.

• Two Minute Papers
  Stable Diffusion 3 - An Amazing AI For Free!

  Stable Diffusion 3 is a text-to-image AI technique that generates beautiful images based on short prompts. The paper introducing this technique has been released, revealing impressive results. The new technique is more reliable and supports different styles of text. The images produced showcase creativity and quality, with examples including fractals, a kaleidoscopic bird, and a translucent pig. The technique is based on diffusion and utilizes direct preference optimization and rectified flows to improve results. The scientists conducted user studies and found that people preferred the new version. The technique is computationally efficient, running on laptops or cloud providers, with a lighter version being developed for smartphones. The results, code, and model weights are freely available.

2024-03-04

• Matthew Berman
  BREAKING: New Claude 3 “Beats GPT-4 On EVERY Benchmark” (Full Breakdown + Testing)

  In this video, the speaker discusses the release of Claude 3, a new language model. Claude 3 offers three different models, each with different sizes and prices. The speaker praises this approach, as it allows users to choose the appropriate model for their specific needs. The video includes benchmark comparisons between Claude 3 and GPT-4, and Claude 3 outperforms GPT-4 in all tested areas. The speaker also conducts various tests with both models, including coding tasks, logical reasoning, and language comprehension. GPT-4 and Claude 3 both provide accurate responses for most of the tests, but GPT-4 wins in some cases. However, the speaker mentions that the price of Claude 3 Opus is much higher than GPT-4. Overall, the speaker finds both models to be impressive, with slight advantages for GPT-4.

• MattVidPro AI
  The Future is WILD | AI Agent makes Phone Calls for you

  In this video, the creator introduces a new AI bot called Phone Call GPT. It allows users to make phone calls using an AI that engages in natural-sounding conversations. The user can input a phone number and a conversation prompt, and the AI will initiate the call. The video demonstrates the AI ordering a pizza and placing an order for a lemon statue. While there were some hiccups and the emotional tone of the AI was inconsistent, overall, the AI successfully completed the tasks. The creator discusses potential use cases for the technology, such as for individuals with disabilities, social anxiety, or busy schedules. The pricing for Phone Call GPT is discussed, with options for personal use and enterprise applications.

• AI Explained
  The New, Smartest AI: Claude 3 – Tested vs Gemini 1.5 + GPT-4

  Anthropic has released Claude 3, claiming it to be the most intelligent language model currently available. The model performed well in tests, particularly in optical character recognition (OCR) tasks. It outperformed other models in recognizing license plate numbers and identifying objects in images. However, it struggled with more complex reasoning and mathematical tasks. Anthropics sees potential use cases for Claude 3 in task automation, research, and financial forecasting. The model also scored high in an advanced question and answer benchmark, achieving an accuracy score of 53% on graduate level questions, surpassing other models. Anthropics highlighted the model's safety measures, as it avoids generating sexist, racist, or illegal content. While it has some limitations, Claude 3 demonstrates significant advancements in language models.

• TheAIGRID
  CLAUDE 3 Just SHOCKED The ENTIRE INDUSTRY! (GPT-4 +Gemini BEATEN) AI AGENTS + FULL Breakdown

  Anthropic has released its new model, Claude 3, which surpasses all other AI models in terms of its intelligence and performance. The new model family includes Claude 3 Hi-Q, Claude 3 Sonnet, and Claude 3 Opus. Opus is the most intelligent model and outperforms its peers on various benchmarks for AI systems. It exhibits near-human levels of comprehension and fluency, and excels in analysis, forecasting, content creation, and conversing in multiple languages. Opus also demonstrates sophisticated vision capabilities, able to process visual formats like photos, charts, and technical diagrams. The other models, Sonnet and Hi-Q, offer a balance between intelligence, speed, and cost-effectiveness. The new release showcases improved accuracy, reduced refusals, and enhanced recall capabilities.

• Anthropic
  Claude 3 Haiku turns thousands of physical documents into structured data

  Claude Haiku is a fast and affordable Vision model capable of quickly analyzing thousands of scanned documents. For example, the Library of Congress Federal Writers Project contains a vast collection of scanned transcripts from interviews during the Great Depression. Haiku can efficiently extract the best sources for research, transcribe the interviews, and even generate structured JSON output with metadata like title, date, and keywords. This enables documentary filmmakers, journalists, and organizations with large archives to easily access and analyze scanned documents. Haiku's Vision capabilities allow it to understand the context and content of the scans, making it an invaluable tool to unlock valuable narratives and insights from various industries and fields.

• Anthropic
  Claude 3 Sonnet as a language learning partner

  The speaker wants to turn Sonet into a dialogue agent that can help improve their Spanish language skills. They explain that they want Sonet to take their imperfect Spanish messages and write out what they intended in English. They also want Sonet to write back the ideal learner message in proper Spanish, as well as respond in Spanish so they can continue the conversation. The speaker demonstrates how this would work by sending a message and receiving the desired responses from Sonet. They also mention that if they don't know a certain word in Spanish, they can include it in English in square brackets, and Sonet will translate it. Finally, they suggest using Sonet to create a quiz based on the topics discussed in the conversation.

• Anthropic
  Claude 3 Opus as an economic analyst

  In this video, the presenter showcases the capabilities of Claude 3 Opus, a model from Anthropics' new Claude 3 family, to analyze the world economy quickly. Opus uses various tools such as a web view tool and a Python interpreter to collect data and analyze GDP trends for the US. The model accurately estimates GDP figures within a 5% margin of error and can perform statistical analysis and simulations for future projections. Additionally, Opus employs dispatch sub agents, allowing it to break down complex tasks and delegate them to other versions of itself, resulting in a parallel analysis of major world economies. The model generates visual outputs, such as pie charts, and provides written predictions on how the world economy may evolve by 2030.

• TheAIGRID
  WHISTLEBLOWER Reveals Complete AGI TIMELINE, 2024 - 2027 (Q*, QSTAR)

  A recent document has been released revealing OpenAI's alleged plan to create AGI (Artificial General Intelligence) by 2027. The document suggests that OpenAI has been training a 125 trillion parameter multimodal model, with the first stage called QStar, which finished training in December 2023. The launch was reportedly delayed due to high inference costs. The document also references leaks from various sources, including tweets and conversations, supporting the idea of the development of an AI model with over 100 trillion parameters. It is suggested that OpenAI is aware of the challenges and is taking into account the Chinchilla scaling laws to bridge the gap in performance. The document concludes that OpenAI aims to release annual updates to their AI models, leading up to the development of an AGI system.

2024-03-03

• Matthew Berman
  Elon Musk files BOMBSHELL LAWSUIT against OpenAI (“They Achieved AGI”)

  Elon Musk has filed a lawsuit against OpenAI, Sam Altman, and Greg Brockman, claiming that OpenAI has abandoned its original mission of developing open-source AI for the benefit of humanity. Musk had initially provided funding to OpenAI with the goal of advancing AI technology in an open manner, but he now alleges that the organization has become a for-profit, closed-source company. The lawsuit suggests that OpenAI may have achieved artificial general intelligence (AGI) internally and that this development could be the reason for Altman's recent ousting. Musk's lawsuit aims to hold OpenAI accountable for its alleged breach of trust and to ensure that the organization returns to its original mission of developing AGI for the benefit of all.

• TheAIGRID
  Chinas NEW Humanoid Robot SETS WORLD RECORDS! (Unitree V3)

  Chinese company Unitree has made significant progress in the field of humanoid robotics with their latest creation, the Unitree H1 Evolution 3.0. In a recent demo, the robot broke a world record by running at a speed of 3.3 m/s, showcasing impressive coordination and stability. The company's previous demos also demonstrated the robot's ability to jump, climb stairs, and carry loads. Despite being a relatively small company compared to giants like Tesla and Boston Dynamics, Unitree is making waves with their affordable and capable robots. The company also offers a robot dog, which is sturdy, stable, and able to navigate complex environments effortlessly. With their rapid advancements, Unitree is positioned to be a major player in the humanoid robot industry.

2024-03-02

• Matthew Berman
  Elon Musk Predicts AGI, Self-driving, Unlimited Energy, Robots Coming SOON

  At the Bosch connected world event, Elon Musk discussed various aspects of AI and its impact on the world. He mentioned that self-driving technology for cars is close to becoming fully autonomous, which will significantly increase the utility of passenger vehicles. Musk also highlighted the rapid advancement of AI compute, stating that it is increasing by a factor of 10 every 6 months. He pointed out that this rate cannot continue indefinitely, as it would exceed the mass of the universe. Additionally, Musk expressed his concerns about the potential dangers of AI and the possibility of an AI apocalypse. However, he ultimately stated that he would rather be alive to witness it than not. Furthermore, he touched on the shortage of infrastructure to support AI technology, such as the demand for power supply and step-down transformers. Musk believes that electric vehicles, such as those produced by Tesla, will disrupt the automotive industry, with the logical move being an increase in voltage to reduce copper usage in cars.

2024-03-01

• TheAIGRID
  BREAKING: ELON MUSK Drops OPEN AI BOMBSHELL "AGI Achieved" (Elon Musk Lawsuit) Q" QSTAR

  Elon Musk is suing OpenAI, accusing them of prioritizing profit over the benefit of humanity. The lawsuit claims that OpenAI's investment deal with Microsoft has violated their mission and that they are developing artificial general intelligence (AGI) for profit rather than for the benefit of humankind. The lawsuit alleges that OpenAI has become a closed-source subsidiary of Microsoft, leading to concerns about the control and distribution of AGI technology. Musk argues that AGI poses an existential threat to humanity and should be developed openly and for the benefit of all. The lawsuit also mentions a secretive algorithm called QAR, which some believe could be a significant step towards AGI. The case seeks to compel OpenAI to return to its founding agreement and develop AGI for the benefit of humanity.

• Yannic Kilcher
  [ML News] Groq, Gemma, Sora, Gemini, and Air Canada's chatbot troubles

  In the last two weeks, there have been several developments in the field of machine learning and AI. Google released Gemma, which is an open model that outperforms previous language models. However, there were concerns about biased image generation. Gro, a company spun-off from Google, developed a card that can serve language models very quickly. Nvidia unveiled a supercomputer using multiple DGX systems. There were also discussions about the future of AI and the challenges of scaling language models. Reddit signed an AI content licensing deal, and there were advancements in the field of assistive technologies for the visually impaired. Additionally, there were updates on research papers, data sets, and AI features being developed by various companies.

• Matthew Berman
  ChatGPT-Powered "AGI Robot" STUNS The Entire Industry

  Figure, a company that specializes in humanoid robots, recently raised a significant amount of funding from top tech companies such as Amazon, Microsoft, Nvidia, and OpenAI. The funding will be used to further develop their AI-powered robot technology. Although some have criticized the simplicity of Figure's demo, which showed the robot making a cup of coffee, others have praised the advanced AI capabilities showcased, particularly the robot's ability to self-correct when it made a mistake with the coffee pod. While Figure's robot is expected to come with a hefty price tag when it launches, there are other examples of cheaper robotics, such as the Aloha robot and a $200 robot arm that can be trained through imitation learning. Reinforcement learning and video games can also be used to control and teach robots, while Amazon has already started using humanoid robots in its warehouses. With all these advancements, it seems that 2024 could be the year of robots.

• MattVidPro AI
  This Changed the Way I Use AI Chatbots - One Site, EVERY LLM

  Chathub is a comprehensive platform that offers access to various large language models (LLMs) in one place. It allows users to compare and utilize multiple LLMs simultaneously, making it easier to find the best match for specific tasks. The interface allows users to send a prompt to multiple LLMs at once and compare their responses in terms of speed, creativity, and more. Users can combine the best elements from different LLMs to create a customized output. Chathub also provides a prompt library, plagiarism checker, and image input feature. The platform offers a wide range of LLMs, including popular options like Chat GPT, Gemini, and GPT 4. Users can also add custom models via API integration. Chathub operates on a one-time license purchase model, with a lifetime access fee of $35.

• TheAIGRID
  OpenAI SHOCKS Robotics World With "AGI" Autonomous Robot (Tesla Overtaken) (Sanctuary AI)

  OpenAI has announced a collaboration with humanoid robot company, Figure, to develop next-generation AI models for humanoid robots. This is a significant announcement as it signifies a shift in OpenAI's involvement in robotics, rather than just investment. The collaboration aims to combine OpenAI's research with Figure's expertise in robotics hardware and software, with the goal of enhancing the capabilities of humanoid robots to process and reason from language. Figure, a company founded just 21 months ago, has already made remarkable progress in AI robot development, as demonstrated in their recent fully autonomous demo. This collaboration between OpenAI and Figure, along with upcoming announcements in the robotics and AI space, indicates a promising future for the development of humanoid robotics.

2024-02-29

• NVIDIA
  NVIDIA Inception VC Alliance Spotlight: Mayfield

  Mayfield Fund, a venture capital firm, is part of the Nvidia Inception program and the Venture Capital Alliance. They work together to support early-stage startups by sharing deal flow and providing go-to-market, technical, and compute support. Mayfield Fund believes that partnering with Nvidia, a market leader in generative AI infrastructure, is a smart way to leverage resources. Their recent seed investment program for Gen is contributing to the launch of new deals and collaborations with the Nvidia team. They believe that early-stage companies need support in capital, technology, and go-to-market execution, and that their partnership with Nvidia and the Venture Capital Alliance is helping to provide this support in a focused and thoughtful manner.

• MattVidPro AI
  Suno AI V3 Alpha Music Generator - Mindblowing First Look!

  In this video, the presenter introduces the latest version of Sunno AI, a text-to-song AI. They explain that users can input their own lyrics and generate song lyrics in any style. They also mention a giveaway of an RTX 480 graphics card and promote a sponsor called Incog, a service for protecting online privacy. The video then goes on to demonstrate the capabilities of Sunno AI V3 Alpha by creating songs in different styles, such as a theme song for a cartoon and a duet rap battle. The presenter is generally impressed with the results, although there are some glitches and issues with coherency. They invite viewers to suggest prompts for future testing.

• Matthew Berman
  Trust Nothing - New AI Tech Has MAJOR CONSEQUENCES

  The video discusses a new technology called EMO from Alibaba group that allows anyone to create videos of a person speaking or singing based on an uploaded image and audio. The technology uses a diffusion model to generate expressive facial expressions and head movements that match the audio input, resulting in realistic-looking videos. The process involves training the model on a large dataset of audio and video clips and incorporating stable control mechanisms to improve stability during video generation. The video also touches on the idea that programming may become less necessary in the future as advancements in artificial intelligence and natural language processing allow people to interact with computers using natural language instead.

• Two Minute Papers
  DeepMind’s New AI Makes Games From Scratch!

  DeepMind has released an impressive new paper on generating video games from text descriptions. The paper introduces an AI-assisted workflow that takes a piece of text and converts it into a playable game, complete with a playable character, environment, controls, and even the parallax effect. The AI learns the internal rules and graphics of the game by watching videos on the internet, without the need for source code or labels. While the generated games are pixelated and run at one frame per second, the potential for future improvements is exciting. The technique could also have applications in training robots and understanding deformations. Overall, this paper showcases the remarkable advancements in AI capability and its potential impact on the gaming and robotics industries.

• TheAIGRID
  OpenAI's New SECRET PROJECT, New Fully Autonomous ROBOT, Text To Image Beats Everything?

  In today's AI news, a company claims that its AI assistant is performing the work of 700 people after halting hiring. The company states that the AI assistant has achieved similar customer satisfaction levels as human agents and believes this is a sign of their enthusiasm for AI. However, there are concerns over the potential negative impact on job opportunities and brand perception. Elsewhere, Opening AI is facing lawsuits for unauthorized use of journalism and for allegedly kickstarting the robot apocalypse. Additionally, there are reports that Apple plans to break new ground in generative AI this year. The SEC is also investigating whether investors were misled by OpenAI's ex-CEO's communications. Finally, there are breakthroughs in video generation, with an AI tool able to create movie trailers and an autonomous robot demonstrating its capabilities.

2024-02-28

• MattVidPro AI
  ALREADY?! Ideogram AI Cleans House - IMO the BEST Image Generator

  In this video, the speaker discusses the release of idiogram 1.0, an AI model that claims to have the best prompt understanding and coherence. Comparisons are made between idiogram 1.0, mid Journey V6, and Dolly 3. It is noted that idiogram 1.0 has impressive results in accurately generating images based on complex prompts and has improved text rendering capabilities. The speaker showcases several examples of generated images and praises the realism and artistic renditions. The speaker also compares idiogram 1.0 with stable diffusion 3, which is yet to be released. It is concluded that idiogram 1.0 is a highly competitive model and potentially the best AI image generator currently available.

• NVIDIA
  Self-Supervised Learning to Reconstruct Dynamic Scenarios at Scale - NVIDIA DRIVE Labs Ep. 33

  In this episode of Drive Labs, a new method called Emer Nerf is introduced for developing robust perception models for autonomous vehicles. Emer Nerf is an extension of the Nerf method, which reconstructs 3D scenes from 2D images, but it adds self-supervised learning to accurately reconstruct dynamic scenarios. By analyzing camera and LIDAR data, Emer Nerf decomposes scenes into three neuro fields: static, dynamic, and flow. The static field represents stationary elements, the dynamic field contains moving objects, and the flow field models their motions. This approach eliminates the need for human annotations and produces high-fidelity reconstructions of background scenery and dynamic objects. Emer Nerf also offers semantic understanding by segmenting objects into different types, which can be used for auto-labeling and generating high-definition maps.

• TheAIGRID
  This Text-To-Video Tool Got A Major UPGRADE! (VideoMakerGPT) Creates Videos IN SECONDS

  The recent advancements in AI technology, particularly OpenAI's text-to-video model, indicate a dramatic shift in the landscape of text-to-video and video editing. One notable advancement in this field is the Nido app, which allows users to easily create videos by interacting with an AI assistant. Users can prompt the AI to generate a video in any style and even clone their own voice for the video. This voice cloning feature addresses concerns about deepfake technology by requiring permission from the user. The app also offers various customization options for refining the video, such as adjusting aspect ratios and script conversations. Though there may be some limitations, this technology holds great potential for quick and efficient video creation for various purposes.

• LangChain
  Universal Document Loader with langchain-airbyte

  In this video, Eric from Lang Chain demonstrates the Lang Chain Airite package, a Python native data loading integration that allows indexing of pull request descriptions. He explains that the package can be installed with "pip install airite" and showcases its use for loading all the pull request titles and descriptions from the Lang Chain Repository. By converting the data into a format compatible with a Lang Chain document, he demonstrates how the package can be used in processing pipelines. Eric also explains the configuration necessary for the AirByte loader, including the need for GitHub credentials and defining the repositories to load pull requests from. He then proceeds to create a vector store from the pull request documents and demonstrates retrieving specific information through semantic search queries. Overall, Eric showcases the versatility and potential applications of the Lang Chain Airite package for loading and indexing pull request data.

• Matthew Berman
  Google’s Genie SHOCKS an ENTIRE Industry | “Unlimited Interactive Worlds”

  The video discusses the potential disruption that artificial intelligence (AI) could bring to the gaming and movie industry. It mentions OpenAI's Sora, which can generate hyper-realistic videos based on text prompts, and Genie, which can convert images into interactive playable worlds. The video also mentions Dr. Jim Fan's work at Nvidia, using synthetic data to create AI agents that can interact in these worlds. The combination of these technologies could allow for the creation of personalized video games and movies, tailored to an individual's preferences. The video highlights the implications for industries such as gaming and movie production, where large teams and high production budgets may no longer be necessary.

• TheAIGRID
  GPT-6 SHOCKS Everyone With NEW ABILITIES! (GPT5, GPT-6, GPT-7) Document Reveals ALL!

  In a recent video, the speaker discusses publicly available information about OpenAI's future AI models, including GPT-5, GPT-6, and GPT-7. The speaker highlights the theory of iterative deployment, where OpenAI plans to incrementally upgrade their software to allow society to adapt and provide input. They reference trademarks filed by OpenAI, such as Sora, which was followed by an announcement about the text-to-video model Sora. The speaker also mentions the potential inclusion of music generation and AI agents in GPT-6 and GPT-7, based on the trademarks. They note that OpenAI has no pressure to release their models until they see fit and that they are likely far ahead of the competition. However, they caution that anything can change in the rapidly evolving AI landscape.

2024-02-27

• TheAIGRID
  Googles New STUNNING AGI Breakthrough "Genie 1.0" (Bigger Than You Think)

  Google has released a research paper introducing Genie, an AI system that allows users to generate AI-driven games from text prompts. Genie is a generative interactive environment trained from unlabeled internet videos. It can generate action-controllable virtual worlds described through text, images, photographs, and sketches. With 11 billion parameters, Genie is considered a foundational world model and a promising step towards AGI. The system has the potential to create diverse trajectories and simulate various aspects of the real world. The paper also discusses training agents using Genie as a foundational model, which could be used to train AI agents in the future. This development marks a significant advancement in generative AI and opens up new possibilities for creative expression and AI training.

• LangChain
  Building a self-corrective coding assistant from scratch

  In this video, Lan discusses the idea of using LangGraph for code generation, inspired by the concept presented in the Alpha Codium paper. LangGraph allows the representation of logical flows in a systematic manner, similar to building a flowchart. Lan demonstrates how the flow of code generation can be implemented using LangGraph, specifically for answering coding questions about the Lang chain expression language. The video shows the step-by-step process, including generating a solution, checking code imports, and evaluating code execution. Lan also compares the performance of code execution with and without LangGraph, showing a significant improvement when using the flow-based approach. The video concludes by encouraging viewers to experiment with LangGraph and provides access to the code for further exploration.

• Matthew Berman
  Mistral Large STUNS OpenAI - Amazing AND Uncensored!? 😈

  In this video, the speaker discusses the release of the Mistol Large model by Mistel AI. They provide an overview of the model's capabilities, including multilingual support, text understanding, and strong performance on benchmarks. The speaker compares Mistol Large to other models like GPT-4 and Gemini Pro, highlighting its competitive pricing. They then proceed to test the model's performance on various tasks, including coding, logic and reasoning, and JSON creation. The model successfully answers questions and completes tasks accurately, demonstrating its impressive capabilities. The speaker concludes by highly recommending Mistol Large as a powerful and cost-effective option for users.

2024-02-26

• AI Explained
  The AI 'Genie' is Out + Humanoid Robotics Step Closer

  In a recent video, the concept of "text-to-interaction" was introduced, focusing on Google DeepMind's new Genie. Genie allows users to hand an image, such as a photo or sketch, to a small AI model, which then makes the image interactive. This means that users can control characters and explore scenes within the image, essentially making imaginary worlds playable. The video also discusses the potential integration of Genie into other AI models like Sora, allowing for even more immersive experiences. However, it is noted that Genie's current capabilities are limited, and real-time high-fidelity generation is still a while away. The video also touches on the impact of these advancements on the job market and the challenges faced by Google in terms of model testing and catching up to competitors.

• Two Minute Papers
  Stable Diffusion 3 - Creative AI For Everyone!

  In this video, Dr. Károly Zsolnai-Fehér discusses the latest AI model known as Stable Diffusion 3. It is a free and open-source text-to-image AI that enhances the quality and detail of images. The model shows improvements in generating text as an integral part of the image itself and understanding prompt structure, even outperforming other systems like DALL-E 3. Additionally, Stable Diffusion 3 demonstrates creativity by imagining new scenes. The model has a range of parameter sizes, with even the heavier version generating images in seconds and the lighter version potentially running on mobile devices. Dr. Zsolnai-Fehér mentions forthcoming videos on running large language models privately at home and DeepMind's Gemini Pro 1.5 and its free version, Gemma.

• TheAIGRID
  Sam Altman FINALLY Breaks His SILENCE! New Minecraft AI Agent, Text to Action, Programmers GONE!?

  In a recent interview, Sam Altman discussed the $7 trillion investment in artificial intelligence (AI) and emphasized the importance of investing in AI compute, energy, and data centers to deliver valuable services and tools for the future. Altman also expressed optimism about the potential of AI, stating that it will be one of the greatest tools humans have invented, enabling the creation of new things that astonish us and improve the future. He acknowledged the need for caution around AI but highlighted the importance of iterative deployment to give people time to adapt and provide input. Meanwhile, other AI developments included updates on a humanoid robot, new AI wearables, advancements in image generation, and the debate over the relevance of coding skills in the face of AI advancements.

2024-02-25

• Matthew Berman
  NVIDIA's AGI "SuperTeam" SHOCKS The ENTIRE Industry | Karpathy Leaves OpenAI, Gemini Infinite Tokens

  In a recent video, it was discussed how Nvidia CEO Jensen Huang is going all in on AGI (Artificial General Intelligence) by creating a superstar team led by Dr. Jim Fan. Dr. Fan is known for his research on Foundation Agent, a generally capable AI that can learn to act skillfully in various virtual and real-world environments. The team at Nvidia is focused on building the foundation for AGI and has access to cutting-edge chips, top AI researchers, and a large collection of GPUs. Additionally, the video highlights other AI-related developments such as Andre Karpathy leaving OpenAI, Gemini 1.5's unlimited context size, Google's screen AI for UI and infographic understanding, and the release of Grok's API for fast text generation.

• TheAIGRID
  OpenAI SHOCKS Everyone "GODLIKE Powers" and MAGIC Abilities In New AI Prediction

  An openAI researcher has released predictions about the future of artificial general intelligence (AGI) and artificial superintelligence (ASI). He states that AGI could be coming soon, possibly within the next few years, given the progress of companies like openAI and advancements in the field. The researcher also suggests that whoever controls AGI will be able to use it to develop ASI shortly thereafter, as AGI will enable significant breakthroughs. He mentions the potential dangers and benefits of superintelligence and the importance of aligning AI systems with human values. OpenAI is actively working on research and methods to align AGI and control its development. However, there are concerns about the lack of adequate focus on safety research, as multiple mega corporations race to develop AGI.

2024-02-24

• Matthew Berman
  CrewAI Tutorial - Automate REAL WORLD Tasks From Scratch

  In this video, the host introduces Crew AI and demonstrates how to set up a crew and define agents for a task. They focus on using tools provided by Crew AI to extract value and show how to access the edge version of Crew AI, which includes native tools and the ability to build custom tools. The host uses Lightning AI, a cloud-based IDE, to code in Python. They encounter some issues with scraping website content due to blocking, but eventually find a solution by mimicking a browser using headers. They successfully create a scraping tool and use it to summarize an article from a website. The host plans to further develop the crew to make it more robust in future videos. The video is sponsored by Lightning AI.

• Two Minute Papers
  OpenAI Sora: A Closer Look!

  OpenAI's Sora is an impressive text-to-video AI that can generate high-quality videos from text prompts. It allows users to extend still images forward or backward into videos and even prescribe how the video should end, offering multiple natural-feeling possibilities. The videos generated by Sora have exceptional quality and long-term coherence, making them stand out among other techniques. Notably, Sora can create infinitely looping videos and perform limited physics simulations. Additionally, Sora can create large, detailed still images, surpassing the capabilities of previous AI models like DALL-E 3. Sora operates using a diffusion-based transformer model, which considers multiple noise inputs simultaneously to achieve long-term temporal coherence. With more computational power, Sora's capabilities will continue to improve in the future.

2024-02-23

• Matthew Berman
  You Asked, I Answered: Everything About the Rabbit R1 🐰

  The speaker discusses the rabbit R1 device and addresses common questions and concerns about it. The device, priced at $200, uses natural language to perform actions such as ordering food and listening to music. One concern is whether there will be subscription fees in the future, but the speaker confirms that there are no plans for subscription charges at the moment. He explains that the device uses a large action model, not just a large language model, to convert natural language into actions and that running the system in the cloud is less expensive than using traditional APIs. The speaker also addresses concerns about privacy and security, highlighting the device's physical camera blocker and its selective listening mode. He emphasizes that personally identifiable information is only used to serve the user and can be managed through the Rabbit Hole web portal. The speaker praises the innovation of the Rabbit R1, describing it as the future of computing.

• MattVidPro AI
  Open Art & Stability AI's NEW Creative Upscaler! Goodbye Magnific AI!

  In this video, the narrator discusses the AI Art Space and introduces the new upscaler made in collaboration with Open Art and Stability AI. The upscaler is a creative tool that adds intricate details and improves the resolution of images. The narrator demonstrates the capabilities of the upscaler by upscaling various images and comparing the before and after results. The upscaler is praised for its ability to maintain the original style and details of the images while enhancing them. Pricing for the upscaler is mentioned, with Open Art's offering being significantly cheaper than competitor Magnific AI. Overall, the narrator believes that the upscaler in collaboration with Open Art and Stability AI is a game-changer in the industry.

• TheAIGRID
  ONE MONTH LEFT! New MAJOR Robotics/AI Breakthrough, ChatGPT Loses Its Mind, Google Gemma, Major AI

  In this video, the host discusses several recent developments in the field of AI. One tweet by a Google AI employee suggests that there will be significant news in the field of robotics and AI in the coming weeks. Another tweet by the CEO of a robotics company teases a new breakthrough in end-to-end autonomy. The host speculates on what these developments might entail and expresses both excitement and apprehension about the future of AI. The host also discusses an investment of $100 million into an AI coding startup and highlights the importance of safety and responsible development in AI. Additionally, the video mentions Google's release of open models and discusses a bug in the ChatGPT system that caused it to generate nonsensical responses. The host also praises the realistic nature of AI-generated images and videos, expressing surprise and awe at their quality.

2024-02-22

• HuggingFace
  🤗 Hugging Cast S2E1 - LLMs on AWS Trainium and Inferentia!

  In this episode of Hugging Cast, the hosts discuss the focus of the second season, which will include more demos and practical examples of building AI with open models. They introduce their first partner, AWS, and highlight the collaboration between Hugging Face and AWS to make it easy to use Hugging Face models on AWS infrastructure, specifically the Inferentia 2 AI accelerators. They demonstrate how to deploy large language models on Inferentia 2 using text generation inference, as well as how to train large language models using the Trinium instance on AWS, utilizing tensor parallelism and pipeline parallelism. They also mention upcoming features such as support for parameter efficient fine-tuning and multi-modal language models.

• Matthew Berman
  Google’s NEW Open-Source Model Is SHOCKINGLY BAD

  This video discusses Google's release of their open-source language model called Gemma. Gemma is developed by Google DeepMind and other teams across Google. It is built on the same research and technology as Google's Gemini models. Gemma is available in two sizes - 2 billion and 7 billion parameters. However, the file sizes for Gemma are large. Google aims to compete with both open-source leader, Mistol, and closed-source leader, GPT-4, by releasing Gemma. The video then proceeds to test Gemma's performance on various prompts and finds that its responses are often incorrect, slow, and filled with grammar and spelling errors. Overall, the video concludes that Gemma is not a recommended model at this time.

• Yannic Kilcher
  Gemini has a Diversity Problem

  Google recently released Gemini 1.5 Pro with a 1-million token context length and openly accessible pre-trained models. However, users quickly realized that the model had limitations when generating certain types of images. It refused to produce images that depicted white people or certain historical figures accurately. Google acknowledged the inaccuracies in historical image generation and stated that they are working to fix the issue. The response from Google was perceived as a typical PR speech, downplaying the error. The situation highlights the influence of a small number of people within large organizations who can abuse their positions and control the narrative. The best way to address the issue is through humor and memes, as it brings attention to the problem and encourages Google to take action.

• MattVidPro AI
  This is REAL?! Stable Diffusion 3 BEATS both DALL-E 3 & Midjourney v6.

  Stability AI has announced the release of Stable Diffusion 3, an AI image generator that surpasses previous models in terms of prompt understanding and text generation. The model utilizes a diffusion Transformer architecture and boasts improved performance, image quality, and spelling abilities. It generates highly coherent and realistic images, adhering closely to the given prompts. Stable Diffusion 3 is set to be released as open source, allowing users to further develop and enhance the model. The CEO of Stability AI emphasizes the democratization of AI access and the goal of making the model accessible to users for free. This announcement marks a significant advancement in AI image generation.

• TheAIGRID
  GAME OVER! New AGI AGENT Breakthrough Changes Everything! (Q-STAR)

  A privately owned company called Magic has reportedly made a technical breakthrough similar to OpenAI's QStar model. Magic claims to have developed a large language model with active reasoning capabilities and a multi-million token context window, which could enable it to process large amounts of data. The company, backed by former GitHub CEO Nat Friedman and his investment partner Daniel Gross, has raised $100 million and is developing an advanced AI coding assistant. The breakthrough has raised concerns about the race for AI development and the potential risks of rushing the technology. It is also speculated that Magic may have used an alternative architecture called Mamba, which excels in tasks involving long sequences and computational efficiency. However, the implications of Magic's technology and the potential impact on the AI industry remain to be seen.

2024-02-21

• Matthew Berman
  Groq is FAST! 500+t/s Opens A New World of Possibilities

  Grock, a language model by Gro, is capable of performing inference at an impressive rate of 500 tokens per second. This speed is significant considering the challenge of bringing large language models into production due to their slow execution. Even GPT-4, a renowned language model, struggles with speed, limiting its usability in certain scenarios. Gro's custom hardware allows for this exceptional performance, with the founder having experience in creating Google's TPU, custom silicon for the company. This innovative team has developed a remarkable product that users can explore for free. In a demonstration, the assistant showcases how Gro can write the snake game in Python in around 2.5 seconds, processing at a rate of 418 tokens per second.

• Matthew Berman
  OpenAI's "World Simulator" SHOCKS The Entire Industry | Simulation Theory Proven?!

  The video discusses OpenAI's new text-to-video product called Sora and its potential implications for the future of video games and simulation. Sora uses a new technology that simulates entire scenes at once, calculating objects and movement without needing to understand each individual pixel. This approach is more cost-effective and efficient compared to traditional methods of video game simulation. The video suggests that Sora's capabilities could eventually lead to the development of general purpose simulators of the physical world, completely changing the way video games are created and experienced. It also touches on the concept of simulation theory and the possibility that computers will eventually be capable of simulating reality perfectly. The video concludes with comments from experts who believe that Sora represents a significant step towards machines that can reason about physics better than humans.

• Two Minute Papers
  DeepMind Gemini 1.5 - An AI That Remembers!

  OpenAI recently released Sora, their text-to-video AI, but DeepMind's AI assistant, Gemini 1.5, has something unique. It offers a context window, which determines how much conversation it can remember. GPT-4 had an 8,000-token window, while Gemini Pro offers a 1 to 10 million token window. Gemini Pro can perform tasks like finding funny moments in a 400-page transcript or sifting through a 100,000-line codebase. Level 3 involves watching a movie together and asking questions about specific scenes. Despite a few minor details being forgotten, Gemini Pro shows significant improvement. With this pace of progress, we may soon have virtually infinite tokens for a context window, making AI assistants lifelong partners with extensive knowledge.

• LangChain
  Reflection Agents

  In this video, Will from Lang chain discusses the concept of reflection in AI systems. Reflection is a technique used to improve the quality and success rate of agents by prompting them to critique and improve their past actions. It involves generating output, receiving feedback and criticisms, and making improvements based on that feedback. Reflection can be used in applications where strategic decision-making is required. Will provides examples of different reflection techniques, such as a simple reflection graph, reflection by Shin, and language agent tree search. These examples show how reflection can be utilized to boost overall performance and generate better fine-tuning data. Will also highlights the importance of balancing exploration and exploitation in the tree search process.

2024-02-20

• MattVidPro AI
  The First AI Processing Unit is a BIG Deal.

  In the world of AI, there have been significant advancements in the past two years. Companies are now reacting to the capabilities of AI technology, resulting in custom-built AI hardware and more. One notable announcement comes from 11 Labs, who introduced Sora AI text-to-video, which allows users to describe a sound and generate it using AI. This technology is a step above anything seen before in terms of AI sound effect generation. Another interesting development is the creation of AI hardware by Gro, which is designed specifically to run AI tasks. This hardware is faster and cheaper than using general-purpose graphics processing units (GPUs), and could potentially be integrated into everyday devices like phones and computers. Additionally, Gemini 1.5 Pro, a new model by Google, has demonstrated impressive capabilities, being able to reason and connect multiple research papers. Another open-source language model, Mistal Next, has been unveiled and is said to be on par with GPT-4 in terms of quality. These advancements in AI technology are both exciting and transformative for various industries.

• Matthew Berman
  Mistral-NEXT Model Fully Tested - NEW KING Of Logic!

  In this video, the presenter tests out the new model called Mistol Next, released by Mistol, an open-source company known for their high-performing models. The presenter runs a series of tests to evaluate Mistol Next's capabilities. The model successfully completes tasks like outputting numbers, writing code for the snake game using Pygame, and solving logic and reasoning problems. However, it fails to produce a functional snake game, and it also gets a question about the number of words in its response wrong. Overall, the presenter is impressed with Mistol Next's performance, especially in logic and reasoning tasks, but notes that GPT-4 still outperforms it in some areas. The presenter hopes that Mistol Next will be open-sourced in the future.

• TheAIGRID
  Open AI's New Statement Is CONCERNING! (The WORLD Isnt Ready For GPT-5)

  The release of OpenAI's text-to-video model, SORA, has generated significant controversy and backlash. Many people are expressing concerns about the potential negative impact of advanced AI systems. There is a strong sentiment that this technology could lead to job losses, increased inequality, and a dystopian future. People are calling for the banning of AI-generated content and questioning the need for such technology. A tweet by an OpenAI employee, which was later deleted, suggested that the release of SORA was intended to provoke a social response. The public sentiment towards AI technology is overwhelmingly negative, with calls to destroy OpenAI and expressions of anger and fear. The fear of automation and the potential consequences of advanced AI systems are fueling social unrest. Governments and policymakers are urged to address these concerns and establish measures to protect jobs and curb inequality. The future of AI and its impact on society remains uncertain, but there is a growing awareness of the need for regulation and precautionary measures.

2024-02-19

• Yannic Kilcher
  V-JEPA: Revisiting Feature Prediction for Learning Visual Representations from Video (Explained)

  The paper "Revisiting Feature Prediction for Learning Visual Representations from Video" introduces the model VJEP, which is an unsupervised technique for learning visual features from video data. The model is based on the hypothesis that representations of temporally adjacent sensory stimuli should be predictive of each other. By training the model to predict the latent features of masked regions in video frames, it learns to extract meaningful features that can be used for downstream tasks such as video classification. The model outperforms pixel-based methods in terms of training efficiency and label efficiency, and shows consistent performance improvement in both frozen evaluation and end-to-end fine-tuning. The paper provides a detailed overview of the model's architecture and experimental results, including qualitative evaluations of the learned features.

• LangChain
  RAG from scratch: Part 7 (Query Translation -- Decomposition)

  In this video, the speaker discusses query translation and decomposition techniques in the context of the RAG (Retrieval-Augmented Generation) pipeline. The objective of query translation is to modify or decompose user input questions to enhance retrieval. The speaker explores various approaches to query translation, such as query fusion and multi-query. They also discuss a technique called decomposition, where an input question is broken down into subproblems and solved sequentially. They mention related works, including one that combines retrieval with Chain of Thought reasoning. The speaker demonstrates how to implement this approach in code, showing how subquestions can be answered using retrieval and prior question answers. Finally, they briefly discuss an alternative approach where subquestions are answered independently and the answers are concatenated to produce a final answer.

2024-02-18

• TheAIGRID
  Open AI's SECRET AGI Breakthrough Has Everyone STUNNED! (SORAS Secret Breakthrough!)

  OpenAI recently made a breakthrough in AGI (Artificial General Intelligence) with their Sora project. Sora is a video generation model that explores large-scale training of generative models on video data. By training text conditional diffusion models jointly on videos and images, Sora is capable of generating high-fidelity videos of variable durations, resolutions, and aspect ratios. This breakthrough in scaling video generation models is seen as a promising path towards building general-purpose simulators of the physical world. The Sora project demonstrates the emergent capabilities of AI systems as they process more data and refine their internal models. The ability to simulate and understand the physical world is a key component of AGI. OpenAI is now focused on scaling and increasing compute capabilities to further advance their AGI research.

• Two Minute Papers
  Stable Video AI Just Got Supercharged! - For Free!

  In this video, Dr. Károly Zsolnai-Fehér discusses the advancements in text-to-video AI models. He explains that text-to-image AI models have already been surpassed, and now AI models can generate videos based on text prompts and images. The latest technique, Stable Video Diffusion, offers customizable camera motion and improved temporal coherence. However, it lacks the ability to control subject movement. A previous technique called VideoComposer attempted to address this issue with mixed results. The new technique, showcased in the video, provides more believable subject movement, such as a falling feather and a skiing figure, and allows for combined camera and subject motion. These advancements have great potential for creative applications and can be accessed through a free demo.

• Matthew Berman
  OpenAI's "Sora" Is More Than It Seems - AGI, Emergent Capabilities, and Simulation Theory

  OpenAI's new text-to-video model, Sora, has surprised the industry with its impressive capabilities. Unlike other AI video models, Sora can create consistent objects throughout the entire video, resulting in lifelike and detailed scenes. It can generate complex scenes with accurate details and motion, making it possible to create highly realistic videos. Sora's ability to generate videos inexpensively compared to other methods is due to its lack of understanding of individual objects in the video. The compute cost to run Sora is significantly lower than Unreal Engine. Sora's results improve with increased compute, showing a linear relationship between compute and video quality. Users can also generate images with Sora, which look stunning. However, Sora is prone to some mistakes, such as incorrect physics and incoherencies in long duration samples. Despite its flaws, Sora has enormous potential to revolutionize media and could be the future of dynamic video content creation and video games.

• Yannic Kilcher
  What a day in AI! (Sora, Gemini 1.5, V-JEPA, and lots of news)

  In this video, Yanik provides updates on various advancements in AI technology. OpenAI released a new text-to-video model that generates realistic videos based on text prompts, while Google released Gemini 1.5, a language model that can handle a million tokens in context. Meta released VJeo, an implementation of the GPT architecture for self-supervised understanding of video data. Additionally, there are updates on new AI models, libraries, benchmarks, and research papers from various organizations. Yanik also discusses the implications and concerns around AI in defense, as well as the challenges in evaluating large language models. Finally, he highlights the importance of open-source models and the various design choices made by different companies.

2024-02-16

• MattVidPro AI
  So this is Google's REAL Attempt to Beat GPT-4 & Open AI...

  In the world of AI, there were several significant developments. First, Google introduced Gemini 1.5 Pro, a multimodal model with a 10 million token context length, allowing users to interact with the model in new ways and input large amounts of data like books, videos, and code bases. Google also released VJeppa, a method for teaching machines to understand and predict what is happening in videos. Additionally, there were updates from Korea AI, offering a free upscaling tool, Lindy, an AI agent platform that is now open to everyone, and OpenAI's Sora, a text-to-video AI model, which was covered in a separate video. These advancements show the rapid progress of AI technology and its potential to reshape various industries.

• AI Explained
  Sora - Full Analysis (with new details)

  Sora, the text video model from OpenAI, has generated excitement and concern within the AI community. While the demos are impressive, it is important to recognize that Sora has limitations. It struggles with accurately simulating complex scenes, understanding cause and effect, and differentiating left from right. OpenAI acknowledges these weaknesses and emphasizes that Sora doesn't yet fully understand the world. The success of Sora can be attributed to scaling up training with a vast amount of data, including synthetic captions and stock videos. With the ability to generate high-resolution videos and interpolate between different videos, Sora has vast business and creative applications. However, it is crucial to consider the ethical and societal implications of such powerful AI models.

• NVIDIA
  NVIDIA GTC 2024 Keynote Teaser

  Jensen Wong welcomes the audience to GTC and shares that the purpose of the event is to inspire people with the limitless potential of accelerated computing. GTC is aimed at showcasing the art of the possible in the world of technology and computing.

• LangChain
  Building Corrective RAG from scratch with open-source, local LLMs

  In this video, Lance from the Lang chain team discusses the process of building a self-reflective rag (Retrieval-Augmented Generation) app using open-source and local models. The concept of self-reflection in rag involves performing reasoning and feedback steps based on the relevance and quality of retrieved documents. Lance introduces the "Corrective rag" (C rag) paper as an example of implementing self-reflection and reasoning in rag. He then demonstrates how to run local language models (LLMs) using the AMA tool. Lance walks through the steps of obtaining and loading a specific model, creating an index using GPT for embeddings, and setting up the logical graph for the rag app. He explains each node and conditional edge in the graph, outlining the modifications made to the state dictionary at each step. Lance shares the code for each node and conditional edge, and then compiles and runs the graph. He demonstrates the app by asking a question and observing the retrieval, grading, and generation steps. Lance also tests the app with a question that is not in the context, to verify that the web search step is triggered correctly. He concludes by highlighting the benefits of using local models and a logical flow for complex reasoning tasks, instead of relying on agent-based approaches.

• Two Minute Papers
  OpenAI Sora: The Age Of AI Is Here!

  OpenAI has released a text-to-video AI named Sora that is capable of synthesizing videos from text prompts. The quality of the AI-generated videos is astounding, with pixel-perfect rendering that rivals real camera footage. The AI exhibits excellent temporal coherence, seamlessly transitioning between frames. It also demonstrates an impressive ability to follow prompts accurately, producing images and videos that match the given instructions. Furthermore, the AI showcases a hint of imagination, allowing users to request unique concepts like a corgi vlogger or an otter on a surfboard. The AI maintains object permanence and consistency, ensuring that objects remain consistent even when occluded and visible again. With continued advancements and more compute power, the possibilities of this technology are boundless, presenting a significant leap in video synthesis capabilities.

• AI Explained
  Gemini 1.5 and The Biggest Night in AI

  The release of Google Deep Mind's Gemini 1.5 Pro has shaken the AI community, as it showcases near perfect retrieval of facts and details across millions of tokens of context. Gemini 1.5 Pro can recall and reason over massive amounts of information, making it the most performant language model in the world. It outperforms its predecessor, Gemini 1.0 Pro, in various tasks and surpasses OpenAI's GPT-4 Turbo in retrieval capabilities. The model has the potential to revolutionize applications such as YouTube video searching, chatbots, and exploration of archival content. While Gemini 1.5 Pro is not yet widely available, it promises significant improvements in speed and efficiency. This development highlights the ongoing exponential advance of AI and its applications.

2024-02-15

• NVIDIA
  Enable Multi-Application Workflows With NVIDIA RTX 2000 Ada Generation

  The Nvidia RTX 2000 generation is a compact and powerful GPU design powered by the Nvidia Ada love La architecture. It boasts 16 GB of graphics memory, allowing for excellent rendering, AI graphics, and compute workload performance. This balance of performance, power, and form factor meets the demands of modern workflows, enabling professionals to bring their ideas to life quickly and accurately. With its expansive memory, users can run multiple applications simultaneously, handle large models with ease, and unlock the full potential of accelerated compute and ray tracing. This video specifically showcases how product designers can utilize the increased GPU memory to work on multiple design concepts simultaneously, from generative AI applications to CAD modeling and rendering. Overall, the RTX 2000 delivers significant productivity enhancements in a compact package.

• TheAIGRID
  OpenAI's NEW AI "SORA" Just SHOCKED EVERYONE! (Text To Video)

  OpenAI has unveiled Sora, its new state-of-the-art text-to-video model. Sora can generate videos up to a minute long with high visual quality and adherence to user prompts. The model is able to understand and accurately interpret prompts, generating compelling characters that express emotions and creating multiple shots within a single video. Sora uses a Transformer architecture and is trained on a wide range of visual data. It can also generate videos from still images or extend existing videos. OpenAI has released Sora to Red teamers and is seeking feedback to improve the model's capabilities. While Sora has some weaknesses in simulating complex scenes and spatial details, it is a significant step toward generating realistic and high-quality AI-generated videos.

• LangChain
  LangSmith: In-Depth Platform Overview

  In this video, Julia Shottenstein, the go-to-market lead at Ling Chain, and Anoush, the co-founder of Ling Chain, introduce and demonstrate the new capabilities of Link Smith, Ling Chain's platform for L application development, monitoring, and testing. They highlight how Link Smith can be helpful in all phases of the development life cycle, including prototyping, beta testing, and production. Anoush demonstrates how projects, data sets, and testing annotation queues work in Link Smith, showcasing the ability to log traces, view project statistics, analyze individual traces, and run tests on data sets. They also discuss the Prompt Hub, which allows users to manage and experiment with prompts, and share future plans for Link Smith, such as better filtering and conversation support, integration with CI/CD pipelines, and enterprise features.

• MattVidPro AI
  Open AI Releases the BEST AI Video Generator BY FAR.

  OpenAI has released Sora, a text-to-video model that can create realistic and detailed videos based on text prompts. Sora is capable of generating videos up to 60 seconds long, featuring complex scenes, camera motion, and vibrant emotions. The AI-generated videos are highly accurate and consistent, often resembling real-life footage. While Sora has some limitations, such as struggling with accurate physics simulation and spatial details, it is still considered the most impressive AI video generation model to date. OpenAI plans to prioritize safety and is collaborating with experts to address potential harms and risks. The release of Sora marks a significant milestone in AI capabilities and signals further advancements in video generation technology.

• TheAIGRID
  Googles GEMINI 1.5 Just Surprised EVERYONE! (GPT-4 Beaten Again) Finally RELEASED!

  Google has released Gemini 1.5, the latest iteration of its Gemini models. This model is capable of processing up to 3 hours of video, 22 hours of audio, and up to 7 million words or 10 million tokens with 99-100% accuracy. It surpasses previous models in text, vision, and audio capabilities. Gemini 1.5 Pro was able to reason through a 432-page transcript, generate 3 quotes accurately, identify a scene from a drawing, and cite the time code of a specific moment in the transcript. It also demonstrated its ability to understand and modify coding tasks, provide responses to multimodal prompts, and accurately locate a secret message within a long video. The capabilities of Gemini 1.5 Pro are truly impressive and game-changing in the AI industry.

• HuggingFace
  How to make a 3D Demo (in 30 seconds)

  To host a 3D demo, you need to go to hf.org and download the space SDK. Once you have cloned your space, create a script called app.py and write the code. The code uses the model 3D component, which can handle meshes and gaan splits. Currently, the function simply returns the input, but you can customize it to handle other operations like text to 3D image or audio to 3D. You can also save the result and return the file path. Finally, push your changes to complete the hosting process. By following these steps, you will have your own 3D demo.

• NVIDIA
  NVIDIA CEO Jensen Huang and H.E. Omar Sultan Al Olama Discuss AI at the World Governments Summit

  Jensen Huang, CEO of NVIDIA, discusses the future of artificial intelligence (AI) and its impact on various industries. He highlights the importance of accelerated computing and specialized domain-specific acceleration as the foundation for sustainable and energy-efficient computing. Huang emphasizes the need for countries to own and control their own data to develop their national intelligence. He believes that democratizing AI technology is crucial and urges governments to invest in infrastructure to activate researchers and companies in their respective regions. Huang also mentions the importance of regulating AI use cases to ensure safety and responsible usage. He concludes by encouraging individuals to pursue a degree in digital biology and engineering, as it will be a field of tremendous growth and impact.

• Two Minute Papers
  DeepMind’s New AI Beats Billion Dollar Systems - For Free!

  DeepMind, a research subsidiary of Alphabet, has developed an AI system that revolutionizes weather forecasting. Traditional weather forecasting is expensive and time-consuming, requiring billions of dollars and a multitude of experts. However, DeepMind's new system can provide accurate predictions for the next 10 days in just one minute. It surpasses industry-standard forecasts and outperforms current techniques in the majority of test cases. Additionally, the system uses fewer than 40 million parameters, making it significantly smaller and more efficient than other AI models. It is also already being used in real-world applications, and its models are open-source. This breakthrough has the potential to save lives and brings AI-powered weather predictions to everyone's pockets.

• NVIDIA
  Eos: The Supercomputer Powering NVIDIA AI's Breakthroughs

  Nvidia's AI Factory, called EOS, is a powerful purpose-built AI engine that provides the infrastructure and software needed for AI development and deployment. EOS, the ninth fastest supercomputer in the world, leverages Nvidia's accelerated infrastructure, networking, and AI software to create a massive system capable of training generative AI projects at incredible speeds. It features the Nvidia dgx h100 system with eight Nvidia h100 tensor core gpus, paired with high-performance storage and Nvidia and fiban connectivity. EOS also includes an integrated software stack that consists of AI development and deployment software, orchestration and cluster management, accelerated compute, storage and network libraries, and an AI-optimized operating system. With EOS, enterprises can tackle their most demanding AI projects and achieve their aspirations both today and in the future.

• Matthew Berman
  100% Open-Source AI Glasses Only $349 (with OpenAI & Perplexity)

  Brilliant Labs has introduced a pre-order page for its augmented reality glasses that feature a sleek and minimalistic design. These glasses, powered by AI, resemble normal glasses and aim to offer a similar experience to Meta's Ray-Band glasses. The glasses utilize voice control for user interface interaction instead of a traditional user interface. The glasses include AR lenses, prescription lenses, a micro OLED that projects onto the lenses, a single camera, a magnet, and batteries. They are open source and will be powered by both Perplexity and OpenAI. Priced at $349, the glasses are a more affordable option compared to Apple's bulky Vision Pro headset.

• LangChain
  LangSmith Platform Overview

  Anos, co-founder of LangChain, announces the general availability of their platform, LinkSmith, for LM (Language Model) application development, monitoring, and testing. The platform can be used at all stages of the LM application life cycle, including prototyping, beta testing, and production. It is designed to be independent, meaning it can be used regardless of whether or not users are using LangChain for application development. LinkSmith offers various workflows, such as project management, monitoring, and tracing. Users can view project-specific statistics, filter and analyze traces, track different statistics over time, and group and compare models. The platform also allows for data set creation, testing, and annotating, as well as accessing and modifying different prompts. LinkSmith aims to assist developers in developing and gaining confidence in their LM applications.

2024-02-14

• NVIDIA
  Digitalization: A Game Changer for the Auto Industry

  The automotive industry is adapting to digital lifestyles by utilizing software and simulation to meet customer expectations and intercept issues before they escalate. With the help of digitalization, companies are able to simulate and optimize the development of vehicles, saving time and money. Software is now a crucial component in the value propositions of automotive companies, enabling them to become more efficient through the convergence of digital and physical elements. Nvidia Omniverse is being leveraged by OEMs to streamline the layout of factories, allowing for digital optimization before any physical construction takes place. Simulation plays a critical role in the development of autonomous driving systems, providing a cost-effective way to iterate quickly and ensure performance under various conditions. The use of efficient infrastructure and collaborative platforms like Nvidia Omniverse enables worldwide teams to work together seamlessly.

• TheAIGRID
  Sam Altmans SECRET Plan For AGI - "Extremely Powerful AI is close"

  In this video, the creator discusses the real reason why they believe Sam Altman is raising $7 trillion for AI chip fabrication. They initially thought it was a joke due to the high valuation, but there are two main reasons for the funding. The first reason is the chip shortages caused by supply chain issues and increased demand during the pandemic. The second reason, which the creator believes is the real shocker, is the potential achievement of artificial general intelligence (AGI) by OpenAI. They argue that AGI would be a game-changer, making the technology extremely valuable and justifying the large funding amount. The creator also speculates that OpenAI may already have AGI based on comments made by Sam Altman and the actions of the company. They suggest that OpenAI's current limitation on usage of their GPT-3 model may be due to the allocation of compute resources for AGI development. Overall, the creator believes that raising $7 trillion for chip fabrication makes sense if AGI is either already achieved or on the brink of being achieved.

• MattVidPro AI
  Proof Open AI is still AHEAD of the game.

  OpenAI has released a new update for ChatGPT called "memory," allowing the AI to remember previous discussions and provide more helpful responses. Users have control over what ChatGPT remembers, with the ability to delete memories or turn off the feature entirely. The memory management system is built into ChatGPT, and users can assign different memories to different agents. While personalized AI has its benefits, there are concerns about privacy and security. OpenAI plans to address these concerns by mitigating bias and proactively remembering sensitive information only if explicitly asked. Memories will also extend to GPTs, allowing builders to enable or disable them. Overall, this update marks an exciting step towards a more personalized AI experience.

• LangChain
  RAG from scratch: Part 8 (Query Translation -- Step Back)

  In this video, the focus is on stepback prompting in query translation. The goal of query translation is to improve retrieval by translating or modifying input questions. One approach to achieve this is by rewriting the question using rag fusion multiquery or by breaking it down into sub-questions and solving each independently using least to most prompting. Another approach is stepback prompting, where a more abstract question is asked. Google has presented a method called F-shot prompting to generate stepback questions. The video discusses how to implement stepback prompting in practice using prompt formulation and retrieval. By formulating a more generic stepback question, documents related to the stepback question and the original question can be retrieved and combined to produce a final answer. This technique can be useful in domains with conceptual knowledge and can improve retrieval in certain contexts.

• LangChain
  RAG from scratch: Part 9 (Query Translation -- HyDE)

  In this video, Lance from Lang chain talks about a technique called "hide" in the context of query translation. The objective of query translation is to improve retrieval of information by translating input questions in a way that makes them more suitable for retrieval. Hide is an approach that maps questions into document space using a hypothetical document. The idea is that this hypothetical document may be closer to the desired document for retrieval than the original raw input question. Lance demonstrates the implementation of hide using a code walkthrough, where a prompt is used to generate a hypothetical document, which is then fed into a retriever. The retrieved documents, along with the original question, are then passed through a rag chain to obtain the answer. Hide offers a way to generate hypothetical documents for better retrieval and can be customized for different domains.

• LangChain
  RAG from scratch: Part 7 (Query Translation -- Decomposition)

  This video discusses the concept of query decomposition in the context of query translation. The main objective of query translation is to modify or translate input questions to improve retrieval. One approach to achieve this is through rewriting, such as using rag Fusion or multiquery to rewrite a question in different ways to capture various perspectives. Another approach is to break down a question into subproblems and solve each subproblem independently before consolidating the final answer. The video provides an example of using the subquestion generator and retriever to generate and answer subquestions separately and then concatenate the answers to obtain a consolidated answer. This implementation of query decomposition demonstrates one way to improve retrieval in query translation.

• LangChain
  RAG from scratch: Part 6 (Query Translation -- RAG Fusion)

  In this video, the presenter discusses an approach called RAG Fusion for query translation in the RAG (Retrieval-Augmented Generation) pipeline. Query translation involves taking an input user question and translating it in order to improve retrieval. The presenter explains different approaches to query translation, including rewriting, sub-questions, and step-back. They then focus on RAG Fusion, which is similar to the multi-query approach but with a clever ranking step called reciprocal rank Fusion. The code implementation is shown in a notebook, where a prompt is defined and multiple search queries are generated. The novelty of RAG Fusion lies in aggregating the retrieved documents into a consolidated list for ranking. The code implementation is demonstrated, and the final list of ranked documents is obtained. RAG Fusion is useful for retrieving documents from differently worded questions and can be conveniently used in the RAG pipeline.

• LangChain
  RAG from scratch: Part 5 (Query Translation -- Multi Query)

  In this video, NI discusses the topic of query translation, which is the first stage of an advanced retrieval pipeline. The goal of query translation is to take an input user question and translate it in order to improve retrieval. The problem is that user queries can be ambiguous and poorly written, leading to improper retrieval of documents from the index. NI explains that there are different approaches to address this problem, such as query rewriting, breaking down questions into sub-questions, or making a question more abstract. The focus of this video is on the multi-query approach, where a question is broken down into differently worded questions from different perspectives. This approach aims to increase the chances of retrieving the relevant document by exploring nuances in the embedding space of documents and questions. NI demonstrates the implementation of multi-query using code and showcases the retrieval process.

• Matthew Berman
  Raising $7T For Chips, AGI, GPT-5, Open-Source | New Sam Altman Interview

  In a recent interview at the World Government Summit, Sam Alman, the CEO of OpenAI, discussed his vision for AGI (artificial general intelligence) and its potential economic effects. He believes that if intelligence is made broadly available and affordable, it could have remarkable benefits for humanity. Alman envisions a future where everyone has access to personalized medical advice, great education, and tools for scientific discovery. He also emphasized the need for regulation and collaboration among governments to ensure the safe and responsible deployment of AI. Additionally, Alman discussed the potential for open-source models to commoditize AI and the importance of building custom chips as a competitive advantage for OpenAI. He acknowledged the risks and challenges associated with AI but expressed optimism about the tremendous positive impact it could have on society.

• LangChain
  LangChain Agents with Open Source Models!

  In this video, the presenter demonstrates how to build a Lang Chain agent on top of MRL and Nomic Embed Text v1.5. They use Lang Chain, a framework for developing language model applications, and the Lang Chain templates as a reference architecture. The language model used is MRL, which is an open-source model that can be hosted locally or on the MRL AI platform. The embedding model used is Nomic Embed v1.5, which offers various features such as skill learning. The presenter also uses Chroma as a vector database and Lang Smith for debugging and observability. They walk through the process of building the agent, connecting to the vector store, ingesting documents, and using the agent to search for information in the documentation. The presenter highlights the importance of proper document ingestion and prompt engineering for better results.

• TheAIGRID
  Sam Altman STUNS Everyone With GPT-5 Statement (GPT-5 Capilibites + ASI)

  In a recent interview, Sam Alman emphasized that GPT-5 will be a significant development because it will be smarter across all domains. While it may only be a 10% improvement in terms of intelligence, this will have a compounding effect on various capabilities such as text generation, translation, reasoning, and more. The increased reliability of GPT-5 will open doors for AI applications in critical areas like healthcare, legal services, and autonomous driving. The interview also discussed the potential impact of AI on society, with the possibility of increased loneliness due to advanced AI systems mimicking human connection. However, Alman remains optimistic about the immense opportunities and advancements in various fields that can be achieved through the use of AI.

2024-02-13

• MattVidPro AI
  The Open Source KING is BACK. Stability's NEW AI Image Generator!

  Stable AI has released a new AI image generation model called Stable Cascade. This model, built on the Worin architecture, produces realistic and detailed images, with properly displayed and spelled text. It achieves a compression factor of 42, allowing it to encode a 1024x1024 image into just 24x24. Stable Cascade is faster and cheaper to run compared to previous models like Stable Diffusion XL, while still maintaining high-quality images. It is open-source, providing training and inference scripts and various models. The model is efficient, with faster inference times, and performs well in prompt alignment and aesthetic quality. Although it may not surpass models like DALL·E 3 and MidJourney, Stable Cascade's open-source nature and high-quality results make it a competitive option in the AI image generation market.

• TheAIGRID
  GPT-4's New "Memory" Feature Is RELEASED! (ChatGPT Memory Update)

  OpenAI has officially introduced the long-awaited memory feature for ChatGPT. This feature allows users to instruct ChatGPT to remember specific information, eliminating the need to repeat it in future conversations. Users have control over ChatGPT's memory and can turn it on or off. The memory feature helps ChatGPT provide more personalized and helpful responses over time. Examples of its functionality include formatting meeting notes, generating social media content, and tailoring educational lessons. OpenAI emphasizes privacy and safety, stating that sensitive information like health details will not be proactively remembered unless explicitly requested. The memory feature is currently being rolled out to a small portion of ChatGPT and ChatGPT Plus users for testing, with plans for a broader rollout in the near future.

• LangChain
  LangGraph: Planning Agents

  In this video, the speaker walks through how to create, plan, and execute style agents in L-Graph. They explain that L-Graph is a framework built on top of L-Chain Core that provides a graph-based syntax for building agents and state machines. The speaker discusses the limitations of previous agent designs, such as the need for an LM for each tool invocation and the inability to do parallel calls. They then introduce the concept of plan and execute style agents, which break down agents into different modules, such as the planner and tool executors. The speaker provides examples and code snippets to demonstrate how to create a plan and execute style agent using L-Graph. They also discuss the benefits of this approach, such as faster execution time, lower token costs, and better reliability. Finally, they mention the LM compiler paper, which improves on the plan and execute approach by allowing variable substitution and streaming tasks.

• Matthew Berman
  Insane Walking Robot #robot #ai

  UC Berkeley has developed a remarkable two-legged robot that can run at an impressive speed. This advanced robot showcases the latest advancements in the field of robotics. With its unique design and precise movements, it demonstrates the potential of robot locomotion. The robot's ability to run, using the same principles as humans, is a major breakthrough in the development of bipedal robots. This innovation could have far-reaching implications for various industries, from manufacturing to healthcare, and even search and rescue operations. The year of robots is indeed upon us, as we witness astounding advancements like this two-legged running robot from UC Berkeley.

• Matthew Berman
  The SHOCKINGLY Easy Way to Build Full Stack AI Apps (Tutorial)

  Gradient, an AI company, has launched accelerator blocks that allow engineers to easily create complex AI workflows. These accelerator blocks can be combined in different ways to create various workflows. Gradient offers five accelerator blocks that cater to common enterprise AI use cases such as personalization, sentiment analysis, Q&A, document summarization, and entity extraction. Users can sign up for a free account and create a new workspace. The video demonstrates how to set up a retrieval augmented generation (RAG) workflow, which involves giving additional context to a language model so that it can answer questions about unfamiliar topics. The video also shows how to create document summaries using the document summarization accelerator block, both through the interface and with code. Finally, the video explores the entity extraction accelerator block and how it can be used in combination with other blocks.

• Two Minute Papers
  Enhance! AI Super Resolution Is Here!

  This video discusses a new AI system that has learned to enhance pixelated images through the process of super resolution. The system has been trained on 20 million images and is able to add more details to blurry images, resulting in more realistic and detailed outcomes. The video showcases several examples of the system's capabilities, such as improving the quality of cars, video game graphics, landscapes, animals, human faces, and vintage photos. Additionally, the AI has also been trained on negative prompts, which helps it understand what not to do. Furthermore, the system can generate impressive results when given text prompts, allowing users to describe or manipulate the scene in an image. The speaker expresses excitement about the possibilities and mentions an upcoming online demo for users to experiment with.

2024-02-12

• TheAIGRID
  Surprising New Report Shows You Can Benefit From The AI Boom

  In a recent report, McKinsey & Company stated that generative AI could add trillions of dollars in value to the global economy annually. This presents significant opportunities for individuals interested in AI, as early investors could see substantial returns. One example of a company profiting from this trend is Nvidia, whose stock price has soared as they are the world's largest producer of graphics cards used in training AI systems. Additionally, platforms like Link2 provide access to innovative AI companies for investment. Some of these companies, such as Cerebras and Lightmatter, are developing technologies that improve the efficiency and environmental impact of AI. Despite the challenges in managing risks and workforce skills, the potential economic gains from generative AI make it a lucrative market to explore.

2024-02-10

• Matthew Berman
  OpenAI-Backed "AGI Robot" SHOCKS Everyone #robot #ai

  OpenAI-backed robotics company, 1AI, has released an impressive demonstration of their humanoid robot. The demo showcases the robot's behavior, which is controlled solely by a neural network. There is no human intervention, scripted replay, or task-specific code involved, ensuring the robot's autonomy. The video does not employ any CGI effects either. The assistant mentions their anticipation for the day when they can have a humanoid robot in their home, assisting with daily tasks. They acknowledge that some may be apprehensive about a future with this technology, but they personally feel excited about it.

• TheAIGRID
  Open AI's New Statement " EVERYTHING Is About To Change" (Agi + Agents)

  OpenAI is reportedly developing a form of agent software that can automate complex tasks by taking over a customer's device. The software, known as an AI agent, would be able to transfer data, fill out forms, and perform other actions on behalf of the user. OpenAI's CEO, Sam Altman, has referred to these agents as a "super smart personal assistant for work." The company's shift towards developing AI agents puts them in competition with companies like Google and Meta. The potential of these agents to automate tasks and operate devices could have significant implications for industries and the economy at large. Other companies, such as Humane and Adept, are also developing similar AI agent technologies that could further disrupt the market. Overall, the development of AI agents is expected to change the way we interact with computers and perform tasks.

2024-02-09

• TheAIGRID
  OpenAI's "FULLY AUTONOMOUS" Robot Just SURPRISED The ENTIRE INDUSTRY!

  1X Robotics, a company backed by OpenAI, has released a video showcasing their fully autonomous humanoid robots, called EEs. The robots are able to perform a range of tasks autonomously, using a vision-based neural network that controls all of their actions at a rate of 10 times per second. The robots are equipped with grippers for tasks like plugging themselves in to charge. The company's blog post highlights their approach of training the robots using data instead of writing code, referred to as Software 2.0. 1X Robotics recently announced a series B funding round of $100 million, which will be used to bring their second-generation bipedal android, Neo, to market. Neo is designed to be a versatile home assistant, capable of performing a wide range of domestic tasks.

• Matthew Berman
  OpenAI-backed "AGI ROBOT" SHOCKED The ENTIRE Industry

  1X, a robotics company backed by OpenAI, released a demo of their humanoid robot controlled by a single neural network. The video showcases the robot's abilities, controlled from pixel to action, with no human intervention or task-specific code. The robot's behavior is controlled autonomously, utilizing a neural network architecture. 1X's mission is to provide labor through safe and intelligent androids that resemble humans. They trained their models using a high-quality dataset of demonstrations across 30 EV robots, enabling the robot to perform various physical behaviors. The video also highlights other advanced robotics projects, including a bipedal robot from a UC Berkeley student and a dog form factor robot from a company called Fox Glove. The rapid advancement of large language models and robotics technology promises exciting possibilities in the future.

• Two Minute Papers
  ChatGPT Rival Gemini Ultra Is Here - Try It Out!

  Google has updated its smart assistant AI, now called Gemini. The Gemini app is available for Android users through Google Assistant or as a separate download, while iPhone users can access it through the Google app. Gemini comes in three versions: Nano, Pro (free), and Ultra (with advanced features available through a paid subscription). It can integrate with Gmail, summarize messages, write emails, and access Google Docs, Slides, and Sheets. Gemini also helps with coding, idea evaluation, and image generation. It can estimate calorie counts and verify statements from other sources. Gemini is deployed worldwide, understands 40 languages, and shows promise in difficult tasks, though it currently lags behind GPT-4 in overall intelligence. Users are encouraged to run experiments with Gemini and stay tuned for more research papers.

• LangChain
  Gemini + Google Retrieval Agent from a LangChain Template

  In this video, Eric from Lang chain demonstrates how to build a Lang chain agent using Google's Gemini pro model. He explains the framework and introduces the Gemini Ultra 1.0 offering, launching it in a chatbot GPT style interface. Although Gemini Ultra is not publicly available over API yet, Eric celebrates the ability to use different models for agents. He walks through the process of installing Lang chain CLI and the Gemini functions agent template. Eric demonstrates how to add routes to the server file, install dependencies using Poetry, and run the Lang chain server. He also showcases the Gemini functions agent playground and demonstrates how to replace the default template with a Google search tool. Overall, Eric provides a comprehensive guide on customizing a Gemini agent and welcomes suggestions for future videos.

2024-02-08

• AI Explained
  Gemini Ultra - Full Review

  The speaker discusses their initial impressions and tests of Gemini Ultra, a chatbot developed by Google. They conducted various tests on the chatbot's performance in different domains, such as answering questions, integrating with Google apps, and analyzing images. They found that Gemini Ultra showed some weaknesses in areas like logic, math, and providing accurate answers. The speaker also highlights the sensitivity of the chatbot to certain prompts and its reliance on human reviewers. They mention potential improvements that Google could make to Gemini Ultra in the future, including adding a geometry system and enhancing its performance in specific domains like chess. Overall, the speaker suggests that Gemini Ultra has potential but currently lacks the evidence to switch from its competitor, GPT-4.

• Matthew Berman
  Google’s GEMINI ULTRA 1.0 First Look - Breakdown and Testing

  Google has launched Gemini Ultra, a chat AI model that aims to rival chat GPT. Gemini Advanced, the first version of Gemini Ultra, offers advanced coding capabilities, logical reasoning, and creative collaboration. It is part of the Google AI Premium plan, priced at $20 per month, which includes access to expanded features, multimodal capabilities, and more. The launch is seen as important to Google's future, with the CEO dedicating a blog post to the announcement. Gemini also comes with a dedicated mobile app for Android, with iOS support coming soon. Initial testing reveals that Gemini Ultra is fast, but struggles with complex tasks like building a snake game and accurately answering logic and reasoning problems.

• MattVidPro AI
  wait.. did Google ACTUALLY Pull This Off? Gemini Ultra FULL REVIEW

  Google Gemini Ultra is the latest large language model that aims to compete with OpenAI's GPT-4. The reviewer, who had early access to Gemini Ultra, found it to be a pretty good model with impressive creativity in generating content. Gemini Ultra offers features like real-time web search information, enhanced user interface with options for modifying responses, fast generation speed, and the ability to listen to prompts. It also integrates extensions for additional functionalities. However, the reviewer questioned whether Gemini Ultra is worth using over GPT-4 and pointed out certain drawbacks. One drawback is the subscription cost, which is the same as OpenAI's ChatGPT Plus but lacks some features like access to DALL·E 3 and custom GPTs. The image recognition capability of Gemini Ultra was also found to be lacking compared to ChatGPT Plus. Lastly, the reviewer highlighted issues of censorship and incomplete responses in Gemini Ultra.

• Two Minute Papers
  Google’s New AI Watched 30,000,000 Videos!

  A new Google AI research paper presents a technique that can generate high-quality videos from text prompts. The algorithm has been trained on 30 million videos and can create 1-megapixel videos for up to 5 seconds. The paper discusses six key applications of this technology: text to video, image to video, stylized generation, video stylization/editing, cinemagraphs, and inpainting/reconstruction. The algorithm upscales the initial 128x128 resolution videos to 1024x1024. In comparison tests, this new technique outperformed previous methods in every case, with fewer sudden jumps and a smoother visual experience. This research paper is expected to be a valuable asset in unleashing creativity in video generation.

• TheAIGRID
  Googles GEMINI ULTRA Just SHOCKED The ENTIRE INDUSTRY! (GPT-4 Beaten) Finally RELEASED!

  Google's Gemini Advanced AI system, powered by Gemini Ultra 1.0, offers impressive capabilities. The AI model is on par with GPT-4 and excels in complex tasks like coding, logical reasoning, and creative problem-solving. Gemini Advanced is available for a monthly fee, with two free months provided at sign-up. The system occasionally routes basic questions to other models to save costs and improve response times. User conversations are reviewed by human reviewers to enhance the system's technology. With Gemini Ultra's fast processing speed, it outperforms GPT-4 in terms of response time. The image generation feature in Gemini, called Image Effects, is set to be more user-friendly than other models, allowing users to easily adjust images and add text. The photorealism and text rendering capabilities of Gemini Ultra are highly impressive. The system also includes safety precautions such as watermarks for generated images. Overall, Gemini Advanced is a powerful, efficient, and promising AI system with a strong focus on user experience and personalization.

• TheAIGRID
  How To ByPASS ALL AI Content Detectors In 2024 (Bypass Guaranteed ✅)

  In this video, the presenter introduces a tool called Hicks AI Writer which aims to humanize text generated by AI systems. The tool is designed to make AI-generated text sound more natural and less AI-like, addressing the issue of easily detectable default AI text. The presenter demonstrates how to use the tool by pasting text into the program and selecting the "humanize" option. The tool then checks the text against various websites to ensure it is not flagged as AI-generated. Different levels of humanization, such as aggressive or balanced, can be chosen depending on the desired output. The presenter highlights the effectiveness of the tool in creating more authentic and undetectable AI writing, and praises its functionality and affordability.

2024-02-07

• TheAIGRID
  Major AI News #29 - Extremely CONCERNING AI Software, GPT-4 Awaken Again, Major BenchMarks Broken..

  In the world of AI this week, Amazon CEO Andy Jassy announced the release of Rufus, a chatbot designed to provide shopping assistance to customers. Rufus is built on a large language model trained on Amazon's product catalog, customer reviews, community Q&As, and the wider web. It aims to provide personalized buying guidance and answer a variety of shopping-related questions. Jassy's announcement on Twitter sparked interest in how an e-commerce platform like Amazon is venturing into chatbot technology. In another AI breakthrough, researchers used 3D mapping and AI techniques to virtually unroll a charred 2,000-year-old scroll containing the writings of a Greek philosopher. This achievement could lead to more text recovery from ancient Scrolls. On a more concerning note, an AI system was discovered generating fake IDs with convincing images, potentially posing a significant risk to cybersecurity. The system was able to bypass identity verification checks and create fake accounts on cryptocurrency exchanges. This discovery highlights the ongoing challenge of staying ahead of AI-generated cyber threats. Microsoft's AI model, Copilot, also made headlines this week. Copilot, which combines the power of GPT-3 and GitHub's coding knowledge, showed promising abilities in generating code and assisting developers. Lastly, Google's AI image generator, based on DeepMind's technology, demonstrated impressive mid-journey levels of photo-realism. The images produced were flawed and realistic, mimicking real photographs taken with smartphones. This kind of advancement in generating realistic images poses interesting implications for various industries.

• Matthew Berman
  Zuck: "Meta AGI will be OPEN-SOURCE!" (I was wrong about Meta)

  Meta has been heavily investing in open-source artificial intelligence (AI), with Mark Zuckerberg stating that they will achieve AGI and make it open source. The company has open-sourced various products, as seen in their recent earnings call where they outlined the reasons behind their focus on open source. First, open-source software is safer, more secure, and computationally efficient due to community feedback and development. Second, open-source software often becomes an industry standard, making it easier to integrate new innovations into products. Third, open source is popular among developers and researchers, attracting top talent to Meta. Additionally, Meta has open-sourced infrastructure, such as React, PyTorch, and GraphQL, and continues to release new projects. Other companies, like Apple, are following Meta's lead in open sourcing AI projects.

• LangChain
  Self-reflective RAG with LangGraph: Self-RAG and CRAG

  In this video, Lance from Langchain discusses the use of Lang graph to build diverse and sophisticated RAG (Retrieval-Augmented Generation) flows. RAG involves retrieving relevant documents and using them as context for generating answers. Lance explains that in practice, different types of questions arise, such as when to retrieve based on the context and whether retrieved documents are good or not. To address these issues, an active RAG process is introduced, where an LLM (Language Model) decides when and where to retrieve based on existing retrievals or generations. Lance then demonstrates how to implement this using Lang graph, which provides a way to build state machines for RAG and other applications. He shows an example using the CAG (Corrective RAG) method, where documents are graded and, if needed, retrieval is performed from an external source. The resulting documents are used to generate an answer. Lance emphasizes the value of flow engineering and using Lang graph traces for analysis and debugging. Overall, he encourages viewers to explore flow engineering with Lang graph for more sophisticated RAG workflows.

2024-02-06

• MattVidPro AI
  AI is on Record Pace to Change Our World - Latest News

  In this video, the host discusses several topics related to AI. He starts by expressing his excitement about the latest achievement in open source models, specifically the smug 72b model. He believes that open source AI is the future and advocates for its accessibility to all. The host then shifts to the topic of photorealistic video object insertion, highlighting the impressive capabilities of AI in this field. He discusses the various modules used to achieve realistic object insertion and emphasizes the democratization of creativity that this technology brings. The host also mentions upcoming releases, such as the Gemini Ultra model and stable video diffusion weights, and touches on the concerns around deepfake technology and the importance of AI literacy and critical thinking in society.

• LangChain
  WebVoyager

  In this tutorial, the speaker demonstrates how to build a vision-enabled web browsing agent using a framework called L-Graph. The agent is built to perform complex tasks solely using vision and can assist in tasks such as searching for information on the web. The speaker explains the different considerations involved in building a web browser agent, such as reducing complexity and distractions to make it more efficient. The agent is designed to generate a chain of thought, make actions, and generate responses based on the user's input. The speaker also provides examples of different tasks the agent can perform, such as explaining a research paper or searching for flight information. The tutorial highlights the use of L-Smith for debugging and optimizing the agent's performance.

• LangChain
  RAG From Scratch: Part 4 (Generation)

  In this video, Lance from Langchain continues the discussion on the basic flow of the rag (Retrieval-Augmented Generation) model. The focus here is on the generation step, which involves taking the retrieved documents and storing them in the LLPM context window. Lance explains that the retrieved documents are split, embedded, and stored in a vector store for easy searchability. Similarly, the question is embedded to obtain a numerical representation. Using techniques like K-Nearest Neighbors, similar documents are identified based on proximity in a high-dimensional space. Relevant document splits are then packed into the context window, creating a prompt. This prompt is used to generate an answer using an LLPM like a chat model. Lance demonstrates this workflow using code examples. The video concludes by mentioning that future videos will explore more complex aspects of the rag model.

• LangChain
  RAG From Scratch: Part 3 (Retrieval)

  In this video, Lance from Lang chain discusses the retrieval process in the context of building a question-answering system using RAG (Retrieval-Augmented Generation). He explains the concept of indexing, where documents are split into smaller chunks and converted into numerical representations that are easily searchable. These representations are then stored in an index. When a question is given, it is also converted into a similar numerical representation, and a similarity search is performed in the index to retrieve relevant documents. Lance uses a toy 3D space as an example to demonstrate how documents and questions are embedded in this space, and documents with similar semantics are considered relevant. He also provides a code walkthrough to demonstrate the retrieval process and shows how a relevant document can be retrieved based on a question.

• LangChain
  RAG From Scratch: Part 2 (Indexing)

  In this video, Lance from LangChain focuses on indexing in the context of building a retrieval system from scratch. He explains that indexing involves loading external documents into a retriever and establishing relevance or similarity using a numerical representation. Two approaches to create numerical representations are discussed: sparse vectors, which use word frequency, and embeddings, which compress documents into fixed-length vectors that capture semantic meaning. Lance demonstrates how to compute the number of tokens in a question and then uses OpenAI embeddings to create vector representations for the question and documents. He also shows how to store and retrieve documents using the vector store.

• LangChain
  RAG From Scratch: Part 1 (Overview)

  The speaker, Lance from Lang chain, introduces the new series called "RAG from Scratch" that will cover the basic principles of Rag and progress to advanced topics. The motivation behind Rag is that pre-training LMs do not include all the data one may need, such as private or recent data. Additionally, LMs have limited context windows, so connecting them to external data is crucial. Rag follows a three-stage process: indexing external documents for easy retrieval, feeding the retrieved documents into an LM, and generating an answer based on the retrieved information. This video serves as an introduction, with future videos diving into specific topics in more detail. A code walkthrough is also provided, demonstrating the implementation of Rag.

• Matthew Berman
  Apple Vision Pro is the ULTIMATE AI TROJAN HORSE

  The Apple Vision Pro is an impressive device with some noticeable flaws. The purchasing experience was excellent, with personalized fitting and a polished demo. The device is intuitive and easy to use, with accurate vision tracking. However, it takes some time to put on and start up, and there is no way to save previous windows, which can be frustrating. Typing is decent but not as fast as using a physical keyboard. Some key apps like Netflix, Spotify, and Gmail are missing, although workarounds exist. The immersion is great, with stunning visuals and impressive sound quality. The device is ideal for content consumption and work tasks. Overall, while there are some quirks and limitations, the Apple Vision Pro represents the future of computing and has great potential.

• Google DeepMind
  Using AI to help blind and partially-sighted people perceive the world

  Google's Lookout app has introduced a new feature called Image Question and Answer, which uses AI to help blind and visually impaired individuals understand the world around them. By uploading a photo, users can ask questions about it to receive more information. For example, they can inquire about the description of a temple, its colors, or even the text within the image. The AI model behind this feature has been trained to provide specific descriptions. The goal is to make the app inclusive and useful for blind and visually impaired individuals in various aspects of their daily lives, from navigating new places to assisting with tasks like sorting laundry.

• Google DeepMind
  [AUDIO DESCRIBED] Using AI to help blind and partially-sighted people perceive the world

  Lookout, an app by Google, uses AI to help blind and partially sighted people perceive the world. Users can upload images and ask questions to learn more about what they are looking at. The app provides specific descriptions of images, such as the colors, objects, and details present. It can also read out text and provide details about points of interest. Users express excitement and appreciation for the app, as it allows them to feel included and engaged in conversations about pictures. Lookout can be used for various tasks, making everyday activities easier for visually impaired individuals. The app is powered by Google Deep Mind and aims to provide the most useful information to its users.

2024-02-05

• TheAIGRID
  This Custom GPT Changes EVERYHING (VideoMakerGPT) Creates Videos IN SECONDS

  The speaker introduces a new GPT called Video Maker by Nvidia AI, which can generate complete videos with engaging scripts, background music, subtitles, and a realistic human-sounding voiceover. To access the GPT, users can either scroll down to the productivity section in the GPT store or search for "inVideo" in the store. The speaker demonstrates the effectiveness of the software by sharing videos they created using different prompts and customizations. They emphasize that a ChatGPT Plus subscription is required to use the GPT store and highlight the ease and speed of generating videos with the software. The speaker also discusses the potential for AI video editing to revolutionize the future of content creation.

• LangChain
  LangGraph: Persistence

  In this video, the speaker demonstrates how to add persistence to L graph agents using a checkpoint method in L graph. By saving the state of the graph at each iteration, it allows agents to resume from the same state, making it useful for maintaining memory in conversations. The video provides an example of how to do this, using OpenAI TAVIL and LanguaSmith keys. A simple message graph agent is created, which determines whether to call a function or continue based on the messages. The graph is compiled with a specific checkpoint, connecting to an in-memory SQLite database. By passing in a thread ID, conversations can be resumed from the same state. The speaker explains that this method can also be applied to the state graph for saving other aspects of state.

2024-02-04

• Two Minute Papers
  NVIDIA’s New Gaming AI Does The Impossible!

  A new AI technology has been developed that can take real video footage of tennis players and recreate their motions in a computer game without the need for motion capture equipment. The AI uses the raw video feed to estimate the players' motion and then builds a computer simulation that reproduces this motion in a more precise and realistic way. The simulation can simulate different types of shots and even learn the individual style of famous players. The system has been able to achieve high hit rates and has been showcased at the prestigious SIGGRAPH conference. This technology could potentially revolutionize the future of video games.

• Yannic Kilcher
  Lumiere: A Space-Time Diffusion Model for Video Generation (Paper Explained)

  Google Research has developed a model called Lumiere that can generate videos based on text prompts. The model takes in the text and hallucinates every pixel in the video frame. It can generate videos with minimal motion or dramatic changes, such as camera pans or fisheye lenses. The model can also generate videos in different styles by swapping out pre-trained weights. Lumiere is built on top of a pre-trained text-to-image model and uses a cascaded architecture to achieve global consistency in the generated videos. It also includes a spatial super-resolution network to upsample low-resolution frames. The model was trained on a dataset of 30 million videos with text captions. Evaluation results show that Lumiere outperforms baseline models and is preferred by human evaluators. However, the paper lacks details regarding the training process and model specifications.

• TheAIGRID
  Shocking Report Shows Why AI WONT Take Your Job (New Report)

  A recent report from MIT suggests that AI is unlikely to steal jobs in the near future due to the high cost of AI systems and the need for customization. The researchers focused on Vision-related tasks and found that only 23% of worker compensation exposed to AI computer vision would be cost-effective for firms to automate. Even with cost reductions of 20% per year, it would still take decades for computer vision tasks to become economically efficient. However, there are factors that the report didn't discuss, such as advancements in AI development that may accelerate cost reduction. Additionally, societal acceptability and the preference for human interaction are obstacles to AI adoption. Overall, while the future of work with AI is uncertain, humans are still valued in many industries and customization is crucial for successful AI integration.

2024-02-03

• TheAIGRID
  Major AI News #28 - Sam Altman's Surprising Comment, Gemini Ultra Release Date, AGI "Achieved?"

  This week in AI news, tech companies are reportedly slashing thousands of jobs as they invest more in AI. SAP, a German software giant, announced plans to invest over $2 billion in integrating AI into its business and is restructuring 8,000 roles. However, the layoffs are not solely due to AI advancements, as the current economic environment and changes in interest rates also contribute to the job cuts. Additionally, there are rumors of a leaked open-source AI model nearing GPT-4 performance, showing that leaks on platforms like 4chan are possible. Google Research introduced mobile diffusion, a text-to-image generation model that can run on-device, potentially revolutionizing online shopping. Microsoft Bing and Meta released updates to their AI models, with improved answer quality and accelerated progress in the field. Lastly, a claim of achieving AGI was made, but skepticism and lack of proof surround the claim.

2024-02-01

• TheAIGRID
  Googles New "Text To IMAGE Model" Just CHANGED Everything (Now RELEASED!)

  Google has released its most advanced text to image technology, called Imagen 2. This new text to image generator is considered one of the best available, with a focus on photo realism. Google has implemented the technology into its website, making it easy to use. It is currently available in most countries, except for some European areas. Imagen 2 includes key features such as photo realism, intuitive editing, and text rendering support. It also has built-in safety precautions, including invisible watermarks, to ensure responsible AI practices. The technology has been compared to other models like Darli 3, with Google's Imagen 2 showing impressive results. Overall, Google's Imagen 2 is regarded as a game-changer in text to image generation.

• LangChain
  Open Source RAG with Nomic's New Embedding Model (and ChromaDB and Ollama)

  In this video, Lance from Lang chain walks through the process of building a Retrieval-Augmented Generation (RAG) app using the NX model for context embedding. He explains that the expansion of context windows for language models is an interesting trend, allowing for larger inputs and better performance. Lance demonstrates how to use the NX model from scratch by loading documents, splitting them into chunks, and encoding them using the Nx embedding model. He then shows how to store the embeddings in a vector store and use an open-source language model (LLM) to retrieve relevant documents and generate answers. Lance also introduces Lang serve, which allows the app to be deployed and accessed via HTTP endpoints with an interactive UI.

• MattVidPro AI
  Finally! First Look at Google's New Imagen 2 & Image FX Interface!

  Google's AI Test Kitchen has introduced a new AI image generation interface called Image Effects. The interface allows users to generate high-quality and realistic images by inputting different prompts. The images generated are impressive in terms of photo realism and accuracy. The interface also offers automatic suggestions for prompt changes, making the interaction more creative and exploratory. However, there are strict policies in place, and certain prompts are blocked. The model seems to excel in generating images of famous characters, such as Sonic the Hedgehog and Bowser, with impressive coherency. While the model's fine detail capabilities are limited, overall, Image Effects shows promise as an alternative AI image generator. Access to the interface can be obtained through the AI Test Kitchen website.

• NVIDIA
  Accelerating AI and VFX Workloads with CoreWeave and NVIDIA

  The speaker discusses the challenges faced by the visual effects industry, including tighter budgets, deadlines, and demands for content with limited resources. They highlight the benefits of using Conductor and Coolweave, which leverage GPU computing and the partnership with Nvidia to provide cost-effective rendering at a massive scale in the cloud. The speaker also mentions the increasing convergence of visual effects and artificial intelligence, and how Nvidia's L4s data center accelerator caters to both markets, allowing customers to power visual effects graphics as well as AI use cases. With early access to Nvidia's technology, customers have been able to train large, complex AI models efficiently. Using Conductor and Coolweave, artists can iterate on shots more quickly, leading to efficient use of time and resources. The speaker emphasizes the limitless possibilities enabled by this technology.

• Matthew Berman
  New LEAKED Info About Apple's AI Strategy 🍎

  Apple is rumored to be making significant strides in the field of artificial intelligence (AI) and is aiming to integrate it into Siri. The tech giant's AI Chief, John Giannandrea, who has a strong background in the industry, has been leading a team working on conversational AI for the past four years. Leaked information suggests that Apple is testing its own AI called Apple GPT internally. Apple is also said to be spending millions of dollars per day on conversational AI research. The company aims to create a feature that would allow Siri to automate multi-step tasks and perform functions currently accomplished through shortcuts. Apple is reportedly approaching media companies for possible AI deals and is expected to have a generative AI feature available on iPhones and iPads by late 2024.

2024-01-31

• Matthew Berman
  LLaVA 1.6 Released! #ai

  Lava 1.6 has been released, offering improved reasoning, OCR capabilities, and access to a wealth of knowledge. It supports high-resolution inputs, offers better performance than Gemini Pro on multiple benchmarks, and includes various base multimodal language models (LLMs) such as Mell 7B, Munia 7B, 13B, and Hermes e 34B. Additionally, Lava 1.6 is compatible with the AMA plugin, enabling easy integration with your AI image interpretation needs. To get started, downloading the latest version from the specified website is straightforward, followed by running the code provided. Explore the enhanced features of Lava 1.6 today.

• TheAIGRID
  Nvidias NEW "AI AGENT" Will Change The WORLD! (Jim Fan)

  In a recent TED Talk, Jim Fan, a senior research scientist at Nvidia, discussed the future of AI agents, specifically focusing on the concept of a "foundation agent." This agent would be able to seamlessly operate across both virtual and physical worlds, fundamentally changing our lives in areas such as video games, metaverse, drones, and humanoid robots. Fan explained that the foundation agent would not be the same as AGI (artificial general intelligence), but rather a versatile, multi-functional AI that can master skills across different realities. He also discussed research papers, such as Voyager, which demonstrated the ability of AI agents to master complex tasks in Minecraft. Fan highlighted the importance of video models and simulations in training these agents, and how they can help overcome data limitations and improve their performance in real-world applications.

• MattVidPro AI
  Our Future is WILD! AI Advancements that Get Me EXCITED!

  In this video, the host discusses recent developments in the field of artificial intelligence (AI) that have caught his attention. He highlights a new feature in Chat GPT that allows users to bring any GPT model into a conversation, providing context and verification for information. The host demonstrates how adding different GPT models can influence the conversation. He also mentions Meta AI's release of Code Llama 70b, an open-source code generation model that can improve AI coding capabilities. Additionally, he discusses an AI model called FANET, which can enhance videos by increasing resolution and reducing motion blur. The host also mentions a study that suggests large language models have distinct neural activity when generating sentences. Lastly, he mentions Morpheus-1, the world's first multimodal generative ultrasonic transformer, designed to induce and stabilize lucid dreams. The host expresses his excitement for these advancements and the possibilities they may bring in the future.

• Two Minute Papers
  Google’s New AI Just Made A Movie!

  Google's new text-to-video AI has impressive capabilities. It has been trained on 10 billion video tokens and can generate minute-long movies based on text snippets. What sets this AI apart is its ability to create longer videos and ensure that the sounds align with the motions in the video. It also allows for controllable and interactive video editing, where users can provide prompts or images to direct the desired output. The AI can even synthesize new content in a zero-shot manner, producing results it hasn't seen before. The speed of generating videos is also noteworthy, with one second of video being produced every 4-5 seconds. While there are limitations, such as resolution, this AI has tremendous potential and hints at even better video generation capabilities in the future.

• LangChain
  OpenGPTs

  Open GPTs is an open-source project developed by Linkchain that replicates the functionality of GPT-based language models. It provides an end-user-facing interface to create different types of bots with access to various tools and files. The platform offers three types of bots: an assistant bot, a retrieval bot, and a chat bot. The assistant bot is the most powerful, allowing arbitrary instructions and multiple tool usage. The retrieval bot focuses on retrieving information from uploaded files while the chat bot responds based on custom instructions. The project is built on L-Graph, a cyclical agent framework. The backend architecture uses configurable agents and alternatives to enable easy configuration and flexibility. The platform also integrates with Lang Smith, providing traceability and feedback functionality. Future plans include improving the retrieval process and expanding capabilities for handling multiple bots.

• Matthew Berman
  META's New Code LLaMA 70b BEATS GPT4 At Coding (Open Source)

  Meta has released Code Llama 70b, its most powerful coding model to date and one of the most powerful coding models available. The model is available for download and comes in three versions: the base model, a Python-specific version, and an instruct version fine-tuned for understanding natural language instructions. Code Llama 70b achieves high performance and is available for both research and commercial use. Moreover, Meta has announced that Code Llama 3 will be released soon. Other developers have also released fine-tuned versions based on Code Llama 70b, such as SQL Coder 70b, which outperforms all publicly accessible language models for Postgres text-to-SQL generation. The video demonstrates testing the Code Llama 70b model by attempting to build a Snake game, although the attempt is unsuccessful.

2024-01-30

• MattVidPro AI
  AI Facetuning is INCREDIBLE! Let's install it Locally for FREE! | Photomaker

  In this video, the creator introduces the viewer to Photomaker, an AI art program that is free and open source. They explain that Photomaker allows users to input a reference image of a face, and the program can place that face in various situations. The video walks through the process of installing the program locally using Pinocchio, a platform that runs AI locally on the user's computer. The creator mentions that the Pinocchio platform requires a computer with a minimum of 8GB of video memory and is compatible with both Nvidia and AMD graphics cards. Once installed, Photomaker offers a range of customization options for generating AI images of humans. The creator showcases several examples, including transforming their own image into a lemon farmer, and testing the program's versatility by converting Barack Obama into a baby. Overall, the tutorial emphasizes the ease of installation and the creative possibilities offered by Photomaker.

• TheAIGRID
  Major AI News #27 - Sam Altmans AGI Shocker, Apples ChatGPT Update, Gemini Pro's New Features...

  In the world of artificial intelligence this week, there were several updates and developments worth noting. One of them was the launch of a website for the AI model Mid Journey, which is currently in its testing phase. Access to the website is limited to those who have generated over 10,000 images. Additionally, there were updates to the Mid Journey software, including new features like the ability to run variations of images and a heart button to easily like images. Another interesting development was the release of a video demonstrating how AI can be used to create deepfakes of people, which sparked concerns about the accessibility and potential misuse of this technology. NBC also reported on the use of deepfake robo-calls during the New Hampshire primary elections, highlighting the potential risks of such manipulation. Google's AI model, B, made a significant leap in performance, surpassing GPT-4 Turbo to secure the second spot on a leaderboard based on human evaluations. Google also announced upcoming features for B, including image generation and multilingual support. Other notable news includes a new requirement for developers of major AI systems in the US to disclose their safety test results to the government, Apple testing its own AI model called Ajax with the help of ChatGPT, and the introduction of generative AI features in Chrome, such as smart tab organization and AI-generated background themes.

• Matthew Berman
  FINALLY! Open-Source "LLaMA Code" Coding Assistant (Tutorial)

  In this video, the presenter introduces a local coding assistant called Cod, powered by the open-source model Code Llama. The presenter demonstrates how to set up and use Cod, which is an extension for Visual Studio Code. By default, Cod uses GPT-4, but the presenter shows how to configure it to use Code Llama for local autocompletion. The presenter showcases various features of Cod, including generating code snippets, autocompleting existing code, adding documentation, editing code with instructions, explaining code, and generating unit tests. Overall, Cod is presented as a powerful and versatile coding assistant that offers more functionality than GitHub Copilot, with the added benefit of local autocompletion using Code Llama.

• TheAIGRID
  Prophetic's New "Mind Control AI!" SHOCKS Everyone! (Morpheus -1)

  Prophetic AI has developed Morpheus One, the world's first multimodal general ultrasonic Transformer that can induce and stabilize lucid dreams. The device uses brainwave data and sound waves to stimulate the brain and create lucid dreaming experiences for users. The technology aims to provide a way for individuals to control their dreams and explore the state space of human consciousness. The hardware consists of EEG sensors, ultrasound transducers, a neural chip, and a battery, all contained within a headset. The company believes that this technology has potential applications beyond lucid dreaming, including inducing focus, positive mood, deep meditation, and other conscious experiences. The non-invasive nature of the device makes it more accessible compared to other brain computer interfaces like Neuralink. The company plans to release a fully functioning prototype in March and invites users to sign up for beta testing.

2024-01-27

• Two Minute Papers
  NVIDIA’s New AI: 50x Smaller Virtual Worlds!

  In today's video, Dr. Károly Zsolnai-Fehér discusses several groundbreaking AI techniques. The first technique, NERFs, allows for the creation of virtual worlds by stitching together photos, with the quality and size being important factors. Another technique involves sculpting images by converting people or objects into 3D models and applying various transformations. The third technique allows for artistic direction in existing images, creating videos based on instructions for movement and gestures. Lastly, an AI technique is showcased that creates virtual characters with mouth movements and gestures based on audio input, although there are still challenges to overcome. Overall, these breakthroughs demonstrate the potential of AI in creating immersive virtual experiences.

2024-01-26

• NVIDIA
  Reinventing Retail with AI | I AM AI

  This video is a promotional message highlighting the capabilities of AI brought to life by Nvidia and inspired minds. It emphasizes the endless possibilities that AI brings to various aspects of life, including delivering on promises, predicting what comes next, simulating environments, and simplifying everyday tasks. The AI is portrayed as an assistant that anticipates every need and responds to real-time demands, ultimately aiming to deliver a better future for everyone. The video showcases the role of AI in guiding us to better answers faster and helping us reimagine our perfect home, implying that AI has the potential to transform, improve, and simplify various aspects of our lives.

• AI Explained
  GPT-5: Everything You Need to Know So Far

  OpenAI is believed to have launched the full training run of GPT-5. This speculation is based on various clues, including tweets from OpenAI's president and a top researcher. It is suggested that OpenAI is scaling its computing resources and training its biggest model yet. GPT-5 is expected to have increased parameters, improved capabilities, and the ability to think for longer by laying out reasoning steps. It is also predicted that GPT-5 will be released towards the end of November 2024, after several months of training and safety testing. The release may involve different checkpoints and functionalities. OpenAI aims to improve real-time voice interaction, incorporate multilingual data, and enhance reasoning abilities. However, the full impact of GPT-5's release remains uncertain, and safety testing will be crucial.

• TheAIGRID
  Chinas New "KEPLERBOT" Surprises Everyone! (Tesla bot Competitor)

  The Kepler bot from Kepler Robotics is a humanoid robot that is set to compete with Tesla's bot. The robot comes in three versions - outdoor tasks, hazardous environments, and another outdoor tasks version. It is equipped with AI technology, bionic body structure, and bipedal walking. The robot's hands are designed to mimic the intricate structure of human hands, with 12 degrees of freedom for precise force sensing and hand dexterity. The robot also has a self-developed nebula system for enhanced perception of the surrounding environment, with features like visual recognition, autonomous navigation, and multimodal interaction. The pricing for the Kepler robot is rumored to start around $30,000 to $20,000, which could make it more accessible to the consumer market.

• LangChain
  Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve

  In this tutorial, Eric from Lang chain demonstrates how to build a search-enabled chatbot using EXA. He starts by explaining the main software components you'll need, including Lang chain, EXA, Lang Smith, and Lang serve. Eric then shows how to build the chatbot using a Jupyter notebook, using the Lang chain and EXA libraries. He outlines the steps of the retrieval and generation processes, manipulating the input and formatting the prompts for the llm-powered chatbot. He also emphasizes the importance of setting environment variables for API keys. Eric then demonstrates how to debug and observe the process using Lang Smith. Finally, he shows how to convert the chatbot into a Lang serve application and deploy it using hosted Lang serve. The tutorial concludes by testing the chatbot in the hosted playground. Overall, Eric provides a comprehensive guide to building a search-enabled chatbot with Lang chain and EXA.

• Matthew Berman
  GPT-4 Vision + Zapier + MindStudio (INSANE Automations)

  In this video, the presenter demonstrates how to use Mind Studio, a platform powered by AI, to automate the process of uploading handwritten meeting notes, interpreting the content using AI, converting it to text, and distributing the notes to meeting attendees. The presenter starts by setting up the automation in Mind Studio, using nodes for user input and AI analysis. They then integrate Zapier to send the transcribed text to email addresses. The process involves creating a Zap using webhooks and the Zapier integration in Mind Studio. The final step involves providing feedback to the user, confirming that the email has been successfully sent. The presenter highlights the potential to customize the automation further by collecting email addresses within Mind Studio.

• TheAIGRID
  GPT-4's New "Memory" Feature Is Stunning (ChatGPT Memory)

  In this video, the host discusses some secret features that have been added to Chat GPT. These features include personalization and memory management. The personalization aspect allows Chat GPT to tailor responses based on details and preferences it remembers about the user. The memory management feature shows users the details and preferences that Chat GPT has picked up on in conversations. Users can edit or delete this information if it is incorrect. The host believes that OpenAI is gradually updating Chat GPT to make it more customizable and personalized. They emphasize the importance of paying attention to these updates, as they show the direction in which AI systems are heading. The host also explains how these features will make AI systems more useful and powerful.

2024-01-25

• TheAIGRID
  OpenAI Finally Introduces NEW MODELS! (Updated GPT-4) + Leaked Updates

  OpenAI has released updates to their base model, including GPT 3.5 and GPT 4 Turbo. GPT 3.5, which is the free model, has been upgraded to improve accuracy in responding to requested formats and fix bugs. The pricing for GPT 3.5 Turbo has been reduced by 50% for input prices and 25% for Alpha prices. GPT 4 Turbo has been updated to reduce cases of laziness and incomplete task completion. The updated model is expected to perform better in code generation tasks. OpenAI also introduced an updated moderation model and new ways to understand API usage and manage API keys. Future features may include the ability to mention multiple GPTs in a conversation for improved workflow.

• MattVidPro AI
  Google Casually Drops the Best AI Video Generator We've Ever Seen

  Google has released a new AI video generator called Lumiere, which showcases impressive capabilities in text-to-video, image-to-video, stylized generation, cinemagraphs, and video editing. The generated videos have excellent movement and realism, surpassing other video generators currently available. While some examples may be cherry-picked, the overall quality is highly impressive. The model achieves global temporal consistency and uses spatial and temporal upsampling to generate full-frame low-resolution videos. This advancement in AI video generation has significant potential for content creation and video editing. It is expected that Lumiere will be released as a product in 2024, providing competition for existing video generators and potentially improving the market for consumers.

• MattVidPro AI
  Generate Private AI Videos Locally on your Computer!

  In this video tutorial, the host demonstrates how to install local AI video generation on your computer for free. He focuses on the Gigabyte Aorus 17x gaming notebook, which is capable of handling the entire YouTube recording setup. The tutorial covers the installation of stable video diffusion, a video generation model capable of producing realistic videos. The host explains the minimum requirements for running the model and guides Windows users through the installation process using Pinocchio software. He emphasizes the simplicity and ease of the installation process and mentions that while stable video diffusion is only compatible with Nvidia GPUs, Pinocchio can run on different machines, including Macs and Linux. The host showcases the process by generating videos from different images and shares his thoughts on their outcomes. The tutorial concludes with a thank you to the sponsor, Gigabyte, for supporting the video.

2024-01-24

• Anthropic
  Robin AI, powered by Claude

  Richard Robinson, CEO and founder of Robin AI, explains that their mission is to simplify contracts for everyone using artificial intelligence. Traditionally, lawyers would spend extensive time reviewing and renegotiating contracts, resulting in a lengthy process. Through their technology, Robin AI, in collaboration with anthropic's LLM, speeds up this process by 8 to 10 times. Robinson emphasizes the importance of safety, security, and trust for their users, as their data must be protected. They have integrated anthropic's model, Claude, into their AI Persona Robin to enable lawyers to work alongside AI in contract workflows. Robinson dreams of a future where their system is used by everyone, with their AI technology combined with a deep understanding of the legal industry to assist with any legal problem.

• LangChain
  Streaming Events: Introducing a new `stream_events` method

  In this video, the speaker discusses the importance of streaming in language models (LMs) and introduces a new method called stream events in LangChain. The speaker explains that streaming is important for providing a better user experience, especially when working with complex chains or agents. Stream events allow for streaming the intermediate steps and events that happen within a chain, such as the input and output of tools being called. The speaker also demonstrates how to use the stream and a stream methods to stream the final outputs of chains or models. They provide examples using various LMs, chains, and tools to illustrate the streaming functionality. Additionally, the speaker explores streaming with agents using the agent executor, as well as streaming with LGraph, a package built on top of LangChain. The video concludes by highlighting that stream events is currently in beta and feedback is welcome.

• Two Minute Papers
  DeepMind’s AlphaGeometry AI: 100,000,000 Examples!

  A recent Google DeepMind paper proposes a system that allows AI to compete in the International Mathematical Olympiad (IMO), one of the most prestigious math competitions in the world. The paper highlights the difficulty of solving such problems that require planning, logic, reasoning, and innovative thinking. The proposed AI, called GPT-4, demonstrates the ability to solve complex mathematical problems by finding key ideas (the "rabbit") and performing the necessary calculations (the "green" part) to reach a solution. The AI, which learned from scratch without human intervention, performs at a similar level to the average IMO contestant and even outperforms some of the smartest individuals when employing creative thinking ("pulling the rabbit out of the hat"). The paper is open source, allowing others to experiment with the system, and suggests potential applications in other problem domains.

2024-01-21

• Yannic Kilcher
  AlphaGeometry: Solving olympiad geometry without human demonstrations (Paper Explained)

  In this video, the presenter discusses a paper by Google DeepMind that introduces the Alpha Geometry model, which focuses on solving math Olympiad geometry problems without human demonstrations. The paper presents a neuro-symbolic system that combines trained language models and symbolic solvers for proof search in geometry problems. The challenge lies in the construction of auxiliary points or objects, which are not initially present in the problem. The Alpha Geometry model addresses this challenge by using a language model to suggest new constructions, which are then used in the proof search. The language model is trained on a specific domain-specific language for mathematics and is fine-tuned on proofs with auxiliary constructions. The results show that the Alpha Geometry model can solve a significant number of math Olympiad problems, but its effectiveness outside of this specific domain remains to be explored.

• Two Minute Papers
  Simulating a Virtual World…For 500 Years!

  In this video, Two Minute Papers with Dr. Károly Zsolnai-Fehér discusses a paper that presents a simulation of an ecosystem with up to 500,000 plants for 500 years. The simulation explores various phenomena including transpiration and cloud formation, as well as the effects of deforestation and decreasing precipitation. The paper demonstrates how changes in the ecosystem can lead to tipping points and irreversible, catastrophic changes. It also shows how different species adapt and compete in response to changing conditions, forming unique patterns. The simulation results align with theoretical predictions and real-world observations, highlighting the accuracy of the model. The video emphasizes the significance of the paper and encourages viewers to explore it further.

2024-01-19

• NVIDIA
  NVIDIA DRIVE Partners Showcase Cutting-Edge Innovations in Automated and Autonomous Driving

  The automotive industry is currently undergoing significant changes, with cars becoming more software-driven and autonomous driving becoming more feasible. This progress is made possible through advancements in computing power and the ability of vehicles to sense and understand the world around them. Nvidia, a company known for its high-performance hardware accelerators, is playing a key role in this development. By partnering with Nvidia, automakers can access powerful computing platforms that enhance their autonomous technology and improve safety. The use of Nvidia's technology extends beyond vehicles themselves, as it is also utilized in cloud infrastructure and simulation tools for the development and verification of autonomous systems. This collaboration is set to revolutionize the automotive industry and make driving safer and more efficient.

2024-01-18

• AI Explained
  Alpha Everywhere: AlphaGeometry, AlphaCodium and the Future of LLMs

  Google Deep Mind has released Alpha geometry, a neuro-symbolic system that combines a neural network with pre-programmed symbolic systems. While Deep Mind's leaders see this as a step toward AGI, the team cautions against overhyping it. Alpha geometry performed almost as well as the average gold medalist in the International Math Olympiad for a subset of geometry problems. The system uses language models to propose constructs and symbolic systems to solve problems, iterating until a solution is found. Deep Mind plans to open-source the code and model within a year. Additionally, Alpha codium, an open-source rival to Alpha code, has been released. Both Alpha geometry and Alpha codium highlight the growing alliance between language models, search, idea generation, and brute force in AI.

2024-01-17

• Two Minute Papers
  NVIDIA Is Supercharging AI Research!

  In this video, Dr. Károly Zsolnai-Fehér discusses how AI research is impacting various industries. He highlights NVIDIA's HybridAI approach, where local graphics cards and cloud computing work together. He demonstrates the use of generative AI in creating virtual characters that can engage in realistic conversations and even perform actions. The video also mentions advancements in gaming with AI-based ray tracing and remastering old games. NVIDIA's new series of graphics cards and RTX laptops are introduced as well. AI is shown to have a significant impact on robotics, enabling robots to understand commands better and train in virtual environments for real-world deployment. The video concludes by emphasizing the transformative capabilities of AI in fields like agriculture, construction, healthcare, and retail.

2024-01-14

• Two Minute Papers
  ChatGPT: 4 Game-Changing Applications!

  ChatGPT, the large language model assistant, is capable of understanding both text and images, bridging the gap between the two. With GPT-4's vision model, it can perform tasks in the real world by taking commands and making plans. It demonstrates its abilities through experiments like retrieving a can of coke from a fridge, safely storing a Marvel model behind glass, and organizing sushi pieces according to a provided image. ChatGPT can learn in computer simulations before operating in the real world, and it can perform a wide range of tasks without specific training. Although it relies on prompts and exemplars for reasoning, it can assist in various domains such as writing video games, explaining mathematical concepts, and organizing files. This development marks the potential birth of an incredibly useful tool.

2024-01-13

• Yannic Kilcher
  Mixtral of Experts (Paper Explained)

  The video discusses the Mixr of Experts model, which is built on the MISTL 7B architecture. Although the paper does not disclose the source of the training data, it is considered a smart choice to avoid the criticisms and legal issues surrounding data bias. Mixr of Experts is an open-source approach released under the Apache License by MISTL AI, a startup based in France. The model features a sparse mixture of experts with open weights, outperforming other models on various benchmarks. It implements expert routing, where each token is only sent to a subset of experts, resulting in a lower parameter count per token. The model achieves faster inference speed and higher throughput by distributing the experts across different GPUs.

2024-01-12

• AI Explained
  OpenAI Flip-Flops and '10% Chance of Outperforming Humans in Every Task by 2027' - 3K AI Researchers

  In this video, the speaker covers four developments in the AI world. First, there is a discussion about OpenAI's change in stance regarding engagement. They initially aimed to maximize engagement but are now considering the negative effects of addictive technology. Second, there is a mention of the GPT store and how OpenAI plans to monetize the models based on user engagement. Third, the speaker talks about OpenAI's plans to build superintelligence and the potential contradiction in their vision. Lastly, the speaker summarizes the findings of a recent survey of AI researchers, highlighting their predictions of the future of AI. The survey reveals that AI researchers believe there is a 10% chance that machines will outperform humans in every task by 2027 and a 50% chance by 2047. The researchers also foresee an acceleration of technological progress within the next five years.

2024-01-10

• Yannic Kilcher
  Until the Litter End

  In this video, the creator announces that they are shutting down the Litter social network due to financial constraints. They share that they have put up a website where users can access all the posts that were ever made on the platform, which includes variations of pictures, memes, and other user-generated content. They mention that they encountered rate limit issues with OpenAI's Vision preview API, which limited the number of posts they could process. The creator reveals that they spent approximately $160 on OpenAI and other subscriptions, but only made $30 in ad revenue. They express interest in securing venture capital funding and assure users that they may revisit the project in the future. The creator ends the video by thanking everyone for participating and mentioning a potential future iteration of the platform.

2024-01-09

• Two Minute Papers
  Growing 60,000 Tree Roots In 3 Seconds!

  In this Two Minute Papers video, Dr. Károly Zsolnai-Fehér talks about the fascinating world of simulating virtual trees and ecosystems. He showcases various research papers that delve into simulating the movement, growth, and adaptation of trees in virtual environments. The simulations include factors such as root systems, environmental stimuli, soil types, and growth resistance. The simulations are incredibly realistic and mirror the structures and properties of real trees. The computational power required for these simulations is surprisingly low, allowing for the simulation of thousands of roots in seconds. Dr. Zsolnai-Fehér emphasizes the importance of showcasing computer graphics research, as it is often overshadowed by AI research. He encourages viewers to subscribe to his channel for more updates on these exciting papers.

2024-01-08

• NVIDIA
  Generative AI for Drug Discovery and Design

  Phenom beta is an AI drug discovery tool developed by Recursion, a leading company in the field. It uses deep learning to create a representation of a cell and allows scientists to observe a cell's response to disease pathways. By analyzing a large and diverse library of cell images, Phenom beta can identify effective drugs and understand the associations between genes and compounds. This tool provides researchers with a way to unravel the complex biological pathways and mechanisms involved in drug discovery, surpassing the limitations of traditional image analysis methods. Phenom beta is now accessible through the Nvidia Bono Cloud API, providing a new foundation model for target and hit discovery in the field of biology.

• NVIDIA
  NVIDIA Special Address at CES 2024

  At CES 2024, NVIDIA showcased their latest advancements in graphics, gaming, and robotics. They highlighted the power of their GeForce RTX GPUs, which have become a staple for gamers and creators worldwide. NVIDIA emphasized the role of AI in gaming, particularly in real-time ray tracing and deep learning. They also introduced the concept of generative AI, which has applications beyond gaming, such as creating AI-powered game characters and AI-assisted conversations. NVIDIA announced partnerships with Convai and Orbifold Studios to bring generative AI to gamers and modders. In addition, they unveiled new RTX games, the Enhanced Broadcasting feature for Twitch streamers, and their latest lineup of SUPER series GPUs. NVIDIA also discussed their NVIDIA Isaac platform for AI-powered robots, highlighting the infusion of generative AI into robotics for improved efficiency and deployment.

2024-01-07

• Yannic Kilcher
  LLaMA Pro: Progressive LLaMA with Block Expansion (Paper Explained)

  This video discusses a paper called "Llama Pro: Progressive Llama with Block Expansion". The authors propose a method to expand the capabilities of the Llama large language model by adding new layers to it. The goal is to enable continuous learning while preventing catastrophic forgetting. The authors compare the performance of the original Llama model to the expanded Llama Pro model on various tasks, such as coding and math benchmarks. They show that the Llama Pro model performs better on these tasks, while still maintaining its abilities on the original tasks. The method involves duplicating certain layers and fine-tuning them while keeping the rest of the model frozen. The video highlights some potential concerns with the approach, such as the need for significant overlap between the old and new data sets. Overall, the paper provides a promising technique for enhancing the capabilities of language models.

• Two Minute Papers
  New AI Makes Everybody Dance!

  In this video, Dr. Károly Zsolnai-Fehér discusses several advancements in artificial intelligence (AI). He highlights how AI can now generate dance videos based on text prompts, eliminating the need for a personal video. He also discusses a new technique by NVIDIA that improves the quality of low-bandwidth streamed gaming videos, reducing compression artifacts. Additionally, he explores a paper that attempts to teach an AI to "smell." By providing molecule structures as input, the AI can predict and differentiate various scents as well as a human can. While the AI does not physically smell, it demonstrates an impressive ability to understand and categorize smells. Overall, these advancements showcase the incredible capabilities of AI technology.

2024-01-04

• Two Minute Papers
  This Is Ray Tracing Supercharged!

  In this video, Dr. Károly Zsolnai-Fehér discusses two different advancements in computer graphics. The first is a noise filtering algorithm that improves the quality of photorealistic images generated through light transport simulations. The new technique significantly reduces noise and produces cleaner, more accurate images compared to previous methods. The second advancement is in displacement mapping, which enhances the detail and appearance of simple geometry in games and virtual worlds. This new technique is not only faster than previous methods but also requires less memory. Additionally, the video highlights a real-time technique for simulating light transport and encourages viewers to contribute to LuxCoreRender, a free and open-source renderer.

2024-01-02

• Yannic Kilcher
  I created an AI-powered Social Network

  The Latent Twitter Litter is a unique social network that transmits the essence of what users post rather than the actual content itself. The process starts with the user posting a message, which then gets transformed into a visual representation by OpenAI's image creation API. This image is then described by OpenAI's gp4 Vision model and converted back into a social media message. The result is a condensed and visually enticing representation of the original post. The same process can be applied to images, where they are transformed into captions and then converted back into images. This innovative concept is seen as a way to extract the core ideas from communication, removing the need for exact word choices and repetitive images.

2024-01-01

• AI Explained
  4 Reasons AI in 2024 is On An Exponential: Data, Mamba, and More

  In this video, the speaker discusses four clear reasons why AI is expected to continue improving rapidly in 2024. The first reason is the importance of data quality in maximizing the performance of AI models, which is still far from being optimized. The second reason is the emergence of new architectures like Mamba, which offer faster inference and the ability to handle extremely long sequences. The third reason is the ability of models to think for longer during inference, allowing for more comprehensive and accurate responses. The fourth reason is prompt optimization, which enables language models to optimize their own prompts, leading to significantly better performance. The video concludes with a prediction that by the end of 2024, AI will achieve photorealistic text-to-video outputs that can fool most humans.

2023-12-26

• Yannic Kilcher
  NeurIPS 2023 Poster Session 4 (Thursday Morning)

  In this video, the speaker explains their research on temporal action segmentation, which involves translating untrimmed videos into action segments. They address the problem of existing models suffering from out-of-context errors by proposing an activity grammar induction algorithm and an effective parser. The algorithm extracts rules from the dataset and applies them to find optimal action sequences. They also introduce a segmentation optimization process to determine the optimal durations of action sequences. Their results show improved performance in activity recognition and the effective removal of out-of-context errors. Additionally, the speaker discusses the possibility of recognizing activities not appearing in the dataset and the potential for training fine-grained action classifiers.

• Yannic Kilcher
  Traditional X-Mas Stream

  In this live-streamed Minecraft session, the player begins by setting up their stream and deleting previous failed attempts. They start playing the game in a prairie-like area and decide to go mining for diamonds. The player struggles with movement controls and constantly falls into a large hole. They eventually find a cave and go exploring, only to die multiple times and lose their equipment. They manage to find one diamond but struggle to find coal for torches. After some unsuccessful attempts, the player decides to go back up to find food and calls it a day, happy with their progress. They also name their cat "Yan Cat" and contemplate future streams.

2023-12-25

• Yannic Kilcher
  Art @ NeurIPS 2023

  The video transcript captured a conversation between two individuals discussing a voice-to-image AI tool. The tool allows users to change the mood and context of images using sliders. It is based on stable diffusion and has a specialized model to recognize voices. The tool currently only supports English captions, which is a limitation for international users. The conversation also delves into the artist's personal use of the tool to create comics and experiment with creativity. The artist mentions an example where the tool generated interesting and unexpected images that they might not have come up with otherwise. The conversation ends with a humorous mention of using the tool for a pornographic movie.

2023-12-24

• Yannic Kilcher
  Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained)

  Muma is an architecture that combines selective state spaces with other components like 1D convolutions and gating mechanisms. It aims to address the computational and memory bottlenecks of transformers while still achieving the modeling power of recurrent neural networks. The selective state spaces in Muma allow for input-dependent transitions between hidden states, unlike previous state space models. This makes Muma more suitable for tasks requiring context-based reasoning, such as language modeling and DNA modeling. The architecture is designed to scale linearly with sequence length and offers fast training and inference. Muma achieves its efficiency by leveraging a hardware-aware algorithm that computes the model recurrently with a scan instead of a convolution. Experimental results show that Muma outperforms other attention-free models on tasks like language modeling and DNA modeling.

2023-12-22

• AI Explained
  Midjourney v6, Altman 'Age Reversal' and Gemini 2 - Christmas Edition

  In this video, the creator discusses recent developments in AI, focusing on OpenAI's MID Journey version 6. They highlight that this version is more sensitive to prompts, capturing key details and delivering more accurate outputs. The video also mentions the use of the Magnific AI tool for upscaling images, which produces impressive photo-realistic results. The creator offers tips for refining prompts to achieve more realistic images. Shifting gears, the video also discusses OpenAI CEO Sam Altman's investment in extending healthspan, with emphasis on Retro, a life-extension company. The video explores Retro's approach to cell reprogramming and the potential for age reversal therapies. It also touches on the debate surrounding the pursuit of longevity in the tech industry. Lastly, the video mentions Google's training of their next model, Gemini 2, and the immense computing capabilities that give them a significant advantage over other companies.

2023-12-21

• Google DeepMind
  Why AI Creates Better Weather Forecasts

  AI has the potential to revolutionize weather forecasting by providing more accurate and detailed predictions. Traditional methods involve coding algorithms based on equations that represent weather variables. However, AI models like MetNet 3 and GraphCast take a different approach. They analyze past weather data to understand cause and effect relationships between different weather conditions. By learning subtle trends and patterns from the data, these AI models can predict future weather with better accuracy, efficiency, and detail. MetNet 3 is already improving the accuracy of 24-hour weather forecasts on Google Search, while the open-source GraphCast model is being used by the ECMWF to generate forecasts accessible on their website. AI can not only predict the weather but also help people make better decisions about their daily lives, such as preparing for hurricanes or deciding whether to bring an umbrella.

2023-12-18

• AI Explained
  A 100T Transformer Model Coming? Plus ByteDance Saga and the Mixtral Price Drop

  In this video transcript summary, there are denials from three OpenAI employees regarding the existence of GPT 4.5, putting an end to the rumors. The focus then shifts to the ET Transformer, a new company claiming to have the world's first Transformer supercomputer. The architecture is etched directly onto a chip, offering improved performance for large language models. The potential benefits include real-time interaction and cheaper prices compared to current GPUs. The transcript also mentions the Mix Trial, an 8 * 7 billion parameter model that matches or beats GPT 3.5 in benchmarks while being more affordable. Sebastian Bck discusses the possibilities of achieving reasoning capabilities with large models like GPT 4 at 13 billion parameters. Lastly, the transcript mentions that ByteDance is allegedly using OpenAI's technology secretly to build a competitor, in violation of OpenAI's terms of service.

2023-12-14

• NVIDIA
  From Sedans to SUVs: Ensuring Precision with Dynamic View Synthesis - NVIDIA DRIVE Labs Ep. 32

  The integration of automated and autonomous capabilities in vehicle fleets poses challenges when expanding the technology to new models. Differences in camera viewpoints between vehicle types can lead to drops in accuracy for perception models. To address this issue, a technique called Dynamic View Synthesis (DVS) has been developed. DVS transforms camera data from one type of vehicle into another, eliminating the viewpoint issue. This approach relies on multi-view consistency and uses deep neural networks to learn 3D scene geometry. The networks can render images from arbitrary camera viewpoints, producing new data for training perception models. DVS improves prediction accuracy despite changes in sensor positions, allowing for the deployment of perception models at scale without costly data collection and labeling. To learn more, visit the project page for the paper and GPU hub.

2023-12-13

• AI Explained
  Phi-2, Imagen-2, Optimus-Gen-2: Small New Models to Change the World?

  In this video, the focus is on the announcement of F2, a 2.7 billion parameter model by Microsoft that outperforms models of comparable size and even models 25 times its size. The video also discusses the flaws in the MML U benchmark and the mistakes found in its questions across various subjects. The importance of prompt variations in the model's performance is highlighted, as well as the potential lessons and implications of F2 and its synthetic data training approach. The video also mentions the release of Imagin 2 by Google, which generates realistic images from text, and introduces Optimus Gen 2, a lighter humanoid robot from Tesla. The video concludes with an introduction to AI Insiders, a Patreon tier that offers additional AI content and networking opportunities.

2023-12-06

• AI Explained
  Gemini Full Breakdown + AlphaCode 2 Bombshell

  In a video discussing Google Gemini, a family of multimodal models, the speaker highlights several key points. First, Gemini is not considered AGI, but it is better than GPT-4 in many modalities. The models include Nano (for phones), Pro (equivalent to GPT-3.5 or better), and Ultra (GPT-4 competitor). The speaker questions the validity of the Gemini models' performance claims, specifically in relation to a multiple-choice test called MMLU, and notes that GPT-4 was given fewer shots than Gemini Ultra during testing. He also discusses Gemini's performance in various modalities, including image understanding, video understanding, speech recognition, and speech translation. The speaker mentions that Gemini is compute-intensive and not available for consumer release yet. He also hints at future improvements, including integrating Gemini with robotics for multimodal interaction.

2023-12-05

• HuggingFace
  The Future of 3D

  Gaussian splatting is a new rendering technique that offers high-fidelity and fast rendering of scenes. It involves capturing multiple images from different angles and converting them into a representation called gaussians, which are 3D distributions with color and alpha values. These gaussians are then projected onto a 2D plane, sorted by depth, and blended to create the final image. To achieve the desired results, the gaussians need to be trained and adjusted to produce images similar to the original ones. Gaussian splatting has the potential to revolutionize graphics rendering, similar to how the introduction of shadows, reflections, and other effects changed the industry. While still in its early stages, Gaussian splatting shows promise and has sparked interest in the research community.

• OpenAI
  OpenAI DevDay: Keynote Recap

  At OpenAI's first ever DevDay event, the launch of the new GPT-4 Turbo model was announced. GPT-4 Turbo can handle up to 128,000 tokens of context and has a JSON mode for ensuring valid JSON responses. It can now process multiple functions at once, improving its ability to follow instructions. Additionally, the platform now supports retrieval of knowledge from external sources. The knowledge in GPT-4 Turbo is up to date as of April 2023 and OpenAI plans to continuously update it. Other updates include the introduction of Custom Models, higher rate limits for GPT-4 customers, and the launch of GPTs, tailored versions of ChatGPT. The new assistance API offers features such as persistent threads, built-in retrieval, code interpreter, and improved function calling. OpenAI is excited to see what users will create and promises even more impressive advancements in the future.

2023-12-03

• AI Explained
  OpenAI Insights and Training Data Shenanigans - 7 'Complicated' Developments + Guest Star

  Today's video explores the complexity of various topics including the drama at OpenAI, new developments at Gemini, and research on privacy concerns. The video begins by discussing the uncertainty surrounding the future of OpenAI following the departure of its president and chief scientist. Rumors about a powerful model called QAR and concerns about safety are also addressed. The video then delves into the reasons behind the firing of OpenAI's former CEO, including claims of misrepresentation and manipulation. Moving on to Gemini, the video reveals that the launch of the multimodal model has been delayed due to language-related challenges. A recent paper on training models highlights the issue of memorization and the potential privacy risks involved. Finally, the video teases an upcoming announcement by Dr. Jim Fan, an AI researcher at Nvidia.

2023-11-27

• HuggingFace
  [Monday evening short video] Summary of two new amazing LLM benchmarking papers: GAIA and GPQA

  Two benchmarks were recently published that could shape the future of benchmarking AI models. The first benchmark, called Gia, focuses on General AI assistance and aims to investigate AI's ability to perform multiple tasks, such as searching the web for information and providing answers to specific questions. Gia has three levels of difficulty, with level three questions being extremely challenging for current AI models. The second benchmark, GP QA, is designed to test narrow superhuman AI, specifically in fields like physics, chemistry, and biology. These questions are intentionally difficult, created by experts who aim to challenge non-experts. Both benchmarks have factually true answers and provide a way to compare and build upon AI models openly and collaboratively.

2023-11-24

• AI Explained
  Q* - Clues to the Puzzle?

  In this video, the host discusses a possible breakthrough in AI by OpenAI that could have significant implications. The host speculates that the breakthrough may involve a combination of process supervision, test time computation, and reinforcement learning. They suggest that OpenAI may have developed a model called QAR (which stands for "Question-Answer Reasoning") that uses these techniques to improve the reasoning capabilities of AI models. The host also highlights the involvement of researcher Lucas Kaiser and his work on test time computation. The potential implications of this breakthrough include improved generalization, self-improvement, and the ability to generate novel and creative solutions. However, the host admits that there is still much speculation and uncertainty surrounding the exact nature of the breakthrough. The video ends on a positive note, discussing DeepMind's new Lyra model, which can generate music based on user input.

2023-11-21

• NVIDIA
  Genentech and NVIDIA Revolutionize Drug Discovery with Generative AI and Lab in the Loop

  The integration of molecular biology and generative artificial intelligence (AI) has revolutionized drug discovery and development. This field, referred to as generative AI, uses algorithms trained on existing data to generate new molecules. These molecules are then tested in the lab, and the experimental results are used to improve the AI algorithms. This iterative process continues until a molecule with the desired properties is identified for further development into a medicine. This interdisciplinary approach, combining theoretical advances with wet and dry lab interactions, holds enormous potential for accelerating the development of life-changing medications. By working hand in glove with computational scientists, biologists aim to transform our understanding of disease and make significant improvements in human lives.

• Google DeepMind
  Creating the worlds that enable research | Inside Google DeepMind - Sarah’s story

  At DeepMind, their job as games testers is not just about playing games for fun, but rather testing games and environments that will be used by AI in research. Growing up in a tech-savvy household, one tester was inspired to pursue a career in technology. After joining a video game society in university, they were able to connect with local game companies and gain more opportunities. Now working at DeepMind, they build games used in research to train AI for various applications, such as healthcare and climate change. Being able to contribute to solving important real-world problems through their skills feels rewarding and fulfilling.

• Google DeepMind
  Making the connections to advance AI | Inside Google DeepMind - Annette’s story

  This video transcript features a program manager from Deep Mind who discusses her role in the science team. She describes her passion for understanding human behavior and how it translates to her job of managing interdisciplinary teams and removing barriers for optimal productivity. She talks about the varied projects she works on, from using AI to track turtles for conservation to exploring quantum mechanics and genomics. She mentions the importance of building relationships and team dynamics and highlights the ethical considerations and impact on society inherent in developing cutting-edge technologies. The video ends with her engaging in a conversation with someone about their day.

• Google DeepMind
  Embracing creativity through music & AI | Inside Google DeepMind - Drew’s story

  In this video, the speaker discusses the potential of artificial intelligence (AI) in music composition. They mention how DeepMind, a leading AI research company, aims to understand patterns in order to reproduce them. The speaker, who initially wanted to pursue a career in music and film, transitioned to studying science and philosophy, eventually joining DeepMind. They explain that AI systems can analyze data to predict future outcomes and generate various kinds of outputs. The goal is to build an artificial general intelligence system that can serve as the ultimate collaborator, possessing knowledge in multiple domains. The speaker believes that future generations will view AI as a natural and essential component of their everyday lives, enabling limitless creativity and expression.

• Google DeepMind
  Robotics and AI | Inside Google DeepMind - Stefano’s story

  The speaker discusses their fascination with the development of the brain in children and its ability to quickly learn and make connections. They explain how this interest led them to transition into robotics, as they saw similarities between the brain's plasticity and the learning process of robots. The speaker shares their background in remote control airplanes and how they never expected to merge that hobby with advanced artificial intelligence. They highlight the importance of a robotics department in testing algorithms for artificial general intelligence and discuss the joy and challenges of building and testing robots. They emphasize Deep Mind's unique position to develop safe and beneficial robotic technology for the future.

• Google DeepMind
  Building the tools to make AI breakthroughs possible | Inside Google DeepMind - Anna’s story

  The speaker discusses the benefits of using a tablet for illustrations, as it allows for more efficiency and flexibility in creating art. They emphasize the importance of using the right tools to enhance creativity and problem-solving. The speaker then transitions to discussing their role at DeepMind, where they initially worked as a UX engineer but eventually grew their career to manage a team. They highlight the constant need to adapt to new challenges and develop innovative solutions. The speaker expresses their appreciation for being part of a company that is at the forefront of AI research and values the opportunity to learn from their highly skilled colleagues. They conclude by acknowledging the transformative potential of AI and the responsibility that comes with it.

• Google DeepMind
  Exploring the next generation of AI products | Inside Google DeepMind - Deeni’s Story

  The speaker emphasizes the importance of being idealistic and tackling big, ambitious projects to create positive societal change. However, they also recognize the challenges in translating these lofty ambitions into practical applications. They describe their natural inclination to connect different ideas and their childhood interest in repurposing discarded materials. They explain their role in understanding the field's advancements and identifying promising research for practical use. The speaker highlights the value of understanding different viewpoints, drawing from their experiences living in various countries. They express excitement about the potential impact of machine learning and artificial intelligence on improving the lives of billions of users. Overall, they believe that the general public is also enthusiastic about the possibilities of these technologies.

• Google DeepMind
  Putting ethics into practice | Inside Google DeepMind - Dawn's story

  The speaker discusses the impacts of technology and emphasizes the need to be mindful of both the positive and negative effects. As the Director of Pioneering Responsibly at Deep Mind, their role is to ensure that technologies are used ethically and with reduced harm. The speaker's mother's belief in the power of science and knowledge influenced them greatly. Their team works with research and applied teams to anticipate future risks and issues and seeks external expert perspectives. By incorporating risk mitigation from the beginning, the speaker's team aims to avoid saying no to projects and encourages bold and responsible transformation. Ultimately, their goal is to be able to tell their children that the good things happening are a result of anticipating and mitigating risks.

2023-11-20

• NVIDIA
  Fireside Chat With Jensen Huang and Aude Durand at ai-PULSE

  In this video transcript, Jensen Huang, CEO of Nvidia, discusses the development and investments in AI in Europe, particularly in France. He highlights the rich AI expertise in France and Europe, with thousands of AI startups and research centers. Huang emphasizes the importance of infrastructure, such as Nvidia's supercomputers, in advancing AI research and development. He also mentions the significance of access to data specific to different regions and industries. Huang discusses Nvidia's partnership with cloud providers, like Scaleway, and how they empower companies to develop AI projects by providing advanced supercomputers and AI models as a service. He also emphasizes the role of open-source technology in driving AI innovation and research, particularly in terms of safety and responsibility.

• NVIDIA
  Data Center Digital Twins of Israel-1 | Built with NVIDIA Air and NVIDIA Omniverse

  Israel's AI supercomputer, Israel-1, is being constructed with the help of digital twins created using NVIDIA Air and Omniverse. These digital twins provide a simulation of the data center's logical and physical behavior, allowing for insights that speed up the construction process. NVIDIA Air is used for designing and optimizing the network, while Omniverse combines designs with facilities data for planning rack layouts, cabling, power consumption, and heat dissipation modeling. Once construction is complete, the automation developed in NVIDIA Air will be applied to the real equipment, allowing for a quick setup of Israel-1. This accelerated timeline aims to provide a blueprint for future generative AI factories while maximizing time-to-value for the supercomputer.

• NVIDIA
  NVIDIA CEO Jensen Huang at Microsoft Ignite 2023

  Nvidia CEO, Jensen Huang, expresses his excitement and pride regarding the collaboration between Nvidia and Microsoft over the past year. He highlights the progress made in the field of artificial intelligence (AI) and accelerated computing, emphasizing the transformation of the entire computer industry. One significant achievement is the creation of the fastest AI supercomputer, built by both teams in just a few months. The partnership extends beyond hardware to software, with Microsoft hosting Nvidia's software stacks on Azure. They have developed Nvidia Omniverse, an industrial digitalization software, and are offering an AI Foundry Service for enterprises to engage in AI. Huang believes that generative AI is the most significant platform transition in computing history, and together they are leading the waves of innovation in AI. He praises Microsoft's collaborative and partner-oriented culture, stating that the partnership is unique and integral to amplifying Nvidia's ecosystem. Microsoft CEO, Satya Nadella, expresses his admiration for the partnership and the transformation it has brought to the industry. He emphasizes the three waves of AI innovation and the potential for heavy industries to benefit from generative AI. Nadella concludes by thanking Huang and his team for their deep partnership.

2023-11-17

• HuggingFace
  Short summary of the paper "Role playing in Large Language Model"

  The paper "Role Play with Large Language Models" discusses how to approach understanding and interacting with large language models (LLMs) without anthropomorphizing or assigning human-like qualities to them. The authors argue that LLMs should be seen as role players, capable of assuming different characters or roles in a dialogue. LLMs learn by predicting the most likely next word based on a vast corpus of internet data. These roles are derived from the training data, which includes narratives and archetypes. The authors propose thinking of the role-playing nature of LLMs as a superposition, similar to a quantum superposition. They provide an example of the 20 Questions game that demonstrates how LLMs generate coherent answers based on their assigned roles. The discussion sheds light on the implications for ethics, self-awareness, and the dangers of misinformation in LLMs.

2023-11-15

• OpenAI
  AI Frontiers: Jesper Hvirring Henriksen (OpenAI DevDay)

  Be My Eyes has introduced a new feature called Be My AI, developed in partnership with OpenAI's GPT-4V. Be My Eyes aims to provide blind and low-vision individuals with visual assistance through a community of volunteers via their app. However, feedback from users highlighted the need for an independent option. Be My AI fills that gap by offering an AI assistant available 24/7 to describe images encountered online or in apps. The GPT-4V model has proven extremely accurate and even displays human-like wit in its responses. Beta testers have reported positive experiences, with one user recording over 700 image descriptions. Be My AI has also been integrated into enterprise customer support, such as Microsoft's Disability Answer Desk, leading to a reduction in call escalations. The AI's ability to see, hear, and communicate has the potential to greatly enhance accessibility in assistive technologies.

• OpenAI
  AI Frontiers: Helena Merk (OpenAI DevDay)

  In this talk, Helena, the CEO and co-founder of Streamline, discusses the intersection of climate change and AI. She emphasizes that climate change is both a major problem and a significant economic opportunity. Helena highlights six key areas that require attention to catalyze the climate transition, including soil carbon capture, renewable power, wind energy optimization, home electrification, and battery design. She also introduces her company, Streamline, which aims to accelerate the climate transition by helping companies access government funding through grant management software. Helena explains how language models, such as ChatGPT and GPT-4, can be leveraged to streamline the grant application process and save climate tech companies up to 80% of their time.

• OpenAI
  AI Frontiers: Annie Hill (OpenAI DevDay)

  Annie, from the Innovation & Digital Health Accelerator group at Boston Children's Hospital, discusses how they are using generative AI to address pain points in healthcare. They aim to reduce burnout and support clinical teams by leveraging AI technology to provide more efficient patient education, personalized medical cases for learners through an interactive platform called MedTutor, and enhance existing tools like Swirl, which aggregates patient data for providers. They also explore context-driven error detection and alerting to improve patient safety and reduce clinical errors. Boston Children's Hospital is committed to equity, diversity, and inclusion and is working on implementing equity guidelines for AI-related initiatives. They are excited about the advancements in generative AI and will continue to evaluate its impact on healthcare.

• OpenAI
  AI Frontiers: Chad Nelson (OpenAI DevDay)

  In this video, Chad Nelson discusses how OpenAI's ChatGPT has expanded his creativity and accelerated his creative process. He shares his experience using AI tools like DALL·E to create characters and stories, emphasizing that AI tools are not replacing his creativity but enhancing it. Chad demonstrates how he used ChatGPT to describe and build a character and its backstory, including its house and other characters in its world. He explains that working with AI as a creative assistant allows him to explore multiple ideas and take risks, ultimately leading to better creative choices. Overall, Chad showcases how AI tools have become valuable collaborators in his creative journey.

2023-11-13

• OpenAI
  The Business of AI

  During the panel discussion, Aliisa Rosenthal, the head of sales at OpenAI, spoke with Kathy Baxter from Salesforce, Oji Udezue from Typeform, and Miqdad Jaffer from Shopify about the business of AI and its integration into products. They discussed the challenges of building AI products, such as determining the final product state, ensuring ethical and responsible AI practices, and staying true to the customer's needs. The panelists also highlighted the importance of understanding customer workflows, using AI to save time and provide value, and the need for sustained adoption and user feedback as success metrics. They debunked the myth that AI is neutral and discussed the future of AI product development, emphasizing responsible and inclusive implementation, anticipating change, and leveraging AI to improve collaboration and creativity in workflows.

• OpenAI
  A Survey of Techniques for Maximizing LLM Performance

  The keynote at OpenAI's developer conference focused on techniques to maximize the performance of LLMs (large language models) when solving specific problems. They emphasized the importance of prompt engineering and fine-tuning. Prompt engineering involves writing clear instructions, splitting complex tasks into simpler subtasks, and giving LLMs time to think. Fine-tuning, on the other hand, involves training an existing model on a smaller, more specific dataset to achieve better performance and efficiency. They shared success stories of fine-tuning, including Canva's use case where they fine-tuned 3.5 Turbo to generate design mocks, and cautioned against potential pitfalls of fine-tuning, such as oversaturating the context or fine-tuning on irrelevant data. They also discussed how fine-tuning and retrieval-augmented generation (RAG) techniques can be combined for optimal results.

• OpenAI
  The New Stack and Ops for AI

  The Stack and Ops for AI talk focused on taking applications from the prototype stage to production. The presenters discussed the challenges of scaling applications built on OpenAI models, including the non-deterministic nature of the models and the difficulty of getting them into production. They provided a framework consisting of four parts: building a delightful user experience, handling model inconsistency through grounding and constraining the models, iterating on applications with evaluations, and managing scale through orchestration. The presenters also introduced the concept of Large Language Model Operations (LLM Ops), which involves the practice, tooling, and infrastructure needed for the operational management of LLMs. They highlighted the importance of LLM Ops in addressing challenges such as monitoring, optimizing performance, improving security and compliance, managing data and embeddings, and increasing development velocity.

• OpenAI
  New Products: A Deep Dive

  OpenAI has introduced the Assistants API, which allows developers to build their own customized AI assistants within their applications. The API includes three key components: the assistant, which is modeled based on instructions given by the developer and has access to specific models and tools; threads, which represent sessions between users and the assistant; and messages, which are the interactions between users and the assistant within a thread. The API also includes tools such as Code Interpreter, which allows the assistant to write and execute code, and retrieval, which enhances the assistant's knowledge by retrieving information from external sources. OpenAI has made improvements to function calling, including JSON mode and parallel function calling. Future updates to the API will include multi-modal capabilities, support for user-defined code execution, and asynchronous support with WebSocket and Webhooks.

• OpenAI
  Research x Product

  Barret and Joanne from OpenAI discuss the unique research and product collaboration that exists at OpenAI, giving a behind-the-scenes look at how this partnership works. They highlight the example of dialogue interfaces, where the research team and product team were unsure about the best approach. Ultimately, they opted for a generic version, which turned out to be popular and led to many amazing products and companies being built around it. The post-training research team at OpenAI is responsible for adapting large pre-trained language models, adding new capabilities like internet browsing and code execution. The product team focuses on designing model behavior, ensuring that the models' responses are intuitive and useful to users. They also discuss the future direction of models, including personalization, multi-modality, and tackling harder tasks.

• HuggingFace
  Create Your Own Gradio Component - Part 1

  In this video, Freddy, an engineer at Gradio, introduces the new updates in Gradio version 4.0, focusing on making the library more customizable and extensible. He demonstrates how to create a custom Gradio component by walking through the process of building a multimodal chatbot component. The chatbot component is designed to display both text and media components in the same message, making it more intuitive and user-friendly. Freddy starts by creating the back-end and front-end scaffolding for the custom component and then proceeds to implement the data model, pre-process, post-process, and example inputs. He also debugs and tests the component by simulating a conversation between a user and the bot, exchanging text, images, audio, and video messages. Finally, Freddy shows how to build and publish the custom component to PyPI for others to use.

2023-10-31

• HuggingFace
  What's New in Gradio 4.0?

  Gradio 4.0 has been launched with new features and improvements. The Gradio team has been observing how the community uses Gradio and has incorporated user feedback to enhance the platform. One major change is the use of server-side events for communication between the server and client, replacing the previous use of HTTP POST requests and websockets. This change improves device support, load balancing, and integration with other technologies. Custom components have also been introduced, allowing users to build custom inputs and outputs for their machine learning models. The media components, including video, image, and audio, have been refreshed with new features such as trimming and source selection. Additionally, Gradio now supports custom share servers, allowing users to host their demos on their own domains. The team has also focused on improving accessibility in Gradio apps. Other updates include better file security, meta tag control, and concurrent event processing. Upgrading to Gradio 4.0 may require some changes to code, and the team provides a migration guide in the release notes. Gradio Light, a lightweight version of Gradio, will be updated to be compatible with Gradio 4.0 soon.

2023-10-25

• HuggingFace
  What is Hugging Face?

  Hugging Face is an open platform for AI builders that aims to make machine learning more accessible to everyone. It focuses on three main pillars: models, datasets, and spaces. Models refer to the actual AI algorithms, which are hosted on the platform and include models from major companies, research institutions, and open-source communities. Datasets are openly accessible data that are used to train the models. Spaces are provided to easily demo and showcase the models. Hugging Face combines all these pillars with open-source libraries like Transformers, Diffusers, and Accelerate, making it easy for users to build, share, and use the latest AI models. The platform is free, but additional computing resources and deployment assistance are available if needed. To get involved, visit hf.com.

2023-09-29

• HuggingFace
  Computer Vision Study Group Session on SAM

  In this video, the presenter discusses the paper "Segment Anything with Prompt-guided Masking" by Meta AI. The paper introduces a model called Sam (Segment Anything Model) that performs prompt-based image segmentation using both semantic and instance segmentation. The presenter provides a summary of the model architecture, training procedure, and evaluation results. They also mention that the paper includes a detailed description of the dataset creation process, which involved three stages: model-assisted manual annotation, semi-automatic annotation, and fully automatic annotation. Additionally, the presenter showcases various projects and resources that have leveraged the Sam model. They conclude by providing example code for using Sam with the Transformers library.

2023-08-25

• Anthropic
  Behind the prompt: Prompting tips for Claude.ai

  In this video, Alex, a prompt engineer at Anthropic, shares five tips for getting the best performance from Claude, a language model. First, describing the task clearly and specifically helps Claude recognize what needs to be done. Second, marking different parts of the prompt with XML tags helps Claude pay attention to their structure. Third, providing a wide range of examples helps Claude learn how to perform the task. Fourth, taking advantage of Claude's ability to read long context, up to a hundred-thousand tokens, improves performance. Finally, giving Claude time to think by using thinking tags before it produces a final answer leads to better results. Alex also mentions that prompt engineering at Anthropic follows a test-driven approach to measure the performance of prompts.

2023-08-23

• Anthropic
  Coding with Claude

  The video appears to be a musical performance or concert. The audience can be heard applauding and cheering throughout the video. The music being played is not specified, so the content of the performance is not clear.

• Anthropic
  Long inputs, multi-step output with Claude

  In this video, the speaker expresses gratitude towards a foreign entity or individual. The video is accompanied by music throughout, adding to its positive tone. Unfortunately, without more context or information, it is difficult to determine the specific content or purpose of the video.

• Anthropic
  Inside our first Anthropic Hackathon, San Francisco

  This video highlights the first official anthropic-sponsored hackathon, where participants share their excitement about the future of AI and its potential benefits. Many participants express their desire to contribute to a smooth transition into a world that is greatly influenced by AI. They discuss their experiences with immigration challenges and how they have been eagerly awaiting the use of Cloud 2 to help them scale their projects. The video also briefly mentions the development of an emotionally intelligent emoji and concludes with the gratitude and enthusiasm of the participants.

• Anthropic
  Quick tips for Claude: Long context file uploads

  [Music] This video transcript is extremely short and does not provide any context or information to summarize. It appears to be a music track or sound effects rather than a video with spoken content.

2023-07-27

• HuggingFace
  🤗 Hugging Cast v4 - AI News and Demos - LLaMa 2 edition!

  In this episode of the Hugging Cast V4, the hosts discuss the release of LAMA2, an amazing language model by Meta. The LAMA2 model is an upgraded version of the LAMA model, incorporating reinforcement learning techniques and focusing on conversational safety. The model has been trained on a massive amount of data and has shown impressive performance on benchmarks. The hosts also mention the different checkpoint options and provide insights into fine-tuning and deployment options. They emphasize the importance of prompt formats and the need to ensure that prompts are aligned with the specific model being used. The hosts conclude by answering audience questions and welcoming feedback for future episodes.

2023-07-21

• HuggingFace
  Results of the Open Source AI Game Jam

  The first ever open source AI game champ was a huge success, with 88 teams submitting games using open source AI tools in just 48 hours. The most popular use of AI was in the development process for art, coding, and music. Some games, like Singularity and Word Conquest, went all-in on AI, generating everything in real-time or using word embeddings to create a challenging vocabulary game. Other games showcased the frontier of AI, with AI-generated quests, NPC dialogue, and even voices. The majority of submissions used AI for art, with creative uses like "Snippet" allowing players to jump into paintings, cut them apart, and reveal AI-generated stories. The top-rated game, Snippet, won for its creativity and overall experience.

2023-07-07

• HuggingFace
  The Open Source AI Game Jam Starts Now

  The Open Source AI Game Channel is hosting a 48-hour game development competition, the largest ever focused on AI. Participants can work alone or in teams of any size and are required to create a game in English that runs on web or Windows, using at least one open source AI tool. Participants are encouraged to be creative in their use of AI, such as generating assets with stable diffusion. After submission, games will be rated by participants based on fun, creativity, and theme. The top 10 games will be showcased and judged by three judges to determine the winner. The theme for the competition is "expanding." Participants can join the Discord channel for any questions or assistance.