Reading Beyond the Hype: Some Observations About OpenAI and Google’s Announcements
Was this email forwarded to you? Sign up here Reading Beyond the Hype: Some Observations About OpenAI and Google’s AnnouncementsGoogle vs. OpenAI is shaping up as one of the biggest rivarly of the generative AI era.Next Week in The Sequence:
You can subscribed to The Sequence below:📝 Editorial: Reading Beyond the Hype: Some Observations About OpenAI and Google’s AnnouncementsWhat a week for generative AI! By now, every AI newsletter you subscribe to and every blog and tech publication you follow must have bombarded you with announcements from the OpenAI events and the Google I/O conference. Instead of doing more of the same, I thought we could share some thoughts about how this week’s events shape the competitive landscape between Google and OpenAI and the generative AI market in general. After all, Google has been the only tech incumbent that has chosen to compete directly with OpenAI and Anthropic instead of integrating those models into their distribution machine. This week’s announcements show that the race between Google and OpenAI might be shaping up to be one of the iconic tech rivalries of the next generation. Here are some observations about OpenAI and Google’s recent announcements:
I could keep going, but this is supposed to be a short editorial. This week was another example that generative AI is moving at a speed we have never seen in any tech trend. The rivalry between Google and OpenAI promises to push the boundaries of the space. 🔎 ML ResearchVASIMMicrosoft Research published a paper introducing Vertical Autoscaling Simulator Toolkit(VASIM), a tool designed to address teh challenges of autoscaling algorithms such as the ones used in cloud computing infrastructures. VASIM can simulate different autoscaling policies and optimization parameters —> Read more. RLHF WorkflowSalesforce Research published a paper proposing an Online Iterative Reinforcement Learning from Human Feedback (RLHF) technique that can improve over offline alternatives. The method also looks to address the resource limitations of online RLHF for open source projects —> Read more. SambaNova SN40LSambaNova researchers published a paper proposing SambaNova SN40L, a technique that combines composition of experts(CoEs) , streaming dataflow and a three-tier memory to scale the AI memory wall. The research looks to address some of the limitations of hyperscalers when deploying large monolithic LLMs —>Read more. Med-GeminiGoogle published two research papers exploring the capabilities of Gemini in healthcare scenarios. The first paper explores Gemini in electronic medical records processing while the second one focuses on use cases such as radiology, pathology, dermatology, ophthalmology, and genomics in healthcare —> Read more. BEHAVIOR Vision SuiteResearchers from Stanford, Harvard, Meta, University of Southern California and other AI labs published a paper introducing BEHAVIOR Vision Suite, a set of tools for generaring fully customized synthetic data for computer vision models. BVS could have a profound impact in scenarios such as embodied AI or self-driving cars —> Read more. Online vs. Offline RLHFResearchers from Google DeepMind published a paper outlining the series of experiments comparing online and offline RLHF alignment methods. The experiments showed clear superiority of online methods and dives into potential explanations —> Read more. 🤖 Cool AI Tech ReleasesGPT-4oOpenAI unveiled GPT-4o, a new model that can work with text, audio and vision in real time —> Read more. Gemini 1.5Google introduced Gemini 1.5 Flash and new improvements to its Pro model —> Read more. Transformer Agents 2.0Hugging Face open sourced a new version of its Transformers Agents framework —> Read more. Model ExplorerGoogle Research released Model Explorer, a tool for visualizing ML models as graphs —> Read more. Gemma 2Google unveiled Gemma 2, a 27B parameter LLM that can run in a single TPU —> Read more. Imagen 3Google released Imagen 3, the latest version of its flagship text-to-image model —> Read more. Firebase GenkitGoogle released Firebase Genkit, a framework for building mobile and web AI apps —> Read more. 🛠 Real World AIInside EinsteinSalesforce VP of Engineering shares details about the implementation of the Einstein platform —> Read more. 📡AI Radarwii
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Sunday, May 12, 2024
The new model can predict the structure of many life's molecules such as proteins, DNA, RNA and several others. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
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