Goretech

  The  MedGemma model and how to use it MedGemma is a collection of  Gemma 3  variants that are trained for performance on medical text and image comprehension. Developers can use MedGemma to accelerate building healthcare-based AI applications. MedGemma currently comes in three variants: a 4B multimodal version and 27B text-only and multimodal versions. Both MedGemma multimodal versions utilize a  SigLIP  image encoder that has been specifically pre-trained on a variety of de-identified medical data, including chest X-rays, dermatology images, ophthalmology images, and histopathology slides. Their LLM components are trained on a diverse set of medical data, including medical text, medical question-answer pairs, FHIR-based electronic health record data (27B multimodal only), radiology images, histopathology patches, ophthalmology images, and dermatology images. https://huggingface.co/google/medgemma-27b-it

  AlphaEvolve : A Gemini-powered coding agent for designing advanced algorithms Designing better algorithms with large language models In 2023, we showed for the first time that large language models can generate functions written in computer code to help discover new and provably correct knowledge on an open scientific problem. AlphaEvolve is an agent that can go beyond single function discovery to evolve entire codebases and develop much more complex algorithms. AlphaEvolve leverages an ensemble of state-of-the-art large language models: our fastest and most efficient model, Gemini Flash , maximizes the breadth of ideas explored, while our most powerful model, Gemini Pro , provides critical depth with insightful suggestions. Together, these models propose computer programs that implement algorithmic solutions as code. AlphaEvolve verifies, runs and scores the proposed programs using automated evaluation metrics. These metrics provide an objective, quantifiable assessment of each...

  The Google for Startups Gemini kit is here This new suite of tools will help startups build faster with its AI tools and resources. We’ve supported thousands of startups as they use AI to scale their businesses, and we know that this work comes with lots of questions: Where do I start? How much does it cost? And who do I ask when I get stuck? We want to make sure that entrepreneurs using AI have everything they need to build the next big thing, all in one place. The  Google for Startups Gemini Kit  is available at no cost and designed to meet you wherever you are as you adopt AI. You’ll find the tools, credits, training and community support you need to build faster and bring AI into your products and workstreams from day one: Quoted text from Paige Bailey describing the Startups Gemini Kit: "Get your Gemini API key in seconds and start  prototyping in AI Studio. Next costs As  you scale you can apply for the Google  for startups cloud program Up to ...

  AlphaQubit tackles one of quantum computing’s biggest challenges Our new AI system accurately identifies errors inside quantum computers, helping to make this new technology more reliable. In a   paper published today in Nature , we introduce AlphaQubit, an AI-based decoder that identifies quantum computing errors with state-of-the-art accuracy. This collaborative work brought together Google DeepMind’s machine learning knowledge and Google Quantum AI’s error correction expertise to accelerate progress on building a reliable quantum computer.

Co-STORM Stanford University Get a Wikipedia-like report on your topic with AI STORM is a research prototype that supports  interactive knowledge curation. GitHub for Co-Storm

Mercury The fastest commercial-grade diffusion LLM  Mercury is a language model developed by Inception Labs, designed to be a fast and efficient commercial-grade diffusion LLM. Here's a breakdown of its key features and capabilities: Speed and Efficiency : Mercury is optimized for speed, capable of generating text up to 10 times faster than traditional auto-regressive models like GPT-3. This efficiency allows it to handle more requests simultaneously, making it suitable for high-demand applications. Diffusion Process : Unlike auto-regressive models that generate text token by token, Mercury uses a diffusion process. This method enables it to output many tokens in parallel, significantly speeding up text generation. Commercial-Grade Capabilities : Mercury is designed for commercial use, offering robust performance across various applications. It supports multiple programming languages and can integrate with existing systems, making it versatile for business needs. Applications : Sui...