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As the title and description of the GitHub repo suggest, I’m working on a small project for purely educational purposes, with the goal of implementing generative model inference (small models capable of modeling 2D distributions) based on the Flow Matching paradigm in C. I’ve worked on generative AI models based on Flow Matching from a more “abstract” perspective, using frameworks like PyTorch, and I wanted to understand what goes on behind the scenes. The repository is still a work in progress

OpenAI is rolling out ChatGPT Health to everyone in the US on Thursday, allowing more people to connect their medical records and health-tracking information to the chatbot. During a briefing, Ashley Alexander, OpenAI's vice president of health product, says the company's models "are now capable of reasoning at levels that are better than clinician level." […]

Primate Labs is releasing Geekbench 7, the latest generation of its popular benchmarking tool. Geekbench 7 features new video and audio encoding / decoding tests, a redesigned multi-core test, and larger, more demanding datasets for CPUs and GPUs to crunch through. It otherwise looks and acts just like Geekbench 6, and a Pro license will […]