We're excited to announce #AlphaFold 3 with @GoogleDeepMind in @Nature: our new AI model for predicting biomolecule structures with unprecedented breadth and accuracy. Expanding beyond proteins to tackle DNA, RNA, small molecules to fuel advances in biology & drug design 🧵

Clear PCBs feel illegal

107 TFLOPS on Mac M3 with a 9070XT attached. Our GEMM with the AMD_LLVM backend is now beating hipBLASLt on the card. And I love how portable LLVM is, this is just brew install llvm@19.

A Microsoft paper suggests that GPT-4o-mini is a ~8B parameter model. It means distillation works pretty well at @OpenAI. Other model sizes from the paper: - Claude 3.5 Sonnet: 175B - GPT-4: 1.76T - GPT-4o: 200B - o1-preview: 300B - o1-mini: 200B @sama, would you consider

Watch @symbolica Principle Scientist Dr. Paul Lessard talk about why category theory is the key to achieving a description of symbolic reasoning in machines and how we are using it to usher in a new era in machine learning.

Introducing Gemini 1.5: our next-generation model with dramatically enhanced performance. It also achieves a breakthrough in long-context understanding. The first release is 1.5 Pro, capable of processing up to 1 million tokens of information. 🧵 https://t.co/qT0aXdFL0n

Optimus folds a shirt

Introducing SDXL Turbo: A real-time text-to-image generation model. SDXL Turbo achieves state-of-the-art performance with a new distillation technology, enabling single-step image generation with unprecedented quality, reducing the required step count from 50 to just one. The

LLM OS. Bear with me I'm still cooking. Specs: - LLM: OpenAI GPT-4 Turbo 256 core (batch size) processor @ 20Hz (tok/s) - RAM: 128Ktok - Filesystem: Ada002

Optimus can now sort objects autonomously 🤖 Its neural network is trained fully end-to-end: video in, controls out. Come join to help develop Optimus (& improve its yoga routine 🧘) → https://t.co/dBhQqg1qya

tinygrad is faster than torch at everything on M2 Max Try it for your next ML project on your MacBook