O Futuro da Informação
O Futuro da Informação
@johnschulman2
Recently started @thinkymachines. Interested in reinforcement learning, alignment, birds, jazz music
Glad to see this -- renderers are a foundational component of the LLM stack. Renderers map between tokens and messages, which are invariant to tokenizer and formatting details. Most APIs, datasets, and RL environments are defined in terms of messages. Getting the details wrong x.com/PrimeIntellect…
Glad to be advising refine.ink, which uses AI to help authors and reviewers do deeper, more thorough analysis than unaided humans could practically do. Seems like a very positive direction for AI in science. x.com/ben_golub/stat…
Seeing the demos come together over the last week has been awesome -- so many things that previously required a special-purpose model (e.g. real-time translation, event detection in video) turn out to be zero-shot instruction following once you have a general-purpose model with
Luke and Rudolf's writing on keeping humans central in an AI-powered world sparked a lot of discussion at Thinking Machines. For me, it captured some things I'd been thinking about but hadn't put as clearly. The more I got to know them and learned about their work, the more I x.com/WorkshopLabs/s…
Great work by Chroma training a search agent with SoTA efficiency. Lots of cool details: a prune tool for editing context mid-search, a synthetic data pipeline with verification steps, and a curriculum that shifts from recall to precision. Trained with Tinker! x.com/trychroma/stat…
Models that are great at calibrated predictions will be transformative for decision making. Excited about Mantic's work and proud they're using Tinker. Their new blog post digs into their methodology and findings. x.com/tshevl/status/…