The models, labs, and research the AI world is actually talking about.
Together AI announced a major infrastructure agreement with Humain for an open source AI data center.
Investor Joe Lonsdale discusses zoning, power costs, and avoiding moral panics around AI infrastructure.
Google DeepMind researcher Jon Barron posted part two of his talk on vision research.
Peter Yang asks how Codex references custom instructions in 200+ page threads.
Patrick McKenzie tweeted about spotting rapid output from an unnamed author.
Hugging Face retweeted the post about an upcoming blog with open training materials.
YouTube channel posts about 8pm conference on language model training and interpretability.
Tweet from machine learning engineer suggests matching fine-tuning to inference cache behavior.
Co-founder Sudip Roy will explain why continuous learning beats scaling for moving AI pilots into production.
Retweet discusses possible first use of terminal guidance by the drone before impact.
The executive at the open source AI platform flags the new upload.
Hugging Face engineer shares video and slides from his CERN talk on training large language models.
DeepMind researcher Nenad Tomasev replies to @hardmaru on reframing RSI.
The Gauntlet AI founder posted a brief question on the platform.
Retweet highlights recommendation to study forums for better prompting of language models.
Tweet highlights differences between how AI models and brains handle information.
Paper proposes BIT method that starts from text and interpolates directly into images.
Kim Isenberg compares usage caps across Anthropic subscription tiers in recent post.
Oxford professor replies that a unified lab structure is central to the group's work.
A tweet recounts advice given to a friend about conversing with LLMs.