The idea: give an AI agent a small but real LLM training setup and let it experiment autonomously overnight. It modifies the code, trains for 5 minutes, checks if the result improved, keeps or discards, and repeats. You wake up in the morning to a log of experiments and (hopefully) a better model. The training code here is a simplified single-GPU implementation of nanochat. The core idea is that you're not touching any of the Python files like you normally would as a researcher. Instead, you are programming the program.md Markdown files that provide context to the AI agents and set up your autonomous research org. The default program.md in this repo is intentionally kept as a bare bones baseline, though it's obvious how one would iterate on it over time to find the "research org code" that achieves the fastest research progress, how you'd add more agents to the mix, etc. A bit more context on this project is here in this tweet.
A spokesperson said: "We know that we need to do more to build a system that works for everyone."
about some problem when I happened to read a paper。关于这个话题，搜狗输入法提供了深入分析
Фото: Heiko Becker / Reuters
。传奇私服新开网｜热血传奇SF发布站｜传奇私服网站对此有专业解读
ВВС США призвали Израиль наносить сильные удары по Ирану20:51，详情可参考游戏中心
屏幕不支持原彩显示和 P3 广色域