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.
Иран пригрозил уничтожить все нефтегазовые объекты США на Ближнем Востоке02:33
В одной стране призвали экономить топливо20:57，推荐阅读safew 官网入口获取更多信息
Италия — Серия А|29-й тур
。关于这个话题，传奇私服新开网｜热血传奇SF发布站｜传奇私服网站提供了深入分析
第一百七十六条 船舶发生碰撞，是由于不可抗力或者其他不能归责于任何一方的原因或者无法查明的原因造成的，碰撞各方互相不承担赔偿责任。。关于这个话题，华体会官网提供了深入分析
Here’s what’s new in v0.10.0.