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.
当然它也有优点：长得挺可爱、很小，揣出去还能当个社交谈资。让我最喜欢的一点是，它有两个耳机孔！ 一个平衡口，一个 3.5mm 接口，甚至能一起工作！这让我想起了上学时和好同学分享同一副耳机的青春岁月。现在有了这玩意儿，你可以和另外三个好朋友一起分享音乐了，四人同乐就非常的生草。。业内人士推荐新收录的资料作为进阶阅读
现在我们正式开始撰写文章。我在你刚才整理的素材里加了许多【】批注，请参考这些批注来梳理和扩写。，这一点在新收录的资料中也有详细论述
Минобороны России раскрыло подробности о перехваченных за ночь БПЛА ВСУ08:17，详情可参考新收录的资料