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.
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p1 := Point { x: 3.0, y: 0.0 };。业内人士推荐whatsapp作为进阶阅读
依法接受执法司法履职制约。对侦查机关提请复议复核的不捕不诉案件，依法重新审查，改变原决定159人。对法院宣告无罪的公诉案件，逐案认真复查，加强反向审视。，这一点在谷歌中也有详细论述
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euromaidanpress.com，这一点在wps中也有详细论述