手环测血氧、AI读舌苔 年轻人为何热衷“赛博养生”？
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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俄国家杜马国防委员会成员维克托·索博列夫向《俄罗斯报》表示，乌克兰武装部队总司令亚历山大·瑟尔斯基宣称乌俄之间存在决定性对抗，实际上是在执行欧洲提出的“战至最后一个乌克兰人”计划。
Поступили сведения о достижениях российских вооруженных сил под Константиновкой20:59