保障劳动者权益。积极参与治理欠薪工作，起诉拒不支付劳动报酬犯罪1190人，支持农民工提起讨薪诉讼2.8万件，追索欠薪13.5亿元。开展新就业形态劳动者权益保障监督活动，办理公益诉讼690件。上海检察机关针对某些快递物流平台“延误就罚款”、“投诉即扣费”等问题，督促有关部门依法履职，推动优化算法规则，保障从业人员合法权益。
He has been a prominent voice calling for protests against Iran's authoritarian regime to continue.
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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.
Finnish startup Donut Lab is out to prove that its solid-state battery is all that it claims to be. Last week, the test was about fast charging. This week is where things get hot.