内塔尼亚胡表示，在当前美以对伊朗进行的轰炸行动中，除了旨在摧毁伊朗的导弹和核能力外，还创造条件让伊朗人民能够推翻当前政权。他还表示以色列正在对伊朗革命卫队、他们的基地、街头武装以及哨所进行毁灭性打击——而更猛烈的行动还在后面。
$ ls $HOME/.be/replicated.live/，推荐阅读51吃瓜获取更多信息
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Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.。关于这个话题，新闻提供了深入分析
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