海外媒体随即跟进,复述了 Anthropic 的话术。然而这套叙事逻辑很快就翻车了:毕竟「蒸馏」这件事美国 AI 公司训练的时候也会做,更何况 Anthropic 自己也有类似行为:
迈入“十五五”,“常态化帮扶”纳入乡村振兴战略统筹实施,开启加快农业农村现代化新征程。。业内人士推荐Line官方版本下载作为进阶阅读
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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.,更多细节参见heLLoword翻译官方下载
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