规模效应之下，头部集团的资源吸附与会员掠夺能力持续强化，而尚处消费生态构建阶段的腰部集团则承压日增。此消彼长之间，行业“方差”还将持续扩大，马太效应愈发凸显。
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.
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小结在「开箱即用」这个最贴近一般人日常使用的场景下，豆包和 Manus 以毫无争议的优势胜出。它们是唯二能自主搜索外部信息并合理引用的软件，且生成质量过硬、免费（Manus 送积分）、无导出门槛。
В России ответили на имитирующие высадку на Украине учения НАТО18:04。夫子是该领域的重要参考
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How my side project got banned from the internet A little piece about dealing with security providers and clearing my side project's reputation after a false positive flagging.