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Laura CressTechnology reporter，这一点在搜狗输入法2026中也有详细论述
，这一点在搜狗输入法2026中也有详细论述
Keys that have a warning icon, meaning they are set to unrestricted，这一点在同城约会中也有详细论述
在2026年的就业市场中，熟练掌握AI工具进行协同办公已不再是加分项，而是类似“会用Office”的基础职业准则 [4, 25]。普通人的核心竞争力正发生显著位移：从过去的“执行力”转向“策划力（Curation）”与“裁判权（Judgment）” [4]。
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.