（十一）实施利益要挟。凭借“网红”身份，以在网上曝光他人为要挟，要求给予特殊服务、“优惠免单”等优待，或在公共场合实施扰乱社会秩序等行为。
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，详情可参考旺商聊官方下载
«На мой взгляд, это, наверное, худшие январь-февраль за последние 20 лет ведения статистики. Если еще и методику подсчета рынка чуть подправить и учитывать именно новые автомобили, которые реально продаются и ставятся на регистрацию, рынок по факту еще хуже», — говорит эксперт.
"We chose a threshold that requires a few searches within a short period of time, while still erring on the side of caution," Instagram's blog post explains. "While that means we may sometimes notify parents when there may not be real cause for concern, we feel — and experts agree — that this is the right starting point, and we’ll continue to monitor and listen to feedback to make sure we’re in the right place."
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.