Трамп высказался о непростом решении по Ирану

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报道援引联合反恐小组一名不愿透露姓名的高级官员的话说,警方在邦迪滩两名枪手车内发现一面“伊斯兰国”旗帜。澳大利亚安全情报组织6年前就已在调查邦迪滩枪击案两名枪手之一的纳维德·阿克拉姆,他与“伊斯兰国”在悉尼的恐怖分子有密切联系。

If you just want to be told today's puzzle, you can jump to the end of this article for the latest Connections solution. But if you'd rather solve it yourself, keep reading for some clues, tips, and strategies to assist you.

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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.