Mass die-offs rising among farmed salmon
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根据 ITC 终裁，GoPro 指控的六项专利争议中，五项被裁定为不构成侵权或相关专利权无效；针对剩余一项外观专利，影石提出的新设计方案也获 ITC 确认不构成侵权。，详情可参考safew官方下载
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.