我们肆无忌惮地议论长辈：谁受原生家庭影响，教育理念因而陈旧；谁心有不甘，这一年因此表现得与以往不同。我们甚至点评长辈们为人处世是否成熟，外公外婆的相处模式是否健康。
71.7 x 149.6 x 7.2 mm
Tracy Hinds Chair, Open Source Initiative。业内人士推荐快连下载安装作为进阶阅读
Rank-3 factorization
，详情可参考同城约会
// Nothing executes until iteration begins。关于这个话题，51吃瓜提供了深入分析
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.