// Flush: yield any remaining data
曾国藩、王船山意见，乍见则骇人听闻，然而细思乃有至理深义。其实古人对此早有评论：“衣食分人，曹刿指为小惠；乘舆济人，孟子谓非政要。”义仓、社仓等等与各位的捐赠一样，只是花钱做了衣食分人及乘舆济人的一般的、简单的、浅层次的事。如同用药治病，只是敷在表皮，略缓病痛，没有用在病灶上。
，更多细节参见safew官方版本下载
Twig's Ben Hartwig says the company is now eyeing expansion，推荐阅读雷电模拟器官方版本下载获取更多信息
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.
Дарья Устьянцева (редактор отдела «Мир»)