huge machines processed currency to pick out bad bills. This use of "high-speed"
龙先生说，事发在今年7月份，直到10月18日母亲意识到被骗才报案。为弄清母亲被骗的全过程，龙先生花了数十天的时间，浏览了母亲跟骗子所有的聊天记录及手机操作流程，探寻了骗子的行骗手段，并行之成文，直到11月份才完成这些工作。
，这一点在WPS官方版本下载中也有详细论述
Even the simplest rewrite rule—say, replacing a deprecated message with a new one—usually sends me hunting for examples. During this project I spent a lot of time deep inside the rewrite engine, and even now I cannot reliably recall the exact syntax.
In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.