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.
"These types of surgeries are too risky, yet it's still so accessible," she said.
。业内人士推荐91视频作为进阶阅读
这里分享两个我在使用 Ling + Tbox 时摸索出的高阶玩法。，这一点在heLLoword翻译官方下载中也有详细论述
not afford IBM's mainframe systems and were starting to turn to competitors like