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.
Москвичей предупредили о резком похолодании09:45
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舞池两侧，专门接待日本客人、手下都是“老虎”的两位“公公”不时在各自的小姐身边逡巡，神情警觉，又有点闷闷不乐。一晚上，偶尔出现的几只“猎物”，也会被他们抢夺分食，而生存最大的资本就是小姐的本事。。WPS官方版本下载对此有专业解读
Варвара Кошечкина (редактор отдела оперативной информации)