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.
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在各地解封之後,中國經歷了一波感染新冠疫情的高峰,劉亮憶述,當時有不少認識的長輩離世,回到老家湖南之後,他參加了很多場喪事,「心裡面特別不舒服......太難受,不斷喝白事的酒。」
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