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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Comparison of the N-closest and N-convex algorithms using an 8-colour irregular palette with . Left to right: N-closest, N-convex.，推荐阅读搜狗输入法下载获取更多信息
Басманный районный суд Москвы избрал меру пресечения заместителю председателя правления «Газпром нефть» Антону Джалябову, обвиняемому в получении особо крупных взяток. Видео с ним предоставили «Ленте.ру» в пресс-службе судов общей юрисдикции столицы.
Hwæthere is a false friend - related to modern "whether"+e, but it means "nevertheless"