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.
他们大多是社区里的退休居民，用无偿服务，既降低了医院的运营成本，也给老年患者带来了专属的温暖。，更多细节参见同城约会
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这个文集可谓是众星云集，齐聚了近 30 位商业、设计、科技等领域领军人物，如苹果现任 CEO 蒂姆 · 库克、前苹果首席设计师乔纳森 · 艾维、日本建筑师安藤忠雄、德国设计师迪特 · 拉姆斯，等等。他们以「给年轻创作者一封信」的形式，分享了各自创造、设计、人生的深刻洞见。
Comparison between Thomas Knoll’s algorithm and the N-convex algorithm, using an 8-colour irregular palette. Left to right: original image, Knoll, N-convex ().，更多细节参见safew官方下载
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