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.
物理遮蔽光线,永远比纯靠前置摄像头识别人脸去隐藏通知或是干脆贴上物理的光栅防窥膜来得更彻底。这项技术一旦铺开,那些劣质防窥膜大概率会被彻底扫进历史的垃圾堆。
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