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.
await scene.play(new Transform(square, circle));，推荐阅读雷电模拟器官方版本下载获取更多信息
，这一点在爱思助手下载最新版本中也有详细论述
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; Eventually returns to the RETF caller here: