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.
13. Taylor Tomlinson: Prodigal Daughter
。关于这个话题，51吃瓜提供了深入分析
特点：在 ReLU 的基础上引入概率思想，让激活与输入大小平滑相关。。夫子是该领域的重要参考
第五十条 任何个人和组织不得实施下列侵害未成年人合法权益、损害未成年人身心健康的行为：。Line官方版本下载对此有专业解读