The irony is that the very mechanism that makes LLMs powerful during training (e.g. compressing raw data into compact, transferable representations) is exactly what we refuse to let them do after deployment.
这是一个极具洞察力的反直觉观点。文章指出，正是训练过程中使LLMs强大的压缩机制，在部署后却被我们拒绝使用。这暗示我们可能正在错失让AI真正进化的关键机会，同时也提出了一个重要问题：为什么我们不让AI在部署后继续学习？