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这项由香港科技大学（HKUST）领衔的研究，为我们展示了一种“Code as Action, State as Memory”的全新可能性。它解决了所有开发过复杂Agent的工程师最头疼的多轮对话中的“失忆”与“漂移”问题。

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如今大模型AI领域的绝大多数概念都是在一个基础功能上打补丁、堆砌。 底层大模型非常非常牛，但也有其自身底层上的局限性。别看大模型一代一代地推出，技术上其实是停滞不前的。 但应用层呢，楼房已经盖到几千层了： 大模型只有一个能力，输入文本序列+温度等参数=>输出文本序列。 多轮对话？记忆功能？就是把上一次的对话和这一次的问题用字符串拼起来。