[人人能懂AI前沿] AI学会了办事、复盘和成长，但它为何还会被骗？

你有没有想过，为什么最聪明的AI，有时会犯下最令人匪夷所思的错误？本期我们要聊的几篇最新论文，就揭示了这种矛盾：有的AI会因为一张伪造的“通行证”而放行危险代码，有的AI却已经学会了给自己“复盘”，在复杂研究中不断迭代进化。我们将一起探索，如何为AI模型进行精准的“功能性断舍离”，如何将它从一个“聊天搭子”升级为可靠的“办事帮手”，甚至，如何让虚拟世界里的角色拥有可以与世界共同成长的“灵魂”。准备好了吗？让我们一起潜入AI思想的最深处。00:00:41 那个看得见危险的哨兵，为什么还是放了行？00:06:13 如何看穿一个系统的“真本事”？00:12:06 AI的下一步，从“聊天”到“办事”00:17:56 让AI角色拥有“灵魂”的关键一步00:22:51 比勤奋更重要的，是会给自己“复盘”本期介绍的几篇论文：[AI] They'll Verify. They Just Won't Act. How Authority Framing and Laundered Code Turn a Trusted Agentic CI/CD Pipeline Into an Attack Surface[Senthex Research]https://arxiv.org/abs/2607.19267 ---[LG] Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks[Google DeepMind]https://arxiv.org/abs/2607.21366 ---[AI] Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes[University of Lethbridge & Universidad de Guadalajara]https://arxiv.org/abs/2607.19297 ---[CL] EvolvingWorld: An Open-Schema Framework for Co-Evolving Role-Play Agents and World Model in Interactive Literary World[Hong Kong University of Science and Technology & LIGHTSPEED]https://arxiv.org/abs/2607.17250 ---[AI] AREX: Towards a Recursively Self-Improving Agent for Deep Research[Beijing Academy of Artificial Intelligence (BAAI)]https://arxiv.org/abs/2607.21461 在小宇宙查看该单集文稿