你有没有想过，未来的AI不仅能回答你的问题，还能从与你的每一次互动中汲取经验，悄悄进化？它甚至还能在犯错后“自我反思”，像我们一样“长记性”。本期我们将一起探索几篇最新论文，看看AI如何学会像一个聪明的“CEO”一样管理自己的思考，如何通过精准“剪枝”在你的手机里狂飙，以及如何消灭那些你看不到的“计算成本”，变得更高效、更智慧。00:00:32 AI进化论，为什么你的“差评”正在喂养一个更聪明的它00:05:19 让AI在手机里狂飙，快，才是一切00:10:38 AI提速19%的秘密，你以为的计算，其实是搬运00:15:20 AI犯了错，能不能让它自己“长记性”？00:21:26 你的大脑里，缺一个聪明的“CEO”本期介绍的几篇论文：[CL] Online Experiential Learning for Language Models [Microsoft Research] https://arxiv.org/abs/2603.16856---[LG] MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale [Meta AI] https://arxiv.org/abs/2603.15954---[LG] FlashSampling: Fast and Memory-Efficient Exact Sampling [LMU Munich & FlashSampling & Princeton University] https://arxiv.org/abs/2603.15854---[LG] Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models [Tsinghua University & JD.COM] https://arxiv.org/abs/2603.15724---[RO] When Should a Robot Think? Resource-Aware Reasoning via Reinforcement Learning for Embodied Robotic Decision-Making [CMU & Northeastern University & Harvard University] https://arxiv.org/abs/2603.16673

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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