本期我们将为你硬核拆解五篇极具启发性的最新论文，带你看看AI如何从“冷面判官”变身为手把手教你改论文、跑实验的“私人医生”。我们还会探讨如何利用存内计算把大模型塞进普通硬盘，并揭秘高效大模型到底为什么总爱“死记硬背”却学不会“活学活用”。最后，我们将一起见证AI如何通过“元认知操纵”掌握科学家的真实直觉，以及如何用文本优化技术揪出海量数据里隐藏的危险“潜台词”。00:00:36 你的论文，需要一位AI私人医生00:05:44 AI太贵？咱们把它塞进硬盘里算00:11:07 死记硬背还是活学活用？AI的成长烦恼00:16:16 AI的“驾驶术”，如何教会机器科学家的直觉00:22:18 数据里的“潜台词”，我们怎么听懂？本期介绍的几篇论文：[CL] PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress[University of Oxford & National University of Singapore & Stanford University]https://arxiv.org/abs/2609.16995 ---[LG] LLM Inference in a Flash![UC Berkeley]https://arxiv.org/abs/2609.16161 ---[LG] On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models[Harvard University & Apple]https://arxiv.org/abs/2609.16540 ---[AI] Metacognitive Steering: Learning the Structure of Scientific Judgment[Autopoiesis Sciences]https://arxiv.org/abs/2609.16245 ---[LG] Verbalizing Subliminal Learning Effects Using Text Optimization[Stanford University]https://arxiv.org/abs/2609.16927 在小宇宙查看该单集文稿

Ask this episode

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

Transcript

Related