这期我们来聊聊，怎样把一个AI从“通才”培养成“专才”，甚至让它学会不只是解决问题，而是先为自己打造一套“专属工具”？一个AI团队如何开“聪明会”，以及它怎样才能记住过去的经验，不再傻乎乎地重复劳动？最后，我们会看到一个大胆的设想：要是我们干脆给AI换一个来自“流体力学”的引擎，又会发生什么？让我们一起进入今天的前沿探索。
00:00:31 给你一个好苗子，怎么把它培养成翻译大师？
00:05:23 别让聪明人开“笨蛋会”
00:12:07 你的时间，只够用在刀刃上
00:17:22 高手做事，都是先打造工具
00:22:37 给AI换个“流体力学”引擎，会发生什么？
本期介绍的几篇论文：
[CL] TranslateGemma Technical Report
[Google Translate Research Team]
https://arxiv.org/abs/2601.09012
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[LG] Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning
[MIT & NYU & Microsoft]
https://arxiv.org/abs/2601.09667
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[LG] SRT: Accelerating Reinforcement Learning via Speculative Rollout with Tree-Structured Cache
[Cornell University & University of Illinois Urbana-Champaign & University of Washington]
https://arxiv.org/abs/2601.09083
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[LG] Programming over Thinking: Efficient and Robust Multi-Constraint Planning
[Nanyang Technological University & Agency for Science, Technology and Research (A*STAR)]
https://arxiv.org/abs/2601.09097
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[LG] Spectral Generative Flow Models: A Physics-Inspired Replacement for Vectorized Large Language Models
[UC Berkeley]
https://arxiv.org/abs/2601.08893