你有没有想过，为什么AI不能像个身手敏捷的伙伴一样装进我们的手机？我们又该如何升级自己的“预测操作系统”，让决策更精准？本期节目，我们将从几篇最新的AI论文出发，聊一聊如何给AI来一场“智慧瘦身”，如何用八分之一的成本办成同样的事，甚至是如何找到AI内部的“隐藏开关”，让它乖乖“变身”。我们还会一起探索一个奇妙的问题：不同的AI模型，为什么会像生物一样“趋同进化”？

00:00:33 AI太“胖”装不进手机？给它来一场“智慧瘦身”

00:05:24 升级你的“预测操作系统”

00:11:20 如何用1/8的成本，办成同样的事？

00:16:40 AI的隐藏开关，如何让它“听话”地变身？

00:21:35 AI 的“趋同进化”，为什么聪明和“看起来聪明”是两回事

本期介绍的几篇论文：

[LG] Hyperloop Transformers: Hyperloop Transformers  

[MIT]  

https://arxiv.org/abs/2604.21254 

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[AI] Agentic Forecasting using Sequential Bayesian Updating of Linguistic Beliefs: Agentic Forecasting using Sequential Bayesian Updating of Linguistic Beliefs  

[University of British Columbia]  

https://arxiv.org/abs/2604.18576 

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[LG] FASTER: Value-Guided Sampling for Fast RL: FASTER: Value-Guided Sampling for Fast RL  

[Stanford University]  

https://arxiv.org/abs/2604.19730 

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[LG] ConforNets: Latents-Based Conformational Control in OpenFold3: ConforNets: Latents-Based Conformational Control in OpenFold3  

[Columbia University & Princeton University]  

https://arxiv.org/abs/2604.18559 

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[CL] Convergent Evolution: How Different Language Models Learn Similar Number Representations: Convergent Evolution: How Different Language Models Learn Similar Number Representations  

[University of Southern California & UC San Diego]  

https://arxiv.org/abs/2604.20817