[人人能懂AI前沿] 从信噪比、凸优化到底线思维：重塑AI的五个底层逻辑

你有没有想过，为什么AI会越练越笨，甚至被人类“算计”？本期节目，我们将一口气解锁五篇最新论文带来的颠覆性思考：从用香农定律解释AI的“U型学习曲线”，到仅用一块显卡就能“调教”出听话的大模型；从赋予AI“底线思维”来应对未知风险，到让它写出“绝对正确”的关键代码；最后，我们还会看到AI如何从“看图识字”进化到真正“读懂规矩”。准备好，一场关于AI思维升级的风暴即将来临！00:00:37 你的模型为什么越练越笨？00:07:11 AI大模型调教指南，如何用一块显卡搞定？00:12:44 面对“深不可测”的世界，AI如何做出明智选择？00:18:45 AI开始写“绝对正确”的代码了00:23:43 AI的新玩法，从“看图识字”到“读懂规矩”本期介绍的几篇论文：[LG] LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws [ByteDance Seed] https://arxiv.org/abs/2605.23901 ---[LG] Convex Optimization for Alignment and Preference Learning on a Single GPU [Stanford University] https://arxiv.org/abs/2605.23244 ---[LG] Infra-Bayesian Reinforcement Learning Agents Outperform Classical RL For Worst-Case Robustness [Purdue University & CMU & WorldQuant University] https://arxiv.org/abs/2605.23146 ---[AI] Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems [UC Berkeley] https://arxiv.org/abs/2605.23109 ---[CV] General Hazard Detection [Swinburne University of Technology] https://arxiv.org/abs/2605.23304 在小宇宙查看该单集文稿