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节目简介
来源：小宇宙
你有没有想过，我们不仅能看懂AI的“鬼点子”，还能直接让它把克敌制胜的“武功秘籍”写成代码？本期节目，我们将一起探索几篇最新论文带来的奇妙洞见：我们会发现AI的“中年健忘”竟是与生俱来的天性，并找到它大脑里那个精准的“谎言开关”。我们不仅要科学地为AI制定最佳“学习计划”，甚至还要在它读书前，先送它去一个纯粹的“数字健身房”锻炼核心能力。准备好了吗？让我们一起出发，看看AI的聪明才智背后，藏着哪些你意想不到的秘密。
00:00:39 当AI学会了写代码，它的“鬼点子”就藏不住了
00:05:48 AI的学习计划，应该怎么定？
00:12:05 大模型的“中年危机”，我们一直都搞错了？
00:17:37 别再被AI骗了，我们找到了它大脑里的“谎言开关”
00:23:23 AI的“健身房”，不读书，如何变得更聪明？
本期介绍的几篇论文：
[LG] Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models
[Google DeepMind]
https://arxiv.org/abs/2603.10098
---
[LG] What do near-optimal learning rate schedules look like?
[Google DeepMind & Mila]
https://arxiv.org/abs/2603.10301
---
[LG] Lost in the Middle at Birth: An Exact Theory of Transformer Position Bias
[Meta]
https://arxiv.org/abs/2603.10123
---
[CL] Adaptive Activation Cancellation for Hallucination Mitigation in Large Language Models
[Dakota State University & North Carolina A&T State University]
https://arxiv.org/abs/2603.10195
---
[LG] Training Language Models via Neural Cellular Automata
[MIT]
https://arxiv.org/abs/2603.10055
00:00:39 当AI学会了写代码，它的“鬼点子”就藏不住了
00:05:48 AI的学习计划，应该怎么定？
00:12:05 大模型的“中年危机”，我们一直都搞错了？
00:17:37 别再被AI骗了，我们找到了它大脑里的“谎言开关”
00:23:23 AI的“健身房”，不读书，如何变得更聪明？
本期介绍的几篇论文：
[LG] Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models
[Google DeepMind]
https://arxiv.org/abs/2603.10098
---
[LG] What do near-optimal learning rate schedules look like?
[Google DeepMind & Mila]
https://arxiv.org/abs/2603.10301
---
[LG] Lost in the Middle at Birth: An Exact Theory of Transformer Position Bias
[Meta]
https://arxiv.org/abs/2603.10123
---
[CL] Adaptive Activation Cancellation for Hallucination Mitigation in Large Language Models
[Dakota State University & North Carolina A&T State University]
https://arxiv.org/abs/2603.10195
---
[LG] Training Language Models via Neural Cellular Automata
[MIT]
https://arxiv.org/abs/2603.10055
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