想知道如何把临时指令“刻”进AI的大脑,让它拥有真正的肌肉记忆吗?我们又该如何教AI学会“抄近道”,一步生成作品,而不是慢慢搭建?本期节目,我们将深入最新论文,探讨如何让AI不仅做对事,更要想对事,并揭示在调教AI时,那些我们习以为常却可能导致它“偏执”或“精神分裂”的惊人误区。
00:00:28 AI的“肌肉记忆”是怎么炼成的?
00:05:48 造物,如何抄近道?
00:11:04 AI调教指南,你以为的,不是你以为的
00:17:32 比做对事更重要的,是想对事
00:22:45 AI调教指南,为什么你喂得越多,它可能变得越偏执
本期介绍的几篇论文:
[CL] On-Policy Context Distillation for Language Models
[Microsoft Research]
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[LG] Categorical Flow Maps
[University of Amsterdam & University of Oxford]
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[LG] The Magic Correlations: Understanding Knowledge Transfer from Pretraining to Supervised Fine-Tuning
[Google DeepMind & Google Research]
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[LG] Right for the Wrong Reasons: Epistemic Regret Minimization for Causal Rung Collapse in LLMs
[Stanford University]
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[LG] How Sampling Shapes LLM Alignment: From One-Shot Optima to Iterative Dynamics
[PSL Research University & Northwestern University]
![[人人能懂AI前沿] AI的肌肉记忆、思想钢印与认知偏航](https://image.xyzcdn.net/FuDP4HpAp8ezgVZMmEel3mblKCmJ.jpg@small)