今天我们要聊一个特别有意思的话题：AI训练是不是一定要“大力出奇迹”？本期节目将通过几篇最新的论文，带你探索AI如何从海量数据中提炼出真正的“结构性知识”，如何像老师傅一样“边干边学”适应新环境，甚至如何靠一个“黄金样本”就打通任督二脉。我们将一起见证，AI正从一个埋头苦干的“莽夫”，进化成一个懂得“刻意练习”的聪明手艺人。00:00:30 数据里，能“算”出新东西吗？00:07:38 让机器像人一样，边干边学00:12:36 AI训练的省钱秘笈，一块显卡如何干出两块的活？00:19:27 AI进化的秘密，从“大力出奇迹”到“一招鲜吃遍天”00:24:11 AI的“手艺”是怎么练成的？本期介绍的几篇论文：[LG] From Entropy to Epiplexity: Rethinking Information for Computationally Bounded Intelligence[CMU & New York University]https://arxiv.org/abs/2601.03220---[LG] In-Context Reinforcement Learning through Bayesian Fusion of Context and Value Prior[University of Cambridge & Mila - Quebec AI Institute]https://arxiv.org/abs/2601.03015---[LG] Chronicals: A High-Performance Framework for LLM Fine-Tuning with 3.51x Speedup over Unsloth[N/A]https://arxiv.org/abs/2601.02609---[LG] One Sample to Rule Them All: Extreme Data Efficiency in RL Scaling[GAIR & Taobao & Tmall Group of Alibaba]https://arxiv.org/abs/2601.03111---[LG] From Memorization to Creativity: LLM as a Designer of Novel Neural-Architectures[University of Würzburg]https://arxiv.org/abs/2601.02997

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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