你有没有想过，AI要如何像高手一样，同时“试驾”多种思路？我们又该如何给狂飙的AI装上“定速巡航”，让它在学习时永不“翻车”？今天，我们就从几篇最新的AI论文出发，聊一聊AI要如何学会“分身术”思考，如何跳出“思维定式”的陷阱，甚至，我们以后可能再也不用费劲地给AI设定KPI，直接“说人话”就能让它们完美协作。准备好了吗？让我们一起探索AI思考方式的深层变革。00:00:35 如何像高手一样思考？答案可能在“分身术”里00:05:07 给狂飙的AI装上定速巡航00:09:57 思维定式是怎么炼成的？AI给了我们一个新答案00:15:23 怎么让AI大模型学会“左右互搏”？00:21:37 AI界的“KPI”革命，未来我们不用再跟机器打哑谜本期介绍的几篇论文：[CL] Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge[Microsoft Research & University of Pennsylvania]https://arxiv.org/abs/2601.08808---[LG] Controlled LLM Training on Spectral Sphere[Microsoft Research Asia & Renmin University]https://arxiv.org/abs/2601.08393---[LG] Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs[MIT & NUS]https://arxiv.org/abs/2601.08763---[LG] Reverse Flow Matching: A Unified Framework for Online Reinforcement Learning with Diffusion and Flow Policies[MIT]https://arxiv.org/abs/2601.08136---[LG] The End of Reward Engineering: How LLMs Are Redefining Multi-Agent Coordination[New York University & Lerna AI]https://arxiv.org/abs/2601.08237

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

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