你有没有想过，我们该如何为机器人设计一个既能测出真本事又绝对安全的“想象考场”？或者，当AI也开始组团队时，我们如何避免“三个和尚没水喝”的窘境，并让它们自我进化出并行思考的“多核大脑”？一个机器人怎样才能不只学习“学霸笔记”，还能从自己“脑补”的错误中成长？而AI超强记忆力的秘诀，又是否藏在被我们一直丢弃的“另一半”信息里？本期节目，我们将一口气深入这五篇最新论文，探索AI能力边界的全新可能。00:00:37 机器人考场：从现实世界搬到AI的想象里 00:05:56 人多，力量一定大吗？AI团队协作的“科学”反思00:11:58 AI思维进化：从单线程到多核大脑00:17:38 让机器人“脑补”未来，光靠学霸笔记还不够00:23:17 AI的记忆秘诀：那个被丢掉的“另一半”本期介绍的几篇论文：[RO] Evaluating Gemini Robotics Policies in a Veo World Simulator[Google DeepMind]https://arxiv.org/abs/2512.10675---[AI] Towards a Science of Scaling Agent Systems[Google Research & MIT]https://arxiv.org/abs/2512.08296---[CL] Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning[Beijing Institute for General Artificial Intelligence (BIGAI)]https://arxiv.org/abs/2512.07461---[LG] Closing the Train-Test Gap in World Models for Gradient-Based Planning[Columbia University]https://arxiv.org/abs/2512.09929---[CL] Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs[Fudan University]https://arxiv.org/abs/2512.07525

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

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