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[人人能懂] 从学会走路，到打通游戏，再到过目不忘
你有没有想过，AI的“开窍”瞬间，背后藏着什么样的秘密？这一期，我们将一口气解锁五篇最新论文，探讨AI智能的进化法则。我们会发现，为什么让AI的大脑长得“更高”而不是“更胖”，能让它学会体操一样的神操作；为什么“学得快”的AI画家比“学得久”的更有创造力；以及AI是如何通过自我复盘和深度研究，从一个模仿者，成长为能打通复杂游戏的通才。
00:00:33 人工智能的成长秘密：与其更胖，不如更高
00:04:46 AI画画，为什么“学得快”的比“学得久”的更聪明？
00:09:32 不止是模仿：机器人如何学会自我迭代
00:14:42 AI上岗：我们是怎么教会它打通一款游戏的？
00:20:44 你的大脑不是硬盘，而是搜索引擎
本期介绍的几篇论文：
[LG] 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
[Princeton University]
https://openreview.net/forum?id=s0JVsx3bx1
---
[LG] Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
[Université PSL]
https://arxiv.org/abs/2505.17638
---
[LG] π∗0.6: a VLA That Learns From Experience
[Physical Intelligence]
https://arxiv.org/abs/2511.14759
---
[AI] Lumine: An Open Recipe for Building Generalist Agents in 3D Open Worlds
[ByteDance Seed]
https://arxiv.org/abs/2511.08892
---
[CL] General Agentic Memory Via Deep Research
[Beijing Academy of Artificial Intelligence]
https://arxiv.org/abs/2511.18423
View all episodes
By fly51fly你有没有想过，AI的“开窍”瞬间，背后藏着什么样的秘密？这一期，我们将一口气解锁五篇最新论文，探讨AI智能的进化法则。我们会发现，为什么让AI的大脑长得“更高”而不是“更胖”，能让它学会体操一样的神操作；为什么“学得快”的AI画家比“学得久”的更有创造力；以及AI是如何通过自我复盘和深度研究，从一个模仿者，成长为能打通复杂游戏的通才。
00:00:33 人工智能的成长秘密：与其更胖，不如更高
00:04:46 AI画画，为什么“学得快”的比“学得久”的更聪明？
00:09:32 不止是模仿：机器人如何学会自我迭代
00:14:42 AI上岗：我们是怎么教会它打通一款游戏的？
00:20:44 你的大脑不是硬盘，而是搜索引擎
本期介绍的几篇论文：
[LG] 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
[Princeton University]
https://openreview.net/forum?id=s0JVsx3bx1
---
[LG] Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
[Université PSL]
https://arxiv.org/abs/2505.17638
---
[LG] π∗0.6: a VLA That Learns From Experience
[Physical Intelligence]
https://arxiv.org/abs/2511.14759
---
[AI] Lumine: An Open Recipe for Building Generalist Agents in 3D Open Worlds
[ByteDance Seed]
https://arxiv.org/abs/2511.08892
---
[CL] General Agentic Memory Via Deep Research
[Beijing Academy of Artificial Intelligence]
https://arxiv.org/abs/2511.18423