本期我们要聊的几篇最新论文,简直就像是AI上演了一出精彩的“进化三重奏”。你有没有想过,AI不仅能亲自下场做实验,还能通过扔掉海量信息反而学得更快?我们还会看到,AI如何像一个不眠不休的科研团队那样在失败中进化,像军队一样高效分工,以及这一切的背后,如何靠一本“备忘录”将所有经验沉淀为真正的智慧。准备好了吗?让我们一起探索AI正在解锁的全新可能性!
AI 不再只是“思想家”,它开始“动手”了
AI 进化新思路,扔掉 95% 的信息,反而学得更好?
AI的“试错”进化论
将军与士兵,人工智能的完美分工
给AI装个“备忘录”,为什么笨办法反而是真聪明?
本期介绍的几篇论文:
[AI] Accelerating Scientific Research with Gemini in the Real-World
[Google DeepMind & Duke University & Columbia University]
---
[CV] LeVJEPA: Efficient & Scalable Video Pretraining without the Heuristics
[German Cancer Research Center & Mila]
---
[AI] AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design
[Hunan University & Nanjing University & The Chinese University of Hong Kong]
---
[AI] Decoupling Planning and Control for Instructable Agents
[UC Berkeley & Google DeepMind]
---
[AI] WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution
[Google Research]
![[人人能懂AI前沿] 从动手实践、信息减法到知识沉淀:AI进化新思路](https://image.xyzcdn.net/FqWpK8fpivLboaqBbRHUe_BCOvxu.png@small)