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Next Stage of AI Scientist: NanoResearch (Skills, Mem, RL)

2026-05-14 Science & Technology
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Description

This video shifts the perspective from Research Automation to Collaborative Agent-Human Co-evolution. An AI scientist shouldn't be a generic paper-generating factory; it must be a dynamic system whose parameter space continuously warps to internalize the unique research procedures or workflows and resource constraints of the specific lab it is deployed in. All rights with authors: NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation Jinhang Xu†1, Qiyuan Zhu†1,2, Yujun Wu†1,3, Zirui Wang†1,4, Dongxu Zhang†1,5, Jianxin Tang, Marcia Tian6, Yiling Duan1, Siyuan Li4, Jingxuan Wei1, Sirui Han∗2, Yike Guo∗2, Odin Zhang∗7, Conghui He∗1, Cheng Tan∗1 from 1 Shanghai Artificial Intelligence Laboratory, 2 The Hong Kong University of Science and Technology, 3 Peking University, 4 Zhejiang University, 5 Xi’an Jiaotong University, 6 East China University of Science and Technology, 7 The Chinese University of Hong Kong arXiv:2605.10813 #airesearch #aiscience #scientist #scientificdiscovery #aibasics

Top Comments (7)

@diga4696 2026-05-14

The signal to noise ratio provided here, is amazing.

3
@SimonStJohn 2026-05-14

This channel goes beyond spruking studies...it synthesises them into coherent learning and action paths. Thanks for your work?

2
@CreepyKiddo-y7s 2026-05-23

Personalization layer is what makes this work. Generic hits a ceiling fast. Same reason TII's Falcon team and MBZUAI build domain-specific stacks instead of importing off-the-shelf.

0
@ALifeInArtifyAI 2026-05-14

Nice, Thanks for sharing

4
@AlephCasara 2026-05-14

I keep watching your videos even having no math skills and no real computer science skills cause my data science college was terrible, but hey, good job I guess?

0
@Data_CPA 2026-05-16

Awesome!

0
@noobman4749 2026-05-15

Thanks

1 1 replies

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