| title | The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement |
|---|---|
| authors | Yi Duan, Ying Liu, Zirui Tang, Haodong Chen, Jun Zhou, Yumou Liu, Bangrui Xu, Yukai Wu, Sidi Chen, Yuhan Zhou, Haoyu Wang, Xiaoyou Yu, Shaokun Han, Xuzhou Zhu, Le Zhou, Bolin Lu, Wei Zhou, Jiachen Liu, Nuozhou Fang, Jiaxin Tian, Ruoyu Chen, Yuxuan Li, Kai Zuo, Kaiyan Zhang, Jiantao Qiu, Conghui He, Guoliang Li, Bowen Zhou, Zhiyuan Liu, Zhoufutu Wen, Jihua Kang, Xuanhe Zhou, Fan Wu |
| date | 2026-09-10 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2609.11873 |
| upvotes | 19 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improvement. We first use the Headroom-Closed Index (HCI) to reveal the problems of existing LLMs, then introduce the RSI concept and its development roadmap: from improvement-execution autonomy, improvement-strategy autonomy, experience-acquisition autonomy, and environment-adaptation autonomy, to recursive meta-improvement. Next we examine RSI across scenarios (e.g., scientific discovery, embodied intelligence, software engineering), highlighting their distinct requirements and development speeds. Drawing on diverse industry practices and preliminary empirical evidence, we connect RSI research with practical systems and identify key challenges to achieving genuine RSI. |
cite
@misc{duan2026last,
title={The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement},
author={Yi Duan and Ying Liu and Zirui Tang and Haodong Chen and Jun Zhou and Yumou Liu and Bangrui Xu and Yukai Wu and Sidi Chen and Yuhan Zhou and Haoyu Wang and Xiaoyou Yu and Shaokun Han and Xuzhou Zhu and Le Zhou and Bolin Lu and Wei Zhou and Jiachen Liu and Nuozhou Fang and Jiaxin Tian and Ruoyu Chen and Yuxuan Li and Kai Zuo and Kaiyan Zhang and Jiantao Qiu and Conghui He and Guoliang Li and Bowen Zhou and Zhiyuan Liu and Zhoufutu Wen and Jihua Kang and Xuanhe Zhou and Fan Wu},
year={2026},
eprint={2609.11873},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2609.11873}
}