{"slug": "the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement", "title": "The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement", "summary": "A paper submitted to arXiv on 10 Sep 2026, titled \"The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement,\" proposes a development roadmap for recursive self-improvement (RSI) in AI systems. The paper uses the Headroom-Closed Index (HCI) to identify problems in existing large language models, then outlines five stages of RSI: improvement-execution autonomy, improvement-strategy autonomy, experience-acquisition autonomy, environment-adaptation autonomy, and recursive meta-improvement. The authors examine RSI across scientific discovery, embodied intelligence, and software engineering, and identify key challenges to achieving genuine RSI.", "body_md": "# Computer Science > Machine Learning\n\n  [Submitted on 10 Sep 2026]\n\n# Title:The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement\n\n[View PDF](/pdf/2609.11873)\n\n[HTML (experimental)](https://arxiv.org/html/2609.11873v1)\n\nAbstract: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.\n    \n\n### Current browse context:\n\ncs.LG\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer \n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers \n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps \n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations \n\n*(*[What are Smart Citations?](https://www.scite.ai/))\n# Code, Data and Media Associated with this Article\n\nalphaXiv \n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers \n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub \n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub \n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face \n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast \n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))\n# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower \n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender \n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\nIArxiv Recommender\n\n*(*[What is IArxiv?](https://iarxiv.org/about))\n# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [**Learn more about arXivLabs**](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement", "canonical_source": "https://arxiv.org/abs/2609.11873", "published_at": "2026-09-13 22:06:45+00:00", "updated_at": "2026-09-13 22:22:08.634812+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "ai-research", "ai-safety"], "entities": ["arXiv", "Headroom-Closed Index", "recursive self-improvement"], "alternates": {"html": "https://wpnews.pro/news/the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement", "markdown": "https://wpnews.pro/news/the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement.md", "text": "https://wpnews.pro/news/the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement.txt", "jsonld": "https://wpnews.pro/news/the-last-ai-built-by-humans-toward-genuine-recursive-self-improvement.jsonld"}}