The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

2026-09-10

AI Summary

本文通过揭示现有LLM的问题并引入递归自我改进（RSI）的概念及发展路线图，探讨了在不同场景下实现真正RSI的关键挑战与方法。

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.

Problem

• Recursive Self-Improvement
• Large Language Models
• Headroom-Closed Index

Innovation

• Recursive Self-Improvement
• Headroom-Closed Index
• Autonomy