Recursive Self-Improvement in AI: From I.J. Good to Modern Frontier Labs
By
Lilian Weng
Summary
This article explores the concept of recursive self-improvement (RSI) in artificial intelligence, tracing its origins to I. J. Good's 1965 definition of an "ultraintelligent machine" and Yudkowsky's 2008 framing of a feedback loop where AI uses its intelligence to improve its own cognitive machinery. The piece discusses how this manifests in modern AI systems, including direct weight rewriting and improvements to training pipelines and deployment systems that enable better successor models, noting the accelerated pace of research development in frontier AI labs like Anthropic and OpenAI.
Source
Twitter / XRecursive Self-Improvement in AI: From I.J. Good to Modern Frontier Labslilianweng.github.ioKey quotes
· 3 pulledThe concept of recursive self-improvement (RSI) dates back to I. J. Good (1965), where he defined an 'ultraintelligent machine' as a system that can surpass humans in all intellectual activities and design better machines to improve itself.
Yudkowsky (2008) used the phrase 'recursive self-improvement' for a specific feedback loop: an AI uses its current intelligence to improve the cognitive machinery that produces its intelligence.
The speed of research development in AI has been shown to drastically accelerated in frontier labs (Anthropic; OpenAI).
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