Thinking Machines Lab co-founder Lilian Weng says human goal specification remains essential as AI self-improvement loops automate

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The analysis explores engineering evaluation harnesses to safely guide recursive self-improvement

Harness Engineering for Self-ImprovementThe 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. This feedback loop in modern AI may indicate the model rewriting its own weights directly, or more broadly the model improves the training pipeline and the deployment system, which in turn enables a better successor model with improved performance across economically valuable tasks. The speed of research development in AI has been shown to drastically accelerated in frontier labs (Anthropic; OpenAI).4h agoLil'Log

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Ferbin@Ferbin08TECH

@lilianweng harness engineering is the easy part. feedback loops that actually work in production are hard. skip that and auto-research dies in the lab.

Thinking Machines Lab co-founder Lilian Weng says human goal specification remains essential as AI self-improvement loops automate

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