Tsinghua study: AI agents lack "rethinking" capability, limiting Recursive Self-Improvement
TheTuringPost · x · 2026-08-26
A Tsinghua University study analyzing 1,338 AI post-training runs reveals a critical bottleneck for Recursive Self-Improvement (RSI). While AI agents can handle training, debugging, and iterating for hours, they rarely stop to "rethink" their fundamental approach. Once a strategy is chosen, agents tend to stick to it even when results suggest otherwise. Increased memory, skills, feedback, or compute did not break this pattern. The ability to iterate is not the same as the ability to rethink.
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