Researcher: Weakly Recursive Models May Blur the Line to Self-Improvement
S_OhEigeartaigh · x · 2026-11-11
AI governance researcher Seán Ó hÉigeartaigh argues that in practice there may be no clean separation between weakly recursive self-improvement and autonomous-experiment-driven improvement.
His reasoning: weakly recursive models can already run large numbers of experiments more or less autonomously, seeing what sticks and eking out incremental gains, with the occasional earth-moving insight. Over time, this ability to try far more things contributes to a greater capacity to "plan your own successor."
So even without strong recursive self-improvement, sheer volume of autonomous experimentation may keep pushing capability boundaries, making a tidy distinction between the two paths unrealistic.
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