This AI recursive self improvement (RSI) paper shows no sign of fast takeoff. The AI model advances at about [Intelligence]^0.075, or the th…

This AI recursive self improvement (RSI) paper shows no sign of fast takeoff. The AI model advances at about [Intelligence]^0.075, or the the 13th root of input intelligence [1,2]. That means the intelligence explosion fizzles out rapidly. 1 - I expect this team or others to do much better than this over time! But no sign they'll get to an exponent even approaching 1.0, which is what you need for runaway self-improvement. 2 - The actual rate of self improvement is probably even worse than the math shows, as this is improvement on a specific metric rooted in a specific training set which taps out at a finite capability cap. Actual improvement on some training-set-independent scale of intelligence is probably log-linear, not merely power-law scaled. I'm super impressed with this work and the team, to be clear! Just not seeing a Singularity on the horizon. Totally awesome to see evidence of AI self-improvement! (Though I'd call @karpathy's auto-research the first.) And, as expected, self-improvement here shows diminishing returns over time. Significant initial boost. Smaller subsequent boost in each iteration. That's exactly what t…

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Source: Gary Marcus (X) | 2026-07-15