Jack Clark: “We've seen both a tremendous advancement in the ability for AI systems to make creative-seeming math breakthroughs … I now think it's more likely we'll see full RSI become possible in 2027, whereas before I thought it was more likely in 2028”
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· Science · Anthropic co-founder, in his Import AI newsletter, on a benchmark of models’ research taste; in May he put at 60% the chance that by the end of 2028 a model could train its own successor on its own
original
“Why this matters – RSI: In my analysis of recursive self-improvement (AI Systems Are About To Start Building Themselves, Import AI 455), I repeatedly noted that creativity seemed like a key variable for how fast AI systems could develop the capacity to improve themselves. At the beginning of this year I said "AI systems haven't yet displayed this [creativity] in a transformative and major way (though some of the results on accelerating math research are suggestive of this)". I think subsequent to writing that we've seen both a tremendous advancement in the ability for AI systems to make creative-seeming math breakthroughs, and with benchmarks like this we see some signs they're becoming increasingly good at AI research as well. I now think it's more likely we'll see full RSI become possible in 2027, whereas before I thought it was more likely in 2028.”— Jack Clark, Import AI 476, 12.10.2026 ↗
backs
Large language model+Reinforcement learning → AI in mathematics (2024)
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The original is given verbatim and only as an excerpt — as much as the meaning needs; “[…]” marks a cut. The translation is ours.
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