Did an AI system truly solve Erdős Problem 728 autonomously?
This explores whether GPT-5.2 Pro and Aristotle independently resolved a decades-old open problem in mathematics, and what "autonomously" means when a human operator directed the search.
The writeup describes its result as "the first Erdős problem ... regarded as fully resolved autonomously by an AI system." The system was GPT-5.2 Pro by OpenAI combined with Aristotle by Harmonic, operated by Kevin Barreto. Its final output is "a formal proof written in Lean," which the authors "translate to informal mathematics in the present writeup for wider accessibility." The theorem is a logarithmic-gap window: for constants 0 < C1 < C2 and 0 < ε < 1/2 there are infinitely many triples (a, b, n) with a! b! | n! (a + b − n)! and C1 log n < a + b − n < C2 log n. The excerpt keeps two objects apart: the Lean proof, which is the formal object carrying the result, and the informal writeup, which is the route a human reader takes to follow it. This note keeps the same split.
The mechanism reduces the problem to the binomial divisibility (m+k choose k) | (2m choose m), with n = 2m, b = m and a = m + k. Working prime by prime, Kummer's theorem turns the p-adic valuation of (2m choose m) into a count of carries when m is doubled in base p (Lemma 3). A counting argument then selects, in each scale [M, 2M], an m whose base-p digits force many carries for every prime p ≤ 2k, while avoiding the case where one of m+1, …, m+k is divisible by an unusually high power of p. Lemma 4 bounds the factorial-weighted count by νp(k!) plus the largest single valuation in the window, and Lemma 5 treats primes above 2k as holding "for free." The writeup is terse at points: the proofs of Lemmas 1 and 2 consist of the single word "Immediate."
Against the nearest notes, the contrast with the Darwin Gödel Machine is sharp. Can AI systems improve themselves through trial and error? swaps formal proof for empirical validation on benchmarks. Here the object that counts is a formal proof, and the search runs over mathematical argument rather than over the system's own code. The guardrails pattern is a closer relation: Can deterministic checks protect LLM judges from failure? puts unarguable checks first. A Lean proof is about the most unarguable check available, and this source gives a case of one used without any LLM judgment at all.
The excerpt does not include the Lean code, the formal statement of Theorem 1, or the Lean check itself, so it cannot confirm that the formal statement matches the problem as posed. It also omits the proof of Lemma 6, which moves straight to "Conclusion," and it cites Lemma 14 for the existence of the good m without showing it. That existence step carries the most weight, so it is asserted here, not shown. "Autonomously" describes the proof search, and the excerpt names a human operator, so the autonomy claim is the authors' and the excerpt does not test it. At the strength the excerpt allows, it supports that a formally checked proof is described and that the writeup gives an informal route to it. It does not show that readers outside the authors have followed the argument, or what the system itself grasped.
Inquiring lines that read this note 19
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
Can we trust AI-generated mathematical proofs without understanding them?- Why did AI-generated proofs go unread by mathematicians?
- Did automated checking loops actually solve Erdős problems correctly?
- Can disclosure alone ensure independent verification of AI-assisted mathematical work?
- Why do some Erdős problem solutions fail to resolve the originally intended claims?
- What evidence exists about whether AI-written proofs reduce mathematician learning?
- How does Kummer's theorem connect base-p digit carries to binomial coefficient divisibility?
- Can opaque AI tools suggest valid mathematics without external validation?
- How does search difficulty differ from construction difficulty in mathematics?
- Does verification by inspection scale for AI mathematics discoveries?
- What pattern does this follow from OpenAI's earlier Erdős problem claim?
- Why did OpenAI's Erdős primality claim collapse under independent verification?
- Can pure mathematics provide an objective test that experimental science cannot?
- What should mathematicians prioritize when machines can solve problems faster?
- Can mathematical literature remain alive if no human experts understand it?
- Does automation always move the goalposts of what counts as real mathematics?
- What would it mean for mathematics to define itself before AI transformation?
- Why do theorem provers crowd out other AI-for-mathematics approaches and tools?
Related concepts in this collection 2
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Can AI systems improve themselves through trial and error?
Explores whether replacing formal proof requirements with empirical benchmark testing enables AI systems to successfully modify and improve their own code iteratively, and what mechanisms prevent compounding failures.
contrasts: the Darwin Gödel Machine validates empirically, where this result's validator is a formal proof
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Can deterministic checks protect LLM judges from failure?
Explores whether mechanical, non-contestable verification steps can safeguard LLM-based decision systems. Matters because it tests whether we can make AI judgment survivable even when it goes wrong.
extends: a Lean-checked proof is the unarguable check the pattern ranks first, here in mathematics
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- Resolution of Erdős Problem #728: a writeup of Aristotle's Lean proof
- Remarks on the disproof of the unit distance conjecture
- Verification abundance, adjudication scarcity: what happens to mathematical knowledge when proof checking becomes free
- From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier
- The crisis of AI-generated mathematics
- Machine-Assisted Proof
- Why the Legendary Erdős Problems Are Falling to AI
- Mathematical exploration and discovery at scale
Original note title
the writeup says an AI system resolved Erdős Problem #728 autonomously and its Lean proof is translated into informal mathematics