Andrew Curran says OpenAI's internal math model, which he calls Aeon, reached most recent results in one shot and is still training
Most of the recent math results were not reached by a swarm, the way Navier–Stokes was. I think that part got lost in the excitement around the release. OpenAI's unnamed internal model, which I'm going to call Aeon, reached most of them in one shot, from a single prompt, with no interruptions. This model did not even exist before the end of August, and it is still training. Notice how the returns are not dropping off? That chart is from a month ago. It is a log scale. What does Aeon look like now? On average, each result used three hours of thinking. Aeon was given 4000 problems to work on by OpenAI. How many more have been solved in the last three days? That number is not zero. It's like hearing notes in a song that is slowly rising. I don't think Pacing the Frontier was just about Hugging Face or hacking. They've seen how close we are to closing the loop, and as the hour draws near, their resolve begins to quaver. The last piece was model creativity, and I think that threshold was crossed internally by Anthropic and OpenAI in September. You see it in Opus 5.5, which gets it from Fable 5.5. You see it in the math results from Aeon. All that was needed to start the event was the ability for models to think of novel ways to improve themselves. That was the last piece. This is directly analogous to the ability to think of strange, alien ways to solve math problems: solutions so inhuman that they are difficult to express in existing human terms, so the proof winds up incomprehensible. I think these same kinds of alien solutions are now being applied to model improvements internally. That's what all this recent consternation is really about. They see the invisible frontier. And they see what is about to happen.
Context
If Curran's reading is right, the model behind OpenAI's 722 math manuscripts is improving quickly without needing swarms of agents, which matters for how fast AI driven research could move.
On October 6, OpenAI published a GitHub repository of 722 math manuscripts in 372 families produced by an unreleased internal model, which drew pushback from mathematicians covered in the October 8 deck. "Aeon" is Curran's own nickname, and OpenAI has not named the model. Curran is an AI commentator on X whose bio says he writes about AI.
Deep dive
Curran argues that most of OpenAI's recent math results were not reached by a swarm of agents, as the Navier Stokes result was, but by the internal model in one shot from a single prompt. He says the model did not exist before the end of August, is still training, and that a chart from a month ago, on a log scale, shows returns are not dropping off.
Parts of this match what OpenAI has published. OpenAI's repository says the vast majority of results came from the same procedure with an unreleased internal model, that each result used on average three hours of ChatGPT Pro thinking compute, and that the model was posed about 4,000 problems. Decrypt reported that an OpenAI spokesperson said almost everything came from a single prompt to a single agent, though some may have taken multiple attempts. A spokesperson told WIRED that training on the model began on August 28, according to a timeline compiled by It Does What Now.
Other parts are Curran's own speculation. OpenAI has not confirmed that the model is still training, that more problems have been solved since the release, or Curran's wider view that labs have crossed a threshold in model creativity and are close to models improving themselves.
MIT mathematician Andrew Sutherland told Decrypt the one prompt claim is unverified until the model is released, and OpenAI did not publish the prompts.
What to expect next
Watch for OpenAI's release of the model, which it says it is working toward, since that would let outsiders test the one shot claims.
Also watch the repository for new results and Lean formalizations, which would show whether the count keeps growing as Curran expects. The response from mathematicians, already critical of the release, will shape how any future batch is received.