alt Hacker NewsThis is speculation right now. The idea would be that if someone used the product and granted training rights, which is the default for many subscription levels, then some knowledge would have been imparted into the general weights of the new model.
oAI has made clear they did not specifically pull in any user data to context for this run.
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Tristan Buckmaster, the mathematician at the center of it (https://cims.nyu.edu/~tristanb/) put out a public statement that everybody should read (pdf) - https://cims.nyu.edu/~tristanb/statement.pdf
So what might have been the incentive for OpenAI to do all this shenanigans? It might have to do with getting its models certified for AGI and getting out of lockin with Microsoft - https://deadneurons.substack.com/p/the-quiet-unwinding-of-mi...
Tristan Buckmaster’s post cited extensive use of LLMs in the process of his collaboration with Levent:
“We used several LLMs throughout: Anthropic’s Claude, OpenAI’s Codex, especially with GPT-5.6 Sol and, more recently, Astra.
The latter was only used for writeups and auditing our arguments. For most of the past year progress was slow. We worked through the literature and upgraded various preliminary results, up to obtaining finite time blow up for the Incompressible Porous Media equation (with smooth forcing).
This was until about a month ago, when we had real progress: on August 15th, we obtained the blow up results, with smooth forcing, for both Boussinesq and Euler. I can say the first LLM generated proof Levent sent me was the most horrendous I have ever read; we verified it on Lean on August 22nd. Since this point, we have been working around the clock to understand this proof and turn it into something readable.”
The OpenAI research post states they began training GPT-6 internally on August 28th, and that user chats are used to train models.
“We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models .”
For an incredibly niche topic like this, I believe it’s extremely likely that Buckmaster/Levant’s work would influence the direction of OpenAI’s agents’ work even as a de-identified drop in the overall bucket of training data.