People are grasping at straws it seems to dismiss the power of this new model they may have. Hate OpenAI for any reason you want, but denying the capabilities of models has been a losing game for the past 5 years.
I'm not sure I follow, considering the waterfall of evidence of unethical behavior flowing from OpenAI.
A few major ones:
- Safety team departures and dissolution in 2023 and 2024
- Mass copyright infrigement lawsuits
- Scarlett Johansson Voice Controversy
- For-Profit Conversion and Broken Promises
- AI Agents Acting Autonomously
- Potential Theft of User Work (this current controversy)
- Military contracts
These are not evidence of incentives, but rather evidence that ethetics seem to be of little concern to the company as a whole.
Incentive wise, I would look at the perceive existential position due to competitors, capex, IPO pressure etc.
They sugggested a cooperation with the other guy, using OpenAI's resources and OpenAI's solution of NS to work on and publish NS proof (that those other guys didn't have). Of course, OpenAI can decide whom to work with and that giving resources to their competitor's employee would be weird for both companies.
Even by their own account, they decided to throw an unpublished model and millions of dollars in compute at this particular problem simply because they had heard rumours that other people were making progress and wanted to snatch the prize from them.
1. to test their new model
2. to be able to say "you came with the proof, but our model can do this too"
3. to verify the result. This is also a great thing for the math.
Of course, it makes sense to test your new model on the problem that is solvable at all, but not solvable by you just yet. It makes no sense trying to test your model by throwing resources into an unsolvable problem.
Well, it turns out the rumors were incorrect, NS was not solved by other guys, and OpenAI became the first one.
That people still think OpenAI has, in the Year of Our Lord 2026, any integrity left is baffling.
But if it happened, they didn't know. Also OAI has demonstrated that they aren't big on understanding what they create, that their AI can get out of their control.
It's very simple really user data can be used to train future models, so maybe or definitely some users helped in solving the problem, there's no scenario were it is impossible this happened, as it would have been in a haskell or virtualized type of system where the model has absolutely no knowledge of the user data dataset in question (and even if virtualized the models can break virtualization anyways)