No, what is happening is that the AI is really good at connecting the dots and human mathematicians aren't.

OpenAI is explicitly not taking credit, btw.

They didn't take full credit for Navier-Stokes; unless I'm mistaken, they're letting the researchers who almost solved it have first authorship on the "official" paper, which the researchers are writing to have a human-readable breakdown of the AI's proof, and OpenAI has announced.

If anyone was close to solving the Exponential Time problem, they could come out and claim so, and they would be taken seriously; and if they have any evidence in ChatGPT logs, I expect OpenAI would announce an official explanation paper with their name on it. Credit is cheap: ChatGPT does get some credit because it did make the final leap, that doesn't mean researchers don't.

I don't really see how this is significantly different from them scraping the entire human knowledge, distilling it into weights and then selling the results.

Sure, this argument is about the _new_ data that researchers feed into the machine voluntarily, but I don't see this distinction as significant.

Not making a moral judgement here, just stating that this is consistent with the way those companies operate in general.

If this is not enabled by default then it need to be the default policy within EU by the enforcement of GPDR, for example.

I don't know if I agree with that. That presumes that the entire point of mathematics is to produce results. I don't believe that at all.

I believe that the entire point of mathematics is to produce human understanding and mental models that are useful or beautiful to humans. (I also believe there's a mysteriously deep connection between those two notions, but that's a different discussion.)

At any rate, I think that the old process, where humans had to cut the paths themselves before the clearing emerged, is one that led to understanding first, then a distilled result. And then the secondary task of distilling the understanding down to a clean proof is the icing on the cake. Some mathematicians are very good at keeping the intuition and understanding clear when presenting proofs. Some are not.

However, very often, the end result and proof is not where the real understanding lies, and that is one of the reasons why mathematics has been such a social endeavor. Often you can't glean the "hidden truths" behind austere proofs before you engage with people who can help you see the picture behind it. Many people who went through Baby Rudin as an undergrad can maybe relate to what I'm saying here. For a very insightful analysis about how intuition and discourse lead the discovery of mathematical truth, I highly recommend Imre Lakatos' amazing book "Proofs and Refutations."

What the models are producing is not what we had before. They are producing the cargo cult equivalent: Equations and words on paper which by means of tracing through the steps might take you from A to B. And after a while, humans might discover the true facts behind why that path from A to B exists, and then understanding emerges. And only then.

But when the process is done through AI, no one (no human) learns how to make discoveries and connections on their own. We are not letting people exercise the cognitive apparatus which is used to gain intuition and understanding. My fear is that after a while, fewer human mathematicians are able to gain the understanding mathematicians before them did.

It's as if someone removed all the barbells from a gym and made automated hydraulic jacks do all the lifting. After a while, people would wonder why our power lifters aren't as strong anymore. "But weights get lifted! That's the entire point, right?!"

Keep screwing over scientists, please OpenAI, eventually it will wake up the lazy institutions in Europe (and other places).

If they just stand by and let it happen, they deserve to be made fools of.

Academics are paid tiny sums at post doc and professor levels. Oai comes along paying millions to these people and giving them the tools and support to actually solve problems.

I guess not quite in how you're framing it, because you take issue with the tool stealing intelligent from the user of the tool.

But how do we confirm these advances depended on data leakage?

The people who feel fear about AI taking their jobs or doing worse things are not coping. They're saying all this is real and impressive and that that is why they are terrified.

The people saying it's bad and lies and they stole the answer and a million other things are just in tribal mode throwing whatever at the wall to defer to the pre-existing conclusion that AI is a corporate hoax. AI would have to be real to fear it in this professional and existential way, but they know it's fake, so they're not afraid.

It's sometimes done with more subtlety, like "it just comes up with some proofs by connecting existing things, it is not producing new insights, it's not creative or truly generating ideas". Which may be partly true. The denialism is shifted into refusing to acknowledge that within 20, or 2, years it probably will be producing new insights.