> I've been wondering whether AI really is improving rapidly at open problems or we're being fooled.

I think your suspicions are warranted and your explanation seems plausible.

If better training data is the reason here, it would still be a case of the models doing something that is in and of itself super useful! The models really can take that data and distill it into solutions for similar problems faster than humans can. This is great!

But there's so much vested interest in the AI companies to be opaque about all this, to hype up their models and avoid giving credit to people whose data made everything possible, that they would never tell us this fact if it were true.

I feel like so much of the AI hype cycle is like this. The models develop extremely useful capabilities, but it's hard to understand what they really are through the hype. The lies and obfuscation by their owners who have vested interests in capturing the value they provide makes it impossible to take anything they say at face value.

>> If better training data is the reason here, it would still be a case of the models doing something that is in and of itself super useful! The models really can take that data and distill it into solutions for similar problems faster than humans can. This is great!

It's perhaps great in the short term although it's not very clear who it's great for. I'm not sure mathematicians find it all so great, I mean.

In the long term, if this contrives to destroy the tradition of human mathematics the whole endeavour is self-defeating. In time, there will be nobody left with the knowledge and skills to produce mathematics to train AI to do mathematics.

And then we'll be left with no mathematics at all: we'll have no human mathematicians and no AI that can do mathematics, either.