But what are the practical implications of that? Isn't it just as likely that those math problems haven't been solved because there was not any particularly good reason to solve them?
With the exception of the Jacobian conjecture, none of these have any practical applications. But it is mistake to think that these problems were not solved previously due there not being any "good reason" to solve them. All of these were well known problems where major mathematicians had worked on them. Erdos 1196 was a problem which saw a lot of work by Jared Lichtman who is one of the leading young number theorists now. The other problems are even more so. Both the unit distance problem and the double cycle cover conjecture were problems that had many mathematicians work on, and the Jacobian conjecture is a problem where many people have had partial results about it and where people have spent years solving special cases.
The rest of your post isn't on the topic in question, but is about broader issues with AI, which may be valid, and may be worth discussing. There's no question that there are some pretty serious negatives. To use one personally annoying example, my spouse works in a library and she has to deal with trying to explain to patrons that just because ChatGPT said a book exists doesn't mean the book is real. But the point of my comment remains focusing on the claim that these systems are " aren't creative they're just really really fancy search engines that regurgitate what they have ingested." That's not accurate, and the results in math show that. And if we are going to understand these systems, both their positives and negatives, we need to understand their capabilities.