alt Hacker News> There are vast libraries full of mathematics no one (in this discussion, anyway) has ever heard of that no one reads anymore and has never been applied to anything.
And that's an issue why? It would seem to me that producing that also produced the mathematics that revolutionized the world repeatedly for centuries. I would go further and claim that, if you want the mathematics that revolutionizes the world, there's no way to get it without advancing mathematics as a field broadly. Those are not two separate activities, and thinking that they are is indeed a misconception.
> This idea of trying to "prove all the math" with AI makes as much sense to me as using chess engines to try to "solve chess."
You're right: "prove all the math" does not make sense on any level, and nobody serious would phrase any of this in that way. I certainly didn't.
And that's an issue why?
The issue is SNR: signal to noise ratio. Generating exponentially more mathematics, particularly if the process is indiscriminate or optimized for something other than usefulness or mathematical relevance (such as optimizing for machine-provability), does not imply that we get exponentially more applications. We may end up halting the progress of applications altogether as the entire capacity of the world's mathematical apparatus is consumed by the interpretation and investigation of machine-generated proofs.
You can already visit arXiv and find vast numbers of not-yet-published mathematical papers. Most should never be published. None of this junk is benefitting humanity in the slightest.