AI is discovering patterns in pure mathematics that have never been seen before

Current-gen Deep Leaning systems are really good at “riffing on” text inputs. So feed them a bunch of known math conjectures, and new conjectures should fall out.

Not that this is a new thing — mathematicians have been using various procedural generation methods to formulate conjectures since Prolog was invented. But the Deep Learning text AIs make this much easier — you don’t need to model the domain, the syntax of a mathematical conjecture; these AIs discover that much for you. So you can more quickly and cheaply apply these modern methods to exploring conjecture-space in new subdisciplines.

And of course, this still has nothing to do with what futurists were expecting ML to eventually do for math (generating proofs, putting mathematicians out of a job); instead, something a lot less obvious as “useful work”, but useful nevertheless!

Could you expand on this? What code did you see, where, and doing what? Were you part of this team?

> There's nothing particularly new about mathematicians using computers to investigate and make conjectures, even if you add ML into it.

I think you're being needlessly reductive here. The article itself explicitly states that "using computers" is not what's new.