Building an AI Mathematician with Carina Hong - #754

Math and coding are two important or perhaps the two biggest part of, digital world, and coding is heavily invested. Math is not not that math is not tractable, but that math has not been turned into programming language yet, and there will be new markets and new use cases that get unlocked because of this. Alright, everyone. Welcome to another episode of the Twinmo AI podcast. I am your host, Sam Charrington. Today, I'm joined by Karina Hong. Karina is founder and CEO at Acxiom. Before we get going, be sure to take a moment to hit that subscribe button wherever you're listening to today's show. Karina, welcome to the podcast. Thank you for having me. Great to be here. I'm excited to dig into our conversation. We'll be talking about mathematical reasoning, which is what you are working on there at Acxiom. And, it is a very timely topic. Before we dig in, I'd love to have you share a little bit about your background. I love math since as long as I can remember, when most people don't. And I feel like Olympiad math training gives you this sense of, like, constant dopamine hit. Like, you solve a problem, and then you feel so good about yourself, and then you move on to the next one. A bit later, I went to MIT and started research mathematics career, and that was a lot more pain and suffering. You usually are stuck on a problem for months. And I remember I was working on a really hard problem for about, like, half a year, and I would meet with my adviser every week and have nothing to report. That's kind of the life of a research mathematician. What particular field in mathematics? Yeah. So I work on numbers theory and combinatorics. Lot of people who work in combinatorics come from the Olympiad math background. So they can solve problems, yeah, a lot faster than than other combinatorics researcher. But number theory, hopefully, is is better. It's you can read a lot of literature and, make really interesting contributions without having this sort of outlier problem solving skill. Nice. I took a real analysis class in grad school, and I think that was about enough for me. I love graduate analysis. Yeah. I remember back then at the graduate analysis class, I don't know if it's because no one is quite following. We were just, like, passing note and saying that the professor looks like Winnie the Pooh. That must mean that the class was a lot easier for you than it was for me. Or maybe we're just completely lost. I don't know. Nice. So, so you're working on the this hard problem at MIT. It took you half a year. Yeah. And then I think I realized at one point that wouldn't it be great if you can just let your intuitions take you? You have some lemma that you want to prove instead of being stuck …