How AI Is Upending the World of Mathematics

Joe Weisenthal (0:00)

Hey, Odd Lots listeners, the Odd Lots tour continues and our next stop is in Chicago.

Tracy Alloway (0:04)

That's right, Joe and I will be at the City Winery Chicago on October 15th for a live Odd Lots recording. Tickets are on sale now at bloomberg.com/oddlots.

Joe Weisenthal (0:14)

And of course, a special thank you to Barclays for supporting Odd Lots Live.

Tracy Alloway (0:19)

So that's October 15th at City Winery in Chicago. Get your tickets now.

Joe Weisenthal (0:26)

Bloomberg Audio Studios, podcasts, radio, news. Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.

Tracy Alloway (0:47)

And I'm Tracy Alloway.

Joe Weisenthal (0:48)

So Tracy, with AI, obviously, one of the big concerns is job loss. What are we gonna, in the future, what are humans gonna be better at than the missionaries?

Tracy Alloway (0:59)

What are we gonna do all day?

Joe Weisenthal (1:00)

What are we gonna do all day, et cetera? We really don't know the answer, I think, to any of these questions yet. But I am aware, obviously, the models are getting very good at math, and at least some mathematicians perceive, they're in a state of existential angst about this. And certainly, crisis, perhaps, some feel about like, well, what are we doing here? These problems that I devoted my life to solving, and the model solves it in a weekend, you know? Like, is this what's potentially coming for many of us?

Tracy Alloway (1:32)

Yeah, math is an interesting one, because you can tell that a lot of the AI companies themselves have an interest in math, right? They see math as a sort of holy grail for, I guess, proving that the models are able to reason.

It's the thing they need to do and able to say that they've achieved AGI, I think, is the way it's couch. And it also makes good headlines. So even though I have no idea what the Navier-Stokes problem actually is, I don't know even if I'm pronouncing that correctly. Is it Navier or Navier? Okay, Navier-Stokes. I see the headline and I'm like, ooh, a model has solved the Navier-Stokes problem as if I know what that actually means and the significance for the mathematics profession.

Joe Weisenthal (2:13)

It's also funny because I downloaded the paper and it's like one paragraph and I have no idea.

I can't even begin to parse the output. Another fascinating aspect of this is just like, it would not have been intuitive to me, say two years ago or three years ago, that a language model would be so good at mathematics. In fact, at one point, they weren't very good at math at all. Go back to like, I don't know, GPT-3 or GPT-35.

Tracy Alloway (2:43)

Oh, yeah, if you ask them to count the number of letters in a word or something, they would get it wrong.

Joe Weisenthal (2:49)

Yeah, and weirdly, they still struggle with certain things like that. But it's not obvious to me, okay, you scan all of the text on text, language, et cetera, and yet somehow that generalizes into this extraordinary math capability.

That too is very surprising.

Tracy Alloway (3:10)

In this conversation, can I just say before we start, I would also just like to learn what advanced mathematics actually is because everything I know about it, which is nothing, comes from watching Goodwill Hunting and just seeing a bunch of formulas on a chalkboard and people get really excited when they start crossing off certain parentheses and stuff like that.

I have no idea what it is. I have no idea how it differs from pure maths of like two plus two equals four. And so I would just like to come away in this conversation with a better understanding of what it is overall and how AI actually fits into it.

Joe Weisenthal (3:44)

Absolutely. So like, I was thinking along the same lines, like, okay, for like someone who like devotes their life to like advanced theoretical math, and you know, other also like things like advanced theoretical physics that don't necessarily have like obvious like industrial applications, etc.

Who is the type of person? What are they hoping to achieve? Why is there still interest in some of these things that perhaps the sort of applicability is not necessarily so obvious. But then like, obviously, you know, like what is the role of the mathematician at this point? And then actually, specifically, it's like, okay, across universe, this is actually the thing I'm very curious about, which is my son studies math, right? Or both my kids study math and like-

Tracy Alloway (4:33)

Hopefully not theoretical math just yet.