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Story that I'm a son of a mathematician.

When I was a child, I was considered gifted in mathematics, and my parents decided at an early age that I was gonna be a mathematician.

My parents actually had a plan for all three of the boys.

My oldest brother was gonna be a pianist.

He did it.

I was the youngest, was gonna be a mathematician.

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Exactly one year ago, I was a happy-go-lucky university professor writing my papers.

I would have described myself as someone who had enjoyed the privilege of being good at mathematics, and then there was a dramatic change.

Now I'm deeply troubled.

For the first time, I struggled to assemble questions that ChatGPT would get wrong.

These models know more facts than any human you would ever find.

I was devastated.

... um, and other like physical engineering disciplines that we couldn't think of in the past.

So put another way, wr- the world runs on code that people don't understand, many people haven't even read.

So software verification, hardware verification, as Karina says, is kind of the challenge for the future, and that's really like doing math.

Okay.

Um, you know, honestly, the, the percentage of math that has been understood by mankind at, out of all the math that probably exists, it's probably close to, like, 1% or 2%.

Math is...

We're just always discovering things.

But you can prove theorems that nobody cares about or will have no application to the real world, and what's the good in that?

I mean, yeah, you tell me.

Yeah, there's a few thing... there's a few things we have to get right.

So first of all, large language models, ChatGPT, Claude, uh, they're not perfect.

They hallucinate.

And so last year when we're talking about, uh, these large m- la- large language models getting a perfect score, well, make no mistake, someone still has to grade those problems.

But in twenty twenty-six, we've come a long way.

There's a second kind of AI called formalization and verification where the computer checks itself.

Right.