2026-03-25
16 分钟For Scientific American Science Quickly, I'm Kendra Pierre-Lewis, in for Rachel Feltman.
In 1997, Deep Blue, a supercomputer built by IBM, did the unexpected.
It defeated chess giant Garry Kasparov at his own game,
leading to a flurry of headlines about whether Deep Blue was truly intelligent
and if computers could now outthink humans.
The answer, at least then, was mostly no.
But it 's now 2026, and we have a growing number of generative AI models that are once again making us wonder,
can machines outthink us?
To dig into this question, a group of researchers aren't turning to chess this time.
They're looking to math.
To learn more about that, I talked to Joe Howlett, a staff reporter here at SIAM, covering math.
Thanks for joining us today, Joe.
Thank you for having me.
So you wrote a piece that's talking about the challenges of AI and math.
Before we kind of get into the meat and potatoes of that piece, I have maybe a more basic question for you.
For those of us who maybe peaked with high school algebra when you 're talking about AI and math problems,
what are the kind of math problems we 're really talking about?
That 's actually a lot of what this story is about,
is that the kind of questions that mathematicians ask and spend their time
thinking about kind of do n't really sound like or have anything in common with the problems