Hi everyone, welcome to the A6 and Z podcast. I'm Sonal and I'm here today bringing back the band together again, the AlphaGo band, I guess.

I don't know how else to describe us, but we have the head of our deal in research team operation, Frank Chen.

We have Steven Sinovsky, A6 and Z board partner.

Just to give people some quick context, you don't have to have heard our previous podcast on AlphaGo. But when AlphaGo, the algorithm produced by Deep Mind, beat the world

champ in Korea in playing Go, which is an ancient Chinese game, we had a podcast where we discussed

a lot of the themes and some of the broad things around that. And what we'd like to talk about today is

their latest paper, but not just only specifically,

but more broadly, what this means for where we actually are what's hype, what's real in

AI or artificial intelligence. So welcome, guys. Welcome. So, like, one thing that, like, you

read this paper, and the paper is published in nature. It's pretty dense. It has 17 authors

on it. And so it's quite the force. But the

thing that sort of jumps out is the paper, the blogs, everybody is the first thing you read

is one step closer to creating general purpose AI. And immediately, like my AI winter fears

of hype antenna pop up because like everything is one step closer,

but like you could take very, very, very tiny little steps or you could overhype them.

And we've heard these promises throughout history and especially around board games.

So we solved checkers and people were like, oh, one step away from general

intelligence. Then we solved chess. Same thing. We're one step away from general intelligence.

Then we did the, oh, I can find bacteria that causes infection. Therefore, we must be one step away.

And I think the fallacy is that because we're doing these things that are considered sort of high

cognition, like there's smart people play chess, smart people

figure it out, then solving one thing that a smart person does must lead us to the next

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