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Today I'm here with Eric Jang, who was most recently vice president of AI at One X Technologies. Before that, senior research scientist at what is now Google DeepMind Robotics. And you've been on sabbatical for the last few months. One of the things you've been doing is rebuilding and improving and hacking on AlphaGo. And so we're today what we're gonna do is you're gonna explain building AlphaGo from scratch and what it tells us about the future of AI research and development. But before we get to that, why is AlphaGo interesting? Why is this why is this the project you decided to do on sabba
Sure. Yeah. I like making things. And AlphaGo and Go AI is one of those things that really got me into the field when I saw the kind of early breakthroughs breakthroughs on on AlphaGo off off ago in 2014, 2015, 2016, and so forth, it was just profound to see, you know, how smart AI systems could become and the the kind of computational complexity class that they could tackle with deep learning. This is a problem that has long been understood to be kind of intractable for search, and yet it was solved through deep learning. And so that was quite mysterious to me, and I've always wanted to under
By the way, if you're listening to this on an audio platform, this is a Blackboard lecture, so I highly recommend switching over to a video platform like YouTube if you can to look at the math and the graphs and the Go board. Okay. I guess we should first discuss how Go works.
Great.
So, yeah, how how does the game work?
So the game of Go is a very simple one that can be implemented quickly and easily in a computer. The the objective of the game is basically to put down black and white stones and try to occupy as much territory in the game as possible. So I might start by putting down a black stone. Black always goes first. Just go ahead. And so the way you capture an opponent's stones is that for every intersection, if you can surround all four of its neighbors with with your stones, then then this one is sort of cut off from oxygen, if you will, and then it and it it it is a dead dead stone. So so then now I
Alright. I'm, like, basically playing randomly here, but I'm trying to get around your stones and see if
I can
Sounds good. Them. Yep.
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