Hi, everyone, welcome to the A6 and Z podcast. Today's episode is on machine learning, deep learning, and AI, the role of university research and making AI production ready for industry and games. The conversation moderated by A6NZ operating partner Frank Chen took place at our recent A6NZ summit event. And it features Cameron Schuller, former entrepreneur operator and executive

director of the Alberta Innovate Center for Machine Learning, now known as the Alberta Machine

Intelligence Institute. It's based out of the University of Alberta, Canada's Department of

Computer Science. And longtime listeners of the podcast will also recall we did a podcast roadshow in the

UK with researchers there as well.

The Institute does R&D in all things machine intelligence. In 2007, they solved checkers,

which is a longstanding challenge for AI researchers. And in 2015, they produced a first AI agent

capable of playing an essentially perfect game of heads-up limit Hold'em poker.

As you look at some of the big successes that the Institute has had in machine learning,

a lot of them sort of cluster around playing games.

So you guys solve checkers before chess.

You have a pretty good solution for poker.

You were the first ones to reinforcement learning on playing Atari games, right?

Which Google later popularized.

Yes.

And, you know, obviously Google has gotten a lot of tension recently with the AlphaGo win, and then StarCraft will be the next big battleground.

I can't wait to see the human versus Google AI on StarCraft.

So maybe take us back and talk to us about why do AI researchers gravitate to doing research on games and is it just a toy?

That's a good question. We do like to have fun, just to be clear, and we're in a university.

So I did a couple of comments actually. So when DeepMind got bought, half the people there were

actually Canadian trained and roughly 20 or 25 percent were our students. So they did take things like Atari. They took that with them. AlphaGo, I think it was roughly 45% of the research cited on their AlphaGo paper came from the University of Alberta. So a very strong connection. And Rich Sutton, who's the father of reinforcement learning, he literally wrote the textbook. He can get the second version off

his website even today. He was one of the supervisors of David Silver. So back to your real

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