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  • So...computers get really good at beating us at chess.

  • And then they get really good at beating us at a lot of things.

  • We're so used to getting beat by computers that when I play Greece in deity mode, I don't

  • cry any more when it stomps me.

  • 'Kay, when I play Greece in any mode, I don't cry when it stomps me.

  • But humanity, crafty devils that we are has long had one secret weapon...Go!

  • And it was just a matter of time before those computers came for that too.

  • Welcome to CompChomp...the only show on the internets where we can talk about atari without

  • having to mention any video game crashes.

  • From the beginning of AI work, GO was considered the impossible dream.

  • There were games like tic-tac-toe that could be completely solved with math.

  • And if you can solve it with math, computers are gonna dominate.

  • There were games like chess that were a bit harder, but with a little bit of tweaking

  • of the algorithms, you could also make computers dominate there too.

  • Hey...uhh...didn't I just talk about this?

  • Go is really different though.

  • You play it by taking stones and placing it on a 19 by 19 grid.

  • And the goal is to surround more territory than your opponent does.

  • There are more possible game combinations than there are atoms in the entire known universe.

  • Possibly the unknown universe too.

  • We haven't counted it.

  • And every single piece has the exact same value.

  • So that chess approach...it ain't gonna work.

  • As recently as 2015, experts in AI were predicting that it would be at least...oh...a decade

  • before any computers were able to beat top Go players.

  • Then, in January of 2016, the journal Nature came out with a little article talking about

  • the algorithms that the Google-backed AI had used to defeat the European champion.

  • And, BTWs, that exact same AI was going to be facing off against one of the top players

  • in the world, Lee Sedol, in March.

  • Mic drop.

  • So what had changed between those expert predictions of at least a decade and that article in Nature?

  • Advancements!

  • Advancements in Machine Learning.

  • Ahhhhhh...Machine Learning.

  • It's my favorite!

  • SInce Go has so many possible moves during any game, that uh whole more game combinations

  • than atoms in the universe thing, you can't have the computer go through every possible

  • move to determine which move is the best.

  • Instead, computers use an algorithm called the Monte Carlo Tree Search.

  • This is where they take a random sampling of possible moves, calculate out to see which

  • one of those is the best, and then select that move.

  • AlphaGo is no different than any of the other Go-playing computers on this front.

  • What sets AlphaGo apart is it uses Deep Learning to prune the unwanted combinations before

  • it does the Monte Carlo Tree Search.

  • What's Deep Learning?

  • So glad you asked!

  • Deep Learning is a kind of artificial neural network inspired by the fancy little brains

  • of mammals.

  • Brains have neuron and artificial neural networks have simple processors.

  • Those neurons in brains can be connected.

  • And so can those processors.

  • Brains have a way of getting input from the outside world.

  • Things like your eyes and your ears.

  • And artificial neural networks have that too.

  • There are processors that can take in data from the world around it.

  • Similar to how the brain passes messages from neuron to neuron in order to make decisions,

  • data gets passed through the layers of an artificial neural network with each layer

  • transforming it in different ways based on what it's "learned" in previous layers - until

  • decisions are made.

  • So AlphaGo's training started out with an initial data set of 30 million training moves.

  • It worked with this data until it could correctly identify the next human move 57% of the time.

  • So, just a little over half of the time, it could look at what a human was playing and

  • say, "I know what you're gonna do!".

  • Then, they matched it up with a slightly modified version of itself and it just played thousands

  • of game.

  • AlphaGo vs AlphaGo Prime!

  • Who will come out on top?!?

  • And, after that, the European champion played hundreds of games against it so it got used

  • to playing against humans too.

  • After alllllll of these games, AlphaGo was ready.

  • This face off was amazing.

  • Game 1 starts and AlphaGo and Lee Sedol trade moves.

  • Back and forth. Back and forth.

  • For over 3 hours!

  • They were mostly testing each other.

  • Trying to get a sense for how the other one played.

  • And at the end, even though he had led the entire game, Lee Sedol lost to AlphaGo.

  • Computers - 1.

  • Humans - 0.

  • The second game got off to a very similar start.

  • They were tentative.

  • Back and forth.

  • Back...and forth.

  • Then, on move 37, AlphaGo's piece gets plunked down....*pop*...on a random part of the board.

  • It's called a shoulder hit, and everyone there that knows anything about Go was just like,

  • Whaaaaaaaaaaaaaaaaa!

  • The people that built AlphaGo thought it made a mistake.

  • They looked at the control room data afterwards and this was not even one of the moves that

  • was in the 30 million training moves.

  • I mean, think of that.

  • 30 million moves by top players, and, not a single one of them was this move that AlphaGo

  • made.

  • Lee Sedol stared at the board.

  • And then he gets up.

  • And he walks out of the room.

  • And he's gone for 20 minutes.

  • So he comes back in.

  • And he sits down.

  • And he makes his move.

  • Move 38.

  • Move 39.

  • But you can tell he's shaken.

  • He just never brings it back.

  • And this game goes on for hours.

  • But then he resigns.

  • And now....it's AlphaGo - 2

  • Humans - 0.

  • But do not be afraid!

  • Don't worry.

  • Because this...this is THE moment that humanity rises up and we throw off the yoke of our

  • new computer overlords.

  • No....this isn't some Hollywood movie.

  • This is real life.

  • And this is a top AI system.

  • Humans lost.

  • We lost 4 of the 5 games.

  • So we're not completely defeated, but, Go is no longer a human-only realm.

  • AlphaGo had made his mark.

  • Or her mark.

  • Or its mark.

  • So with this loss, should we run for the hills and hide from our robot overlords?

  • No!

  • I mean, AlphaGo knows how to play Go.

  • Ask it to play chess and it'd probably do worse than my kid sister.

  • Well, I haven't got a kid sister.

  • Chomp!

So...computers get really good at beating us at chess.

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B1 alphago ai deep learning neural move chess

Deep Learning and AlphaGo - Computers Beating Humans #2

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    Caurora posted on 2017/01/27
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