AlphaGo

It's intensely contemplative.

It is almost hypnotic.

It's like putting your hand on the third rail of the universe.

If you play Go seriously,

there is a chance that you will get exposed

to this experience that...

is kind of like nothing else on the planet.

Go is putting you in a place

where you're always at the very farthest reaches

of your capacity.

There's a reason that people have been playing Go

for thousands and thousands of years, right?

It's not just that they want to understand Go.

They want to understand what understanding is.

And maybe that is truly what it means to be human.

When I was a kid, I loved playing games.

I started off with board games like chess.

And then I bought my first computer when I was eight

with winnings from a chess tournament.

Ever since then, I felt that computers

were this sort of magical device that could extend the power of your mind.

Virtual environments and games,

we think they're the perfect platform for developing and testing AI algorithms.

Games are very convenient, in that a lot of them have scores,

so it's very easy to measure incremental progress.

So I'm going to show you a few videos of the agent system, the AI.

So let's start off with Breakout.

So here you control the bat and ball,

and you're trying to break through this rainbow-colored wall.

The agent system has to learn everything for itself,

just from the raw pixels.

It doesn't know what it's controlling.

It doesn't even know what the object of the game is.

Now, at the beginning, after 100 games, you can see the agent is not very good.

It's missing the ball most of the time.

But it's starting to get the hang of the idea

that the bat should go towards the ball.

Now, after 300 games,

it's about as good as any human can play this,

and pretty much gets the ball back every time.

We thought, "Well, that's pretty cool."

But we left the system playing for another 200 games,

and it did this amazing thing.

It found the optimal strategy

was to dig a tunnel around the side.

And put the ball around the back of the wall.

The researchers working on this, the amazing AI developers,

well, they're not so good at Breakout, and they didn't know about that strategy.

So, they learned something from their own system,

which is, uh, you know, pretty funny and quite instructive,

I think, about the potential for general AI.

So, for us, what's the next step now?

Go is the most complex game, pretty much, ever devised by man.

Beating a professional player at Go

is a long-standing, grand challenge of AI research.

Wow.

You really want to kill me, yeah?

No, I don't want to, but I'm trying to survive.

Yes, that's it. That's it.

I am a Go professional player.

I am also a European Champion.

With that move,

you're going to lose for sure.

You were happy to defeat me but then you panicked.

You're afraid that victory will escape you.

In general, when you're afraid, victory always escapes you.

I was born in China.

When I was 18, I wanted to change my life.

That was why I went to France.

I wanted to try to forget Go.

But it was impossible.

Because all the things I learned in my life was through Go.

It looks like a mirror.

When I see Go, I also see myself.

For me, Go is real life.

Dear Mr. Fan.

My name is Demis Hassabis.

I run an artificial intelligence company based in London called DeepMind.

As the strongest Go player in Europe,

we would like to invite you to our offices in London,

both to meet you in person and to share with you

an exciting Go project that we are working on.

If you would be interested in coming to visit us,

please let us know.

Many thanks. Kind regards, Demis.

When I saw this e-mail,

I didn't know if it was true or not.

I will accept this. Why not?

For me, everything is an adventure.

I want to go visit DeepMind

to know what this Go project is.

On my first visit, I thought maybe they wanted me

to sit in a special room,

attach numerous wires to my head,

and also my body,

let me play to scan my brain.

I don't know,

to make some research.

We needed to get Fan Hui to DeepMind

to see we were a serious operation, and we were serious people...

doing proper research.

And the search time is getting better and better

as we go from, for example, one to eight, in any one of these,

it always goes up.

We think of DeepMind as...

kind of like an Apollo program effort for AI.

Our mission is to fundamentally understand intelligence,

and recreate it artificially.

And then, once we've done that,

we feel that we can use that technology to help society

solve all sorts of other problems.

If you step through the actual game,

we can see, kind of, how AlphaGo thinks,

what's the most likely variation that it thinks will happen.

We've been working on AlphaGo,

our program to play Go, for just under two years now.

All the little patterns cascade together,

layer after layer, after layer, after layer.

I started talking about the game of Go with Demis more than 20 years ago.

And so, this has been a really long journey.

The game of Go is the holy grail of artificial intelligence.

For many years, people have looked at this game

and they have thought, "Wow, this is just too hard."

Everything we have ever tried in AI,

it just falls over when you try the game of Go.

And so that's why it feels like a real litmus test of progress.

If we can crack Go, we know we've done something special.

So with Fan Hui, we started talking around

what the real purpose of the visit was.

It wasn't just a Go project we wanted him to help with,

that actually we wanted to play him, and we had a very strong program.

It's okay, it's just a program.

It's so easy.

So, it will be easy to play.

A lot of people have thought that it was decades away.

Some people thought it would be never.

Because they felt that to succeed at Go, you needed human intuition.

Go is the world's oldest continuously played board game.

And, in some sense,

it is one of the simplest and also most abstract.

There's only one type of piece.

There's only one type of move.

You just place that piece on the board.

And then, your goal is to create a linked group of your stones

that surrounds some empty territory.

And when you surround enemy stones,

you capture them, and remove them from the board.

You earn points by surrounding territory.

And, at the end of the game, the person with the most territory wins.

It seems really simple.

But, then you sit down to play, and you realize right away,

it's like, "Well, I technically know what I'm allowed to do,

but I have no clue what I should do."

Go is incredibly challenging for computers to tackle

because compared to, say, chess,

the number of possible moves in a position is much larger.

In chess, it's about 20.

In Go, it's about 200.

And the number of possible configurations of the board

is more than the number of atoms in the universe.

So even if you took all the computers in the world,

and ran them for a million years,

that wouldn't be enough compute power to calculate all the possible variations.

If you ask a great Go player why they played a particular move,

sometimes, they will just tell you it felt right.

So, we have to come up with some kind of clever algorithm

to mimic what people do with their intuition.

- Nice to meet you. - Oh, hello. Nice to meet you, too.

So with Fan Hui, we agreed a best-of-five match.

And we agreed it would be filmed.

You know, we would treat it as a serious match.

I played with AlphaGo.

Aja Huang pushed the stones for AlphaGo.

And, of course, I thought I will win the game with AlphaGo

because it's just a program.

Good game.

Have a nice game.

The first game, I made some mistakes,

and I lost the game.

Oh. Strange. Very strange game.

In that first match, I think something clicked for him

that this wasn't an ordinary Go program.

We weren't just doing the same as everyone else,

that something new was happening.

The second game, I tried to change my style.

But the problem is I also lost the second game.

And also the third game,

the fourth game,

even the last game.

I lost, five-zero.

AlphaGo won all the games.

After losing, losing, losing,

you can feel his pressure is getting heavier and heavier.

And several times after the game,

he said he wanted to go out for fresh air.

I said, "Oh, I can go with you and have a chat."

He said, "No, I want to go by myself."

I felt something very strange.

I lost to a program.

And I didn't understand myself anymore.