Original subtitles

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 are amazing AI developers, but 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 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.

I'm a gold professional player.

I'm also a European champion.

I was born

in

China.

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

This is why I go to French.

I want to try to forget the goal.

But it's impossible.

Because all the things I learned in my life is with this goal.

It looks like a mirror.

I see the goal.

I also see myself.

For me, goal 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 see the female, I don't know if it's true or not.

Well, I will accept about this. Why not?

For me, everything is an adventure.

I want to go to visit Dima to know what is this Go project.

The first visit, I think maybe I want me to sit in the special room.

push many many where in my hand also my body let me play to scan my

spring i don't know to make some research we needed to get fanway

to deep mind to see we were a serious operation and we were serious people um

doing proper research and the search time is getting better and better like

as we go from for example one to eight in any one of these it always go 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 what AlphaGo thinks,

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

We've been working on AlphaGo.

in 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've thought, wow, this

is just too hard.

Everything we've 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 Hoi, 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, just the program is 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'll 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. 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 play with AlphaGo.

Ajia Huang push the stone for AlphaGo.

And, of course, I think I will win the game with AlphaGo because it's just a

program.

The first game, I make some mistake and I lose the 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 also I lose the second game and also for third game.

The first game, even the last game.

I lose 5-0.

AlphaGo win all the game.

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 myself.

I worried whether he'd even come back. You know, he seemed very low, and he

spent about an hour away from the office, and he came back completely

changed.

with the program she tell me yes we know but for you is i do i okay

i told her not and yes i

i'm not happy to lose a game but and we will be happy for play in the history

Artificial intelligence researchers have solved the game of Go a decade earlier

than expected.

The computer named AlphaGo was able to beat the European human champion.

Artificial intelligence researchers have made a significant breakthrough.

It really is a big leap forward. There's a big difference between the way the IBM

computer beats Kasparov.

which was programmed by expert chess players, and the way the Go playing

computer more or less learned itself.

The way we start off training AlphaGo is by showing it 100,000 games that strong

amateurs have played that we've downloaded from the internet.

And we first initially get AlphaGo to mimic the human player.

And then through self-play and reinforcement learning, it plays against

different versions of itself many millions of times and learns from its

errors. These specific ideas that are driving AlphaGo are going to drive our

future. The technology's at the heart of AlphaGo. They're what are called deep

neural networks, which essentially mimic the web of neurons in the human brain.

It's a very old idea, but recently, due to increases in computing power...

These neural networks have become extremely powerful, almost overnight.

Big neural networks that operate on big data can achieve surprising things.

AlphaGo found a way to learn how to play Go.

Learning is the key thing here. It's machine learning.

The whole beauty of these types of algorithms is that because they're

learning for themselves, they can go beyond what we as the programmers know

how to do and allow us to make new breakthroughs in areas of science and

medicine. So AlphaGo is one significant step towards that ultimate goal.

My wife called me.

She told me, don't see Internet, don't connect Internet, because people talk

terrible things about you, much with AlphaGo.

Fan Hui is living so long time in Europe, he's not real professional, he's

just amateur player.

This is so hard for me, so hard.

The Go world were skeptical about how strong really was AlphaGo and how much

further did it need to get to be the top professionals.

So our program is improving over time, and we want to push the AI algorithm to

the limit and see how far this kind of self-improving process can go.

So we needed to look for an even greater challenge.

A match like no other is about to get underway in South Korea. Lee Seedol, the

long reigning global champion. This guy is a genius. Will take on artificial

intelligence program AlphaGo and the ultimate human versus machine smackdown.

This is a huge moment for both the world of artificial intelligence and I think

the world of Go.

So far, AlphaGo has beaten every challenge we've given it.

but we won't know its true strength until we play somebody who is at the top

of the world, like Lee Sedol.

We chose Lee Sedol because we wanted a legendary, historic player, somebody who

has been acknowledged as the greatest player of the last decade.

I will not be too arrogant, but I don't think that it will be a very close

match. The level of the player that Africa went against in October is not

the same level as me. So given that a couple of months was only passed, I

don't think that it is enough for it to be able to catch up with me.

My hope is that it will be either 5-0 for me or maybe 4-1. So the critical

point for me is to make sure I do not lose one.

We don't know how well our system will play against someone

as creative as Lee Sedol. Also, he's very famous for very creative fighting

play. So this could be difficult for us, but we'll see. Maybe in some ways he's

the most difficult opponent we can pick.

There was still so much of a question about whether or not they could beat

someone like Lee Sedol.

Fan Wei is a good player, but he's nothing like the very top players.

Lee Sedol is a nine-down professional.

Nine-down professional is the highest rank that you can achieve and go.

The ranking system.

Fan Wei, who is the European champion, is just a two-down professional.

On the other hand, the very top Lee Sedol is nine-down professional.

Lee Sedol is to go what Roger Federer is to tennis.

He's playing in Wimbledon to win the Grand Slam. And it's not just this year.

He'll be there next year, and the year after that, and the year after that. Of

course, in Internet and all the Go community, everyone, maybe

not 100%, maybe 99.999% think Lee Sedol will win very

easily.

Go is taken seriously in Korea. It's so much part of the culture, like breathing

or, you know, like taking swimming lessons or something.

On the surface, it's a game, but inside had a very deep philosophy.

Go board reflects the individual who's playing.

The true gonna show itself on the board.

You won't be able to hide it.

In ancient China, Japan, Korea, Go is one of the four noble

things, like four accomplishments for literati with music, poetry,

and painting.

So people think the Go players...

are very smart and very noble.

Master Kwon started this school so that he could produce great players in Korea.

Lee Se-dol, when he was age of eight, he came in here attending class 9 a.m. till

9 p.m., seven days, and then he stayed with Master Kwon.

Ise Dol was a little boy that I remember when I was a student studying Go. He was

very young and rural enough to think that pizza grew on trees.

Lee Sedol plays things that are interesting where you felt like he's

beyond winning and losing he wants to do something that's innovative or takes

things to the next level so every gold player started his game for sure roughly

10 years he dominates the professional gold world he win 18 world championships

Definitely Lizardo is going to win the game.

5-0.

Yeah, all game.

He's going to win all game.

We had our evaluation match last week.

We won a game and we lost a game. And we lost a game in a way that would have

made us look extremely foolish if that happened publicly.

It means that we still have work to do and we need to take this really

seriously. It's just too much risk that...

actually we could we could lose um overall not only that but we could lose

in a way that makes us look rather silly so i guess um yeah did you want to say

anything about what you're trying we're working

around the clock at the moment training our algorithms further trying to

incrementally keep on improving right up to the moment where we have the match

we've collected together people with different skill sets onto the same team

so we have researchers, engineers,

evaluation guys.

So you mean what happens if it creates something new which wasn't in the

beginning? Yeah.

Then we don't see it.

We don't see it.

Okay. The first thing to know is just to fix it. Oh, well, things can help. A

perfect solution. So it's not the... Azure is the lead programmer and built

the original search engine.

So Azure's responsibility is quite a big one. He will be the one sitting opposite

Lee Sedol and actually playing the moves AlphaGo makes.

I'm feeling excited.

At least I know he's a great player and I feel honored to play with him.

Many of my friends, they are very excited about the match. They keep

telling me that the whole world is watching.

Just prepare AlphaGo.

Hello. Hello, Dennis. Can you hear us? Yes, I can hear you guys. Can you hear

me okay?

Yes, perfect.

I was curious to meet you. Such an amazing developer who made iPhone.

He used to be a professional chess player.

and then I stopped playing when I was about 14.

When I was 13, I was the second highest rated player in the world.

After the match, I would like to propose that I give you one teaching game of Go

and you give me one teaching game of chess.

How does that sound?

That sounds very good. I would be very honored to do that. I'm not sure if it's

okay to ask you this question.

I saw the games against Fan Hui and I didn't think it was quite at the level

to play with me, but I heard that it's getting really stronger.

Can I ask how much it got stronger since then?

I can't say too much, of course, but it's definitely got significantly

stronger.

With more time, I think.

A logical approach would be to follow up on Azure's local search and run that in

FastELF to generate a whole new data set and iterate for more time.

But we're just out of time for that, so we have to be realistic.

We realized that if we wanted to prepare for a mammoth task like taking on Lisa

Dole, there would be nothing better than talking to a professional.

And we couldn't have picked a better person than Fan Wei.

We invited him as an advisor because during the match, we found he is a man

of good spirit.

Welcome back. Thank you very much. It's very precious that we have Fan Hui with

us.

He was crushed by AlphaGo, but then he became very positive and a big help to

us.

When they tell me, can you come back to help us make AlphaGo more stronger, I

feel this respect.

Of course I accept about this.

I play with AlphaGo to understand where is the strong point about AlphaGo and

where is maybe the weakness.

I play in the morning, afternoon, all the time.

And I find something.

I find big weakness about AlphaGo.

The big one.

The superheroes always have a hidden vulnerability, right?

And the same is true of AlphaGo.

It's unbelievably superhuman in general, but it has some particular weaknesses in

some situations.

We can think of there being this space of all the things it knows about, and it

knows about most of it extremely well. But then there'll be these tricky lumps

of knowledge that it just understands very poorly.

And it's really hard for us to characterize when it's going to enter

into one of these lumps.

But if it does, it can be completely delusional, thinking that it's alive on

one part of the board when in fact it's dead or vice versa.

So there is a real risk that we could lose the match.

Everybody in the team tried to work more and more to fix the problem, but I think

it's difficult to fix this very quickly.

We've got version 18 in the pipeline, haven't we?

Well, we'll only go for version 18 if it makes a significant improvement, which

we're having to rerun all the tests.

They went wrong, unfortunately. We're sort of a day behind in our evaluation

because of that. Well, maybe we just need to be realistic that we've tried a

bunch of things and we've come to the point where we said we would actually

start freezing the code and saying, look, it's actually not

panning out.

These delusions are still a realistic possibility for the match.

We have some weaknesses that I don't think we're going to fix fully before

the match, so that's causing us a little bit of anxiety.

Lee Sedol is getting ready to rumble. On Wednesday, live across the internet,

this professional South Korean Go player will take on artificial intelligence

program AlphaGo.

Tomorrow, Julian and George, they pack up version 18, they stick it on a

laptop, and they fly out to Seoul.

See you all in Korea.

is everything is all set for the victory against he says no everything is set i

think but i will when i get to the hotel i'm going to catch up with the team what

we should do in the time remaining is list things that could go wrong in the

solidity of the system we need somewhere to put um i have to go under here all

right rehearsal let's go please folks have you arranged the baseball please

have to stop

When I

got here,

I didn't expect the attention on the match. It was literally front-page news

about... 8 million Koreans play the game of Go. And even those who don't

recognize Lee Sedol, he's a national figure.

And so there's that, right? There's some national pride involved, but it's more

than that.

Just the very thought of a machine playing a human at something like this,

I think is inherently intriguing to people.

All the world gave the pressure to Lee Sedol.

Before this, he played the tournament for country, for himself.

But this time, I played for the human.

I just really hope we win this first game.

If you lose the first game, you literally have to win three out of four.

Which is hard work.

Where are you going to be?

I'll start in the match room, and then I'm going to come in here and make sure

everything's... Yeah, you should probably be in there.

I know you're nervous.

Yeah, I'm nervous.

I'm nervous.

How are you? You're not nervous?

A bit. A little bit, yeah?

It's good to have a little bit of nerves.

Be fine. Be fine.

Hello and welcome to the DeepMind Challenge Game 1 Round 1, live from the

Four Seasons here in Seoul, Korea.

I'm Chris Garlock of the American Go E-Journal. I'm here with Michael Redman,

Nine Dawn professional.

Welcome, Michael. I want to give a shout out to all the folks watching around the

world. Well, the excitement is pretty palpable here in the hotel.

I've never seen a crush of interest of reporters from around the world. The

media is overwhelming.

If we were to call it Alpago, we would have enjoyed Hwacheom.

I wonder if it would have changed in five months.

All right, folks. You're here. You're going to see history made. Stay with us.

Five minutes, guys.

Five minutes.

I just thought we should take a moment together and just think about what's

about to happen.

Extremely excited to be there, extremely proud of every one of you and what we've

done. And win or loss, I think it's just amazing that we're here.

Isn't it weird?

I don't want the machine to beat the person in the game.

This country applies the rule of China and has a limit of 7 days.

The time limit is 60 seconds and 3 days for each 2 hours.

Thank you for watching.

Please subscribe and like.

We had worked so hard to make sure that this would go technically smoothly.

We tested it and tested it and tested it.

And still, there comes that moment when you're live, all the TV cameras are

broadcasting everything, and now it has to do the thing you built it to do.

Oh, but I'm really thinking about the second number.

I was a bit nervous. It's the first time that I sit in front of a world-class co

-player.

And I actually can feel the spirit and courtesy of a great co-player, at least

I know.

Because I think it is the first time he faced a strange opponent.

I think he's not a human, has no emotion, it's cold, but he stayed very

calm. And I can feel his mental strength.

I'm Andrew Jackson. With me here is Myung Won Kim, nine-time pro from the

Korean Baduk Association.

We are here live at the Four Seasons Hotel on the 21st floor. What are we

looking at? How's the game going?

Oh, it's fighting from the beginning. From the very beginning?

Yeah, yeah.

AlphaGo plays very well. Yeah?

Just like a top professional.

Just like a top professional.

Yeah, it's very aggressive.

Now the fight is getting really

complicated. This is actually the first time I've seen AlphaGo playing...

a game that has this difficult a fight.

I just

saw him

looking at his opponent's face, and that's just a kind of a habit.

It's just an instinct as a player to look at the person across the court.

Yeah, it's sort of like something that Lee Se-lo would do when he was wondering

how his opponent was feeling.

It's just a habit.

So it's not as if Ah Ja-hwang is going to do any giveaway, because Ah Ja-hwang

isn't AlphaGo, right?

He came and went, and now he's smiling.

I think it was a mistake.

No, it's ridiculous.

He came here and went. What are you doing now?

Two people lost today.

I was going to turn here, but my hand went in without thinking.

Because you have a lot of strength.

It's hard now.

I was a little embarrassed.

This is what we're most afraid of.

Yes. Is it shaking?

It's shaking.

I can feel many, many things.

But, out of a goal, you can feel nothing.

So, when you can feel nothing when you play, you have more than one question

about yourself.

At the beginning, you think, OK, my move is good.

And, really good?

Really good?

Oh, maybe bad. Oh, terrible.

Why do I play here?

More than more.

It's hard to know where to be. All the different rooms are exciting in a

different way.

Quite nice to be here at the heart of the operation.

Yeah, I feel safe here.

White's thinking of doing this huge invasion here from its thick wall.

Yes, go for it.

He's done it.

He's gone in.

Look at his face, look at his face.

That is not a confident face.

He's pretty horrified by that.

a little bit behind and she made a very aggressive move here okay and make it

very complicating okay i think if he doesn't you know respond correctly then

he can collapse i mean this one is kind of unthinkable as a human

role player what if she knows everything about what's going to happen next

50 or 60 moves ahead.

That's the maximum number of moves ahead that AlphaGo is looking from the current

game position.

It's typically over 50, it's often over 60.

In the games we've seen, often around move 150, AlphaGo goes for the kill.

We're at move 115 now, so we're getting to that critical point.

We are all astonished.

just in the middle of the game, because AlphaGo seems to be doing a much better

job than we all thought it would.

I thought this adult would be leading the game comfortably, but it turned out

that he's struggling at the moment.

But I think eventually he will prevail, I hope.

I was, you know, more 5-0, but now I'm not sure about that.

There might be the first mistake, kind of clear mistake that

White made.

It looks

like

you've got a count.

Yeah, right.

What do you think?

White won a lot at this time. If it's like this, White has won by a lot.

Wow,

it's so shocking.

I expected AlphaGo to win only one game.

I can feel his pain.

He couldn't believe, you know, he couldn't accept it. It takes time for

him to accept the outcome.

Maybe AlphaGo is very strong now, but he don't want to believe he will lose.

It's just the goal posture player. We can't believe this because...

For us, it's something very, very far.

It's not can be coming now. It's impossible.

But in reality, it's now.

I think he resigned in a very polite way.

Lizardo, he's black, but he put a white stone.

I think he resigned.

Oh, my gosh.

I feel

really

good. I feel like I really believe in AlphaGo.

Of course, it's natural that humans want humans to win. I mean, I think that's a

natural response.

But AlphaGo is human-created, and I think that's the ultimate sign of human

ingenuity and cleverness.

Everything that AlphaGo does, it does because a human has either created the

data that it learns from, created the learning algorithm that learns from that

data, created the search algorithm. All of these things have come from humans.

So, really, this is a human endeavor.

In the battle between man versus machine, a computer just came out the

victor. DeepMind put its computer program to the test against one of the

brightest minds in the world and won.

AlphaGo beat a professional player who has 18 Go World Championships under his

belt. The victor is considered a breakthrough in artificial intelligence.

First of all, I think the failure in the beginning continued until the end.

Of course, I didn't know I'd lose in the beginning. I didn't know I'd be able to

receive it so perfectly.

I was really surprised.

I've won several world championships.

And the actual experience itself is very different.

I don't think I'm shaking too much because I lost one game.

To be exact, I think it's 5 to 5 now.

In research, we normally work to produce an academic paper. It gets published,

and maybe we get to talk about it in a conference if we're lucky.

This is not normal for research. In fact, I've never experienced any...

media attention remotely close to this so it's a special moment for us all and

we're just enjoying it while it lasts

in a matchup between man

and machine who wins well so far it's the machine in seoul south korea the

artificially intelligent computer defeated the global champion in the

ancient chinese board game go lee sidol lost the first matchup but He's got four

more chances.

It

is

a bit strange being the front cover and everything as a computer scientist.

Normally you sit there in your corner, you code, nobody really knows about it.

Perhaps heard the joke, how can you tell that a computer scientist is an

extrovert? and not an introvert.

If he's an extrovert, he looks at your shoes when he's talking to you instead

of at his own.

Like, if you look at Aja, he avoids all the cameras like crazy.

He's like, the game is finished, and he's like out the back and back in his

room.

And I think a lot of computer scientists would be like that.

We are more about doing our work than standing in the spotlight.

Hello and welcome to Game 2, Round 2 in the Google DeepMind Challenge

throwdown between man and machine.

Game 1, the machine takes down man.

Huge shock.

Headlines around the world.

The reactions on the ground here from the folks in Korea were just stunned.

They estimate 60 million people watched the game in China alone.

It's probably bringing up to maybe 80 million people watch this game

worldwide. It was just incredible.

And if anything, today is probably even more of a madhouse.

So Isidore knows today. He knows that this is just a really important game,

right? He's got to win.

Isidore on white. I think probably looking for a little payback.

My impression is that maybe he underestimated AlphaGo and he's going to

change his tactics.

Yeah, but Lee Sedol is playing much, much slower today, which is going to

affect us.

He's playing at half his speed, actually.

You can't let your guard down.

I don't think I can handle this.

network which was trained on high-level games to imitate those players and then

we have a second component we call this the value net and it can evaluate the

board position and say what is the probability of winning in this

particular position and the third component is the tree search where it

would look through different variations of the game and try to figure out what

will happen in the future

So if we now take a position like this, first the policy network would scan the

position and come up with what would be the interesting spots to play.

And it builds up a tree of variations and then employs this value net that

tells it how promising is the outcome of this particular variation.

So AlphaGo tries to maximize its probability of winning.

But it doesn't care at all about the margin by which it wins.

Okay, so when you see a slow-looking move, that's maybe an indication that

AlphaGo thinks it has a good chance to win.

Yeah, that is a little giveaway.

A little tell. We're looking for a tell.

Ooh, looks like Lee is taking a little bit of a break.

Ahjap sees AlphaGo play the move 37, and Ahjap puts the stone in the board.

That's a very

surprising move.

I thought it was a mistake.

When I see this move, for me, it's just a big shock. What?

normally human we never play this one because it's bad it's just bad we don't

know why it's bad but it's a little bit high yeah it's fifth line normally you

don't make a shoulder here on the fifth line um so coming on top of a fourth

line stone is really unusual yeah that's an exciting move i i think we've seen an

original move here that's the kind of move uh that you that you play go for

Hey.

Interesting stuff.

This fifth line shoulder hit. I wasn't expecting that.

I don't really know if it's a good or bad move at this point.

The professional commentators almost unanimously said that not a single human

player would have chosen move 37.

So I actually had to poke around in AlphaGo to see what AlphaGo thought.

AlphaGo actually agreed with that assessment.

AlphaGo said there was a 1 in 10,000 probability that Move 37 would have been

played by a human player. So it knew that this was an extremely unlikely

move. It went beyond its human guide, and it came up with something new and

creative and different.

I am very much...

watching the game through these commentators.

That's the way it works. So when they're confused, I'm certainly confused.

At the same time, I'm latching on to the fact that they are confused, right? That

is an interesting moment.

When everyone else is confused, who's not confused, right? Besides the

machine.

He's back. Lee is back.

Normally, he'd think about one, two minutes, no more. But this time, he

think more than 12 minutes.

The more I see this move, I feel something changed.

Maybe for humans we think it's bad, but for AlphaGo, why not?

Go is like geopolitics, like something small that happens here that have a

ripple effect, you know, hours down the road in a different part of the board.

The game kind of turned on its axis at that moment.

This move is very special because with this move...

All the stone play before is work together.

It's connect.

It's not like a network, link everywhere.

It's very special, very special.

This is a tough game for Lee Sedol.

AlphaGo is just not letting Lee Sedol do what he wants. Right.

That's not a good sign.

Lee Sedol just slapped himself on the side of the head.

Oh, wow.

I think black's ahead at this point.

It's looking good, isn't it? We're on that steady path now.

I just see Lee Sedol, he lose so much.

Normally, we resent before long time ago, but he won't try.

He play, he play, he play. He just don't want to resent.

Because then White, oh, he resigned.

It looks like Lee Sedol has just resigned.

There was this heavy sadness over that whole floor.

You could feel it during the game. I felt it during the game.

And I'm leaving the commentary room to go to the press conference. And I was

stopped by someone, another technology reporter.

At first, all he wanted to talk about was the technology and how great this

was. But then even he kind of slipped into this moment of melancholy where he

was upset as well.

I am quite speechless.

I admit that it was a very clear loss on my part. From the very beginning of the

game, that was not a moment in time that I felt that I was leading the game.

You feel elated and you feel a little bit scared.

There is something, I think, frightening to people about a machine that learns on

its own.

For us, AlphaGo is obviously just some computer program.

but looking at the commentary on the internet,

I already saw the commentators call AlphaGo like he and she during the

games, completely unconsciously, which AlphaGo is really a very, very simple

program. It's not anywhere close to full AI, and we already see that happening,

so I found that very interesting.

The tendency to anthropomorphize AI systems is...

one of the big obstacles in the way of actually trying to understand how AI

might impact the world in the future. For example, the conversation is about

what could go wrong, like what the risks are. Then invariably you see this

Terminator picture. Every single time there are these red glowing eyes, right?

We're really closer to a smart washing machine than Terminator.

If you look at today's AI,

We are really very nascent. I'm extremely excited and passionate about

AI's potential, but AI is still very limited in its power.

I think that people are right to think that there is a danger that as we

continue to improve these systems that we might miss that threshold where we do

cross over into danger.

But the good news is that there are already people thinking about those

dangers. You know, there's a lot of talk now, and we're leading the discussions

on this, that maybe there should be a kind of cross-industry best practices

working group or something, where the leaders of the research teams in those

organizations, you know, the big ones that are working on AI, IBM, Microsoft,

so on, come together and make sure that AI is used ethically and responsibly.

I think what is important is that there is this community of people who are

leading.

the cutting edge of ai who are interacting with academics and already

are thinking about the the long term and how we can ensure that innovation is

responsible as the power of these machines gets even greater this is it

folks day three game three lease it all go master back to the

wall he's down to zero he's got to win today to keep hope alive

I heard that four pros went to visit him to console him and to review

Africa's... Console him? You think he's upset?

I mean, Isidore's upset.

Yeah.

In the beginning, there was a fierce fight, and then Avalgo played very well.

So he secured a very early lead.

From move 50, the win rate was very high already, and it was climbing toward

100%. Oh, that's great.

He tried to fight directly in the game.

but it's not have stealth.

When we change our stealth to play with opponent, normally it's very very bad.

So it's again more easy for AlphaGo.

I don't know how to describe the situation.

If I were Black, I would resign.

We should admit that we are facing the strongest existence ever, ever in the Go

history.

There's no point in playing out the endgame and you're gonna lose, right?

Even if Black can live here... Oh, he resigned.

Wow.

Wow.

You saw history made here tonight.

AlphaGo has won again, three straight wins. Three straight wins, has won the

match.

When Lister is in the game, he looks like unhappy.

It's not just he loses the tournament.

It's just especially about this game, because he doesn't play his game.

I'm very hurt about this, very.

But I can do nothing.

You know, certainly I feel a bit ambivalent about it, given I'm a games

player and, you know, Go is the pinnacle of board games.

But I really like the statement one of the top Chinese professionals said of,

you know, if AlphaGo wins, maybe we'll really start to get to see what this

game's about.

I couldn't celebrate.

It was fantastic that we'd won, but there was such a big part of me that saw

this man trying so hard.

and being so disappointed.

I see internet, many, many people are talking about Lisa Dahl, maybe I don't

play the best.

You know, we are Go players.

OK, sometimes in China, in Korea, in Japan, we see Go, we're like, ah, we are

artists, you know. We play our best for Go. So, please gentle with Lizard.

He's very, very good player, great player.

I am in the room, I see Lizard, he won't win.

He try everything.

We just, we can't. Just this.

So...

First of all, I'd like to say I'm sorry.

I'm

sorry

to show you such a helpless appearance.

I'm sorry to show you such a powerful appearance.

I'm sorry to show you such a powerful appearance.

I don't think I've ever felt that way.

So I think my ability to overcome that was a bit lacking.

This was an unbelievable situation.

No matter what the opponent is like, it's not 3-0, it's 5-0.

Oh, I lost 5-0.

This is really a huge scratch on my pride. And

people... I'm so sorry to those who

cheered

for me.

You can see that he was more relaxed after he had lost three games in a row.

That said, the stakes were still high.

You know, in the end, it isn't about pride.

Hey, don't feel like confidence.

But they feel light.

Can Lee Sedol find AlphaGo's weakness?

Is there, in fact, a weakness?

I was thinking I'd just pull the plug.

You'd just pull the plug. Everyone's still cheering for Lee Sedol.

And then, yeah, it's not going very well.

It feels pretty good for Black at this point. It feels pretty good for Black,

yes. I want Alistair to play his game.

Because for the moment, he tried many, many things to play with AlphaGo, to

understand AlphaGo, but he never tried to play himself.

I thought many, many times AlphaGo looked like the real mirror.

When you play with AlphaGo, you feel very strange.

Look like you're all the time naked.

The first time you see this, you want to see, because, oh, it's me, real me?

And more than more, you need to accept, oh, it's real me.

So how, now, how I can do?

It's developing into a very, very dangerous fight.

This is really Lee Sedol's type of game. He likes this kind of fight.

White has to find something inside Black's territory. I think he is already

planning on trying something.

So you believe in Isidore's ability to live in the very small area, right? Yes,

yes. There is a little potential there, and I think maybe he's going to try to

do something.

Isidore, magic.

What would be the magic move?

Isidore, he's running short on time, but he's going to have to use up all his

time. Yeah, he just burned like seven or eight minutes.

Just on this move already.

I don't see anything.

We can't find anything.

What is Lisa doll up to here? Yeah, he's really concentrating.

He really is. Look at that.

Lisa is very patient. He wait, he wait, he wait this moment.

I feel something look like the wolf.

Wait in the forest in the winter.

He called.

He feel very, very cold.

But I need patience.

But the moment coming, he go out to attack.

This is the end of the game.

Oh, look at that move. That's an exciting move.

Oh, he found the wedge.

Whoa. It's going to change the equation because now black cannot escape.

That would be so cool if that works.

AlphaGo has just played something maybe unusual.

You know, I'm not actually sure what AlphaGo is trying to do here. What's

that about?

I don't really understand it. Well, well. That was a sharp drop in win rate.

That's the sharpest drop in win rate we've seen.

Drop 8%. Wow.

This could be that it actually can't find a way through.

I think this is, it's looked far enough ahead to see that it doesn't work and

now maybe it's on tilt. I don't know.

There it comes.

It looks like it's fallen off the cliff.

Yeah, it's made a mistake.

Did anything strange happen in there?

No, it all looks normal.

Well, there you go. We can definitely say, well, there's weakness.

We can definitely say it's a mistake.

Five fail.

this mixture of this sinking feeling in my stomach, where I was wondering if

AlphaGo was becoming delusional in this situation, where I could see that it was

starting to play strangely, and at the same time, relief for Lucidal, that he

was actually in with a chance now.

I just like trying not to look horrified.

I knew after move 17, after like 10 or 20 moves, I saw AlphaGo strange

moves, and...

I know AlphaGo somehow became crazy, but I didn't realise why.

We searched from 1995 ahead at that point?

I think something went wrong. That's the longest we've searched the entire game.

I think it's like we've searched so deeply, it's not hard.

I do get the impression that AlphaGo has sort of gone off on a tangent.

What is it doing there?

Or maybe it has a master plan.

No, it doesn't even think it has, does it?

So it knows it's made a mistake because it starts evaluating it the other way.

Look, look, look, Lisa's confused.

I was like, what is it doing? That's not a, I'm scared confused. That's a, what

is it doing?

Why is it going on?

You know, you asked if it was a bug.

I've said before that if DeepMind has figured out how to write code that

doesn't have bugs, that is a bigger news story than AlphaGo.

Oh, you're kidding me.

Literally, this next movie we're going to play, I think they're going to laugh.

Everybody's going to laugh.

I don't really know what AlphaGo is trying to do here.

That's the understatement of the app.

Is it mouse misclick? Nope. Nope. That's the move. Aja Hong makes no misclick.

Isidore is very confused.

These are not human moves.

This move also sort of inexplicable.

I mean, those you can clearly call those.

Mistakes. Yes, of course. This is the first time in the four matches that

we've seen moves like that. Oh, the value dropped even more.

That's weird.

We're like 45%. White.

White. I think white is winning.

Come on, Lee Sedol!

All right!

I was so confident that this black moya would just be consolidated by black and

that there was nothing there, and somehow he's just erased it all, like

it's gone.

So he's found his weakness.

That wedge move probably surprised him. Yeah, that wedge. Yeah.

AlphaGo seemed to have such a good game, and then this whole sequence in the

center sort of changed that.

He pulls off a miracle.

He managed to make it so complicated that the artificial intelligence

doesn't... evaluate it correctly i think it looks like ajaf wong maybe sitting

there also knows that the game is over i can't i can't you know stop smiling did

he smile no i haven't seen him smile yet i think he is still checking yes he's so

serious he wants to be careful he cuts off a lot he really does his

best i think he feels some something like you know uh this possibility

Looks like AlphaGo is resigned.

The most amazing game.

I'm almost going to tear up, was game four, where he comes back and wins,

right?

I heard from so many people saying they were running out in the street They were

so happy. You know, they were chanting, they were celebrating.

Especially after a 0-3 down, at the time, it seems to be hopeless that the

end of the world is coming, but we see the light.

Usually, I'm happy when I win, not like my colleague wins.

But this time, it felt like my win.

I didn't think about putting it in this kind of place.

I have to do it quickly.

I really didn't expect it to be this good.

I couldn't believe it.

I couldn't believe it.

Thank you.

I think this is the first time I've been congratulated after winning one game.

I can't be this happy after winning three games and one win.

This one win is...

My question is about number 78 move.

Chinese top goal player Gu Li said it was a god's play.

What were you thinking when you made that play? Thank you.

It does leave me a little bit in awe of the human brain's power, in particular

Li's amazing ability to cause AlphaGo problems and find something seemingly

out of nothing.

And so we really want to understand what had happened.

So it really was Lee's move. The key is the center. If the center goes out, then

it's no chance.

We were winning before this.

If AlphaGo thought it was winning, and it couldn't convert that win, that means

it wasn't actually winning. Otherwise, it would have had the right responses.

Would we have played it?

What probability does it give it as white?

0.007%. Is that in the position that he played?

That's when he played it. I see. So we thought this was the one.

The value is really low.

So the god move was literally a god move because we believed that only one in 10

,000 humans would have found that move. That's right. It doesn't come to mind as

the top five, in the top five moves that you would consider. Unless you're Lisa

Dole. He said it was the only one.

And he thought it was the only one, yeah. Hey, Michael, what was that?

Welcome back to the Four Seasons. World champion Lee Sedol went looking for

AlphaGo's weakness in Game 4, and he found it today.

Last round, he's looking to see if he can repeat that. We'll see what happens.

The place is a madhouse downstairs.

Maybe as many, if not more, journalists here today than there were for Game 1.

We all were really excited for the fifth match to see what would happen. Was this

going to be a 3-2 thing or was it going to be a 4-1 thing?

And, you know, there's a different message with both of those.

For me, I don't think AlphaGo will make the mistake again.

But who knows?

Maybe it will come.

And Lisseter has now more confidence about this.

Looks like maybe Lisseter will find the key to open AlphaGo.

You weren't crazy about the timing on this move.

Oh, yeah. And now you don't approve of this.

Yeah, I'm sort of thinking that maybe AlphaGo hasn't recovered from game four

yet.

Still deleted?

Oh, no, I hope he doesn't play right now. No, he needs to play though.

Him play some move is bad move. I feel something. Oh, maybe his weakness come

back again I think it could be a kind

of a misreading

There's

no reason for white to be playing that move It's a bad move, and in some cases

it's going to lose a point too.

Well, 91% certain now.

Yeah, because it's incorrect again.

The whole game we thought that AlphaGo was wrong about the board position. We

were super worried that, oh, it's going to play garbage, it's going to lose in a

very embarrassing way. And this continues for the whole game.

But this is a bit weird.

When did they play that? Just now.

So I don't know. I mean, it doesn't... Well, that we don't know, but we're not

good enough Go players to know that, right? Yeah.

As it turned out, none of us know Go well enough to accurately judge what

AlphaGo is doing.

But why is he winning now?

This one looks like White is winning.

We all say some of AlphaGo moves are so weird and strange and maybe mistakes.

But after a game is finished, we have to doubt ourselves, our judgment.

AlphaGo making another kind of nonsensical throw-in.

We're not really sure what that's about. This is what 10 or maybe 11.play looks

like. It looks weird, and we don't quite understand it. I think it is important

to study more about Alpago's mistake-like moves.

Then maybe we can adjust our knowledge about Go.

To me, the most amazing thing to come out of my understanding of Go as a

result of watching AlphaGo play.

are the infamous slack moves.

Well, there's something strange about the way it's playing because it's

playing some moves that are not really necessary.

Right. A slack move is a move that looks lazy.

You can see these other better moves, and AlphaGo is rejecting them. But what

I think AlphaGo is teaching us is that... We've been using score as a

proxy for chance of winning. So the bigger my margin of territory, the more

confident I am that I'm going to win. And AlphaGo is saying, no, no, no. It

shouldn't matter how much you win by. You only need to win by a single point.

Why should I be seizing all this extra territory when I don't need it? The

lessons that AlphaGo is teaching us are going to influence how Go is played for

the next thousand years.

By my counting, I won this game.

By how much? Are we talking two points? One and a half. One and a half points.

One and a half.

Maybe half. One and a half. Of course, Go is just a game, but we can learn

important lessons from our computer being so successful at Go.

Machines will have the capability not only to crunch through a huge amount of

data, but also to analyze it intelligently.

Just as in the case of the Go games, the machine made moves that surprised even

the experts.

And eventually the machines will gain our confidence because we will see that

very, very often they make a better guess than we could have made as humans.

Unfortunately for...

Lee said, oh, I think white might have a slight advantage here.

Winning, okay. No, they're not one. That's what she said. Winning.

I have to

go say it's going to resign.

I'm not only joking.

Jesus, that was a heart attack.

That was very good.

Red plate.

Red plate. No, not really.

I couldn't do it in too long. I just couldn't make that. Waiting two years to

do that.

Waiting two years to do that.

We don't know the score. We have no idea what's going on.

Two and a half. Two and a half.

It was very hard to... It was very hard to...

Yes, he touched the rock.

I think I'm going to give up.

That's it.

I mean, I think it just really is a once-in-a-lifetime thing.

I would say it's the most amazing thing I've experienced.

For us, it's the culmination of a 20-year dream.

It started as a pure research endeavour. We just wanted to understand, can neural

networks play the game of Go?

And from there, it went on to a level that I never expected.

And I'm unbelievably proud of the team.

When I started doing artificial intelligence, it was four or five years

ago, and I was really interested in that, but, like, many people would

discourage me, and they would say, OK, there is no future. So actually seeing

that within five years we are at this stage right now, it's amazing by itself.

Everybody say... There are so many possible

application domains where creativity...

in a different dimension to what humans could do could be immensely valuable to

us and i just love to have more of those moments where we look back and say yeah

that was just like move 37 something beautiful occurred there at least in a

broad sense move 37 begat move 78 begat a new attitude at least a new way

of seeing the game he improved through this machine

His humanness was expanded after playing this inanimate creation.

And the hope is that that machine, and in particular the technologies behind

it, can have the same effect with all of us.

I remember hearing a talk by Kasparov, who says that a good human plus a

machine is the best combination.

This is a unique experience.

Nobody can have this experience.

play with AlphaGo 5 games like this.

So, I hope Lysidor can find something in this 5 game, maybe some

change in his game.

I see today he fight, fight, fight.

It's very good.

Big master.

Real big master.

Is this even done?

But for all the...

story maybe it's just a big game we don't know

it's just when i play with alphago he showed me

something i feel beautiful just it i see the world different before

everything began what is real thing inside the goal game

with this thing i will change something with my game

Maybe he just can show humans something we never discovered.

Maybe it's beautiful.