(dramatic music)
- 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 wanna understand Go.
They wanna 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 in 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.
I'm gonna show you a videos of the A-Jen system, the AI.
Let's start off with Break Out.
So here you control the bat and ball and you're trying
to break through this rainbow-colored wall.
The A-Jen system has to learn everything for itself,
just from the raw pixels,
doesn't know what it's controlling,
doesn't even know what the object of the game is.
Now, the beginning, after a hundred games,
you can see the A-Jen 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 Break Out
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 longstanding, grand challenge of AI research.
(bells tolling)
- Wow.
- 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're working on.
If you would be interested in coming to visit us,
please let us know.
Many thanks, kind regards, Demis.
- 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
and 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 search through the actual game
we can see kind of how an algorithm thinks.
What's the most likely variation that it thinks will happen.
- [Demis] We've been working on AlphaGo and 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 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 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.
- 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's 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. - Oh, hello.
Nice meet you too.
- [Demis] 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.
- 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.
- 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.
He came back completely changed.
- 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.
- [Reporter] 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
beat Kasparov, which was programed 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
a 100,000 games that strong amateurs have played
that we downloaded from the internet.
And we first, initially, get AlphaGo to mimic
the human player and then, through self-playing
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 gonna drive our future.
The technologies 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 how 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.
- The Go world were skeptical about how strong
really was AlphaGo and how much further did it need
to get to beat the top professionals.
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.
- [Reporter] A match like no other is about
to get underway in South Korea.
- [Reporter] Lee Sedol, the long-reigning global champ.
- [Reporter] This guy is a genius.
- [Reporter] He will take on artificial intelligence program
AlphaGo, in the ultimate human versus machine smack down.
- 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.
- [Translator] 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 AlphaGo 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 five-zero for me
or maybe four to one.
So the critical point for me
is to make sure I do not lose one.
(speaking in foreign language)
- 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 could pick.
- There was still so much of a question about whether or not
they could beat someone like Lee Sedol.
Fan Hui is a good player but he's nothing
like the very top players.
- Lee Sedol is a nine dan professional.
Nine dan professional is the highest rank
you can achieve in Go, the ranking system.
Fan Hui, who's the European champion,
is just a two dan professional.
On the other hand, at the very top, Lee Sedol
is nine dan 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.
(children chattering)
- 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.
- In ancient China, Japan, Korea,
Go is one of the four noble things for accomplishment
for literati with music, poetry and painting.
So people think the Go players
are very smart and very noble.
- Mr Kwon started this school so that he could
produce great player in Korea.
Lee Sedol, when he was age of eight, he came in here
attending class nine a.m until nine p.m. seven days.
And then he stay with Mr Kwon.
- Lee Sedol 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 Go player study his game, for sure.
Roughly, 10 years, he dominates the professional Go world.
He win 18 World Championships.
- Definitely, Lee Sedol is gonna win the game, five all.
Yeah, all game.
He's gonna 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 lose overall.
Not only that, but we could lose in a way
that makes us look rather silly.
So I guess...
Yeah, Aja, did you want to say anything
about what you're trying?
- Um, I'm working hard.
(group laughing)
- [Demis] So 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 skills sets onto the same team.
So we have researchers, engineers, valuation guys.
- [Man] We don't see it.
- Okay.
- [David] Aja is the lead programmer and built
the original search engine.
- [Demis] So Aja's responsibility is quite a big one.
He'll be the one sitting opposite Lee Sedol
and actually playing the moves AlphaGo makes.
- I'm feeling excited.
Lee Sedol, 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, Demis, 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 AlphaGo.
It's very nice to meet you.
- Thank you, thank you.
So likewise.
It's a real pleasure to meet you.
I love the game of Go.
I'm not very good, but I don't know if you know,
but we actually have something in common.
I actually also trained at a game at a young age.
I used to be, when I was young, a professional chess player.
(speaking in foreign language)
I used to play for the England team
and then I stopped playing when I was about 14.
When I was 13, I was the second highest
rated player in the world.
- [Translator] 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 it's okay to ask you this question,
but 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 stronger?
(Demis laughing)
- Um, uh, 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 Aja's local search.
Run that in AlphaGo, generate a whole new data.
- [Man] Exactly.
- 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 Lee Sedol,
there would be nothing better than talking to a professional
and we couldn't have picked a better person that Fan Hui.
- [Aja] We invite him as an advisor
because, during the match, we found
he is a man of good spirit.
- [Woman] 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.
- 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 that being the 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 could be completely delusional
thinking 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.
- [Woman] 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
cuz they went wrong unfortunately.
So we're basically 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 a little bit of anxiety.
(upbeat music)
- [Reporter] 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.
- [David] Tomorrow, Julian and George,
they pack up version 18, they stick it on a laptop
and they fly out to Seoul.
(dramatic music)
- Is everything all set for the victory against Lee Sedol?
- Everything is set, I think, but when I get to the hotel,
I'm gonna 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.
- [Woman] Alright, rehearsal, let's go, please folks.
- Yes, there is a terrace and we will have security
so he'll be able to go up there and be by himself.
- When I got here I didn't expect the attention on the man.
It was literally front page news.
About eight million Koreans play the game of Go
and, even if you 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.
(crowd chattering)
(cameras clicking)
- [David] 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.
- [Demis] Where you gonna be?
- I'll start in the match room
and then I'm gonna come in here,
make sure everything's sound.
- 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.
It'll be fine.
Be fine, be fine.
- Hello and welcome to the DeepMind challenge,
game one, round one, live from the Four Seasons
here in Seoul, Korea.
I am Chris Garlock of the American Go E-Journal.
I'm here with Michael Redman nine dan professional.
Welcome, Michael.
Want to give a shout out to all
the folks watching around the world.
- [Man] Well, the excitement is pretty palpable
here in the hotel.
I've never seen a crush of interested reporters
from around the world.
- [Announcer] All right, folks,
here you're gonna see history made.
Stay with us.
- [Man] 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 here.
Extremely proud of everyone of you and what we've done
and, win or loss, I think it's just amazing that we're here.
(cameras clicking)
(soft music)
(dramatic music)
- [David] 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.
(cameras clicking)
(dramatic music)
- [Aja] I was a bit nervous.
It's the first time that I sit in front
of a world class Go player.
And I actually can feel the spirit and courtesy
of a great Go player like Lee Sedol
because I think it is the first time
he face a strange opponent.
I think it's not a human, has no emotion.
It's cold, but he stay very calm.
And I can feel his mental strength.
(soft music)
- Oh! - Oh.
- I'm Andrew Jackson.
With me here is Myungwan Kim,
a nine dan prof 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?
- From the very beginning?
- Yeah, yeah.
AlphaGo play very well, just like a top professional.
- Just like a top professional?
- [Myungwan] 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.
- [Michael] I just saw him looking at his opponent's face
and that's just a kind of a habit.
- [Chris] Just an instinct as a player to look
at the person across the board from you.
- [Michael] It's sort of like something Lee Sedol would do
when he was wondering how his opponent was feeling.
It's just a habit.
So, it's not as if Aja Huang is gonna do any giveaway
cuz Aja Huang isn't AlphaGo, right.
- Oo. - Oh!
- [Man] Oo.
(soft music)
- It's hard to know where to be.
All the different rooms are like exciting
in a different way.
Like nice to be here at the heart of the operation.
- [Demis] Yeah, I feel safe here.
- Yes, go for it.
- [Demis] It's done it.
It's gone in.
- Ooh, look at his face, look at his face!
- That is not a confident face.
He's pretty horrified by that.
- I can't believe what I see right now.
She thought, you know, she's only a bit behind.
It's made a very aggressive move here.
It make it very complicated.
I think Lee Sedol, if he doesn't respond mentally,
then he can collapse.
- [Man] 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 see often, about move a hundred and fifty,
AlphaGo goes for the kill.
We're move a hundred and fifteen now
so we're going 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 that Lee Sedol would be leading
the game confidently, but it turned out
that he's struggling at the moment.
But I think eventually he will prevail, I hope.
I was more five to zero, but now I'm not sure about that.
- Myungwan, it looks like you've gotta count.
- Yeah, right. - What do you think?
- White won a lot at this time, if you check that.
- If it's like this, white has won by a lot.
- Wow, it's so shocking.
I expected AlphaGo to win only one game.
- Oh.
- [Aja] 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.
- [Aja] I think he resigned in a very polite way.
Lee Sedol, he's black, but he put white stone.
- [Man] I think he resigned.
- Oh my gosh.
- Yeah, time has stopped.
- Wow.
(upbeat music)
- [Woman] Congratulations.
- [David] 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.
(cameras clicking)
- [Reporter] In the battle between man versus machine,
a computer just came out the victor.
- [Reporter] DeepMind put its computer program to the test
against one of the brightest minds in the world and won.
- [Reporter] AlphaGo beat a professional player
who has 18 Go World Championships under his belt.
The victory is created a breakthrough
in artificial intelligence.
- [David] 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.
- [Reporter] In a match up 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 Sedol lost the first match up,
but he's got four more chances.
- It is a bit strange being on the front cover
and everything as a computer scientist.
Nobody used to learn codes.
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.
- [Julian] Like if you look at Aja, he avoids
all the cameras like crazy.
He's like, the game is finished,
and he's like, I'll go back in his room.
And I think a lot of computer scientists would be like that.
We're more about doing our work
than standing in the spotlight.
- [Announcer] Hello and welcome to game two,
round two in the Google DeepMind challenge throw down
between man and machine.
Game one, the machine takes down a man.
Huge shock.
Headlines around the world.
- [Man] 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
watched this game worldwide.
It was just incredible and, if anything,
today is probably even more of a madhouse.
So Lee Sedol knows today, he knows that this is just
a really important game, right.
He's gotta win.
- [Michael] Lee Sedol on white.
I think probably looking for a little payback.
- [Chris] My impression is that maybe
he underestimated AlphaGo and he's gonna change his tactics.
- Yeah.
- He's playing at half his speed actually.
- [Michael] Well, if I say anything about AlphaGo
that is not normal, is maybe the way it handles a game
when it thinks its ahead.
- We're actually gonna have a visit
from one of the team and we'll talk about exactly
that point from the inside.
Thanks so much for coming by.
I really appreciate it.
Can you sort of share a bit of what is going on in AlphaGo.
- So AlphaGo has these three main components.
There's the Policy 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 will 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.
- [Man] Oh, looks like Lee is taking
a little bit of a break.
(soft music)
(speaking in foreign language)
- The value, uh...
- That's a very surprising move.
- [Chris] I thought it was a mistake.
- So coming on top of a fourth line zone is really unusual.
- [Chris] Yeah, that's an exciting move.
I think we're seeing an original move here.
That's the kind of move that you play Go for.
- [Man] Hey.
Interesting stuff.
- This fifth line shoulder hit is uh...
- [Michael] I wasn't expecting that.
I don't really know if it's a good
or bad move at this point.
- [David] The professional commentators almost unanimously
said that not a single human player
would have chosen move 37.
So I actually had a poke around in AlphaGo
to see what AlphaGo thought.
And AlphaGo actually agreed with that assessment.
AlphaGo said it was a one 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 onto the fact
that they are confused, right.
That is an interesting moment.
When everyone else is confused,
who's not confused beside the machine?
- [Chris] He's back, Lee is back.
(dramatic music)
- Go is like geopolitics.
Like something small that happens here
can have a ripple effect hours down the road
in a different part of the board.
The game kind of turned on its axis at that moment.
- [Michael] This is a tough game for Lee Sedol.
AlphaGo is just not letting Lee Sedol do what he wants.
- Black has almost 60 points.
That's a lot.
- [Andrew] That's not a good sign.
Lee Sedol just slapped himself on the side of the head.
- [Myungwan] Oh wow.
- I think black's ahead at this point.
- It's looking good, ain't it?
We're on that steady path now.
(soft music)
- 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 on 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,
there 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 was 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.
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 and 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 misstep that threshold
where we do cross over into danger.
But the good news is there are already people
thinking about those dangers.
- You know, there's a lot of talk now
and we're leading the discussion 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 longterm 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.
Lee Sedol, Go master, back to the wall.
He's down two-zero.
He's got to win today to keep hope alive.
- I heard that four pros went to visit him
to console him into a review after--
- Console him?
You think he's upset?
- I mean Lee Sedol is upset.
Yeah.
- In the beginning, there was a forceful fight.
And AlphaGo play very well so he secure a very early lead.
From (mumbles) the window was very high already.
It was climbing towards a hundred percent.
- It's looking good for us.
That black ruby is huge and it's got nowhere to go
and it's gonna be running around.
(soft music)
- [Commentator] I don't know how to describe this situation.
If I were black, I will resign.
He should admit that we are facing the strongest
existence ever in Go history.
- There's no point in playing out the end game
when you're gonna lose, right.
- [Chris] Even if black can live there, oh, he resigned.
- [Michael] It's done, it's done.
- Okay. - Wow.
Wow.
You saw history made here tonight.
- [Chris] AlphaGo has won again, three straight wins.
- [Michael] Three straight wins has won the match.
- [Demis] You know, certainly, I feel a bit ambivalent
about it given I'm a games player
and Go is the pinnacle of board games.
But I really like the statement
one of the top Chinese professionals said,
if AlphaGo wins, maybe we'll really start
to get to see what this game is about.
- [Maddy] I couldn't celebrate.
It was fantastic that we had won,
but there was such a big part of me that saw this man
trying so hard and being so disappointed.
(dramatic music)
- [Cade] 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.
- [Chris] 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? - Yeah.
- Everyone's still cheering for Lee Sedol
and, yeah, it's not going very well.
- It feels pretty good for black at this point.
- It feels pretty good for black, yes.
- [Michael] 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.
- [Commentator] I think he is already planning
on trying something.
- Yes, yes.
- There is a little potential there.
And I think maybe he's gonna try to do something.
- [Andrew] Lee Sedol magic.
- Lee Sedol, he's running short on time,
but he's gonna have to use up all his time.
- [Commentator] He just burned like seven or eight minutes
just on this move already.
- We can't find anything.
- [Chris] What is Lee Sedol up to here?
- [Michael Yeah, he's really concentrating.
- [Chris] He really is, look at that.
- [Chris] This is the hinge of the game.
- Oh, look at that move.
That's an exciting move.
- Look. - Oh, he found the wedge.
- [Chris] Whoa.
- [CMichael] It's gonna change the equation
because now black cannot escape.
- That would be so cool if that works.
- Ooh!
- [Commentator] AlphaGo has just played
something maybe unusual.
- [Michael] You know, I'm not actually sure
what AlphaGo is trying to do here.
- [Chris] What's that about?
- [Michael] I don't really understand it.
- Well, well.
- 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's like it's fallen off a cliff.
Yeah, it's made a mistake.
- Did anything strange happen in the...
- [Man] No, it all looked normal.
- Well, we can definitely say, well, there's a weakness.
Well, we definitely say it's a mistake.
- [David] I felt this mixture of a sinking feeling
in my stomach where I was wondering if AlphaGo
is becoming delusional in this situation where I could see
that it was starting to play strangely.
And, at the same time, relief that Lee Sedol,
that he was actually in with a chance now.
- I knew after move 78, after like 10 or 20 moves,
I saw AlphaGo strange moves.
I know AlphaGo somehow became crazy,
but I didn't realize why.
- Whoa!
We slipped from 95 ahead.
- At the point, where we made the mistake?
I think that something went wrong.
That's the longest we've searched this entire game.
I think it's searched so deeply it's confused itself.
- [Michael] I do get the impression that AlphaGo
is sort of gone off on a tangent.
- What are you doing now?
- Maybe it has a master plan?
- No, it doesn't even think it has, does it?
So it knows it's made a mistake.
It starts evaluating it the other way.
Look, look, Lee's so confused.
He's like what is it doing?
That's not a I'm scared confused.
That's a what is it doing?
- 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 that AlphaGo.
- Oh, you're kidding me.
This next move we're gonna play,
I think they're gonna laugh.
Everybody's gonna laugh.
- [Commentator] Oh, oh, oh!
- [Man] I don't really know
what AlphaGo is trying to do here.
- That's the understatement of the year.
- [Andrew] No, no, that's the move.
Aja Huang makes no misclicks.
Lee Sedol is very confused.
These are not human moves.
- This move, also, sort of inexplicable.
- [Chris] I mean you can clearly call those the saves.
- [Michael] Yes, of course.
- But it's the first time in the four matches
that we've seen moves like that.
- Oh, the value dropped even more.
- That's weird.
- [Andrew] Come on, Lee Sedol.
- This unbelievable.
- Alright!
- I was so confident that this black mire
would just be consolidated by black
and there's 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 it.
- 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.
I think it looks like Aja Huang maybe sitting there
also knows that the game is over.
- [Andrew] No, I haven't seen him smile yet.
- [Andrew] He's so serious.
He wants to be careful.
(dramatic music)
- [Man] There you go, AlphaGo resigned.
- Looks like AlphaGo has resigned.
- [Chris] Wow.
- The most amazing game,
I'm almost gonna tear up,
was game four where he comes back and wins.
(crowd cheering)
- I heard from so many people
saying they were running out in the street.
They were so happy.
They were chanting, they were celebrating.
- Especially after a zero-three down, at the time,
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.
(upbeat music)
(crowd clapping)
- My question is about number 78 move,
Chinese top Go player (mumbles) it was a brave play,
what were you thinking when you made that play?
Thank you.
- [Demis] It does leave me a little bit in awe
of the human brain's power, in particular,
Lee's amazing ability to cause AlphaGo problems
and find something seemingly out of nothing.
And so we really want to understand what had happened.
(upbeat music)
- [Announcer] Welcome back to the Four Seasons.
World champion, Lee Sedol, went looking
for AlphaGo's weakness in game four and he found it.
Today, last round, he's looking to see
if he can repeat that.
We'll see what happens.
- [Commentator] The place is a madhouse downstairs.
There may be as many, if nor more, journalists here today
than there were for game one.
- [Maddy] We were really excited for the fifth match
to see what would happen.
Was this going to be a three-two thing
or was it going to be a four-one thing?
And, you know, there's a different message
with both of those.
- You weren't crazy about the timing on this move.
- No, 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.
- Oh no, I hope it doesn't...
Oh no, it needs to play the...
- [Chris] Are we seeing another short circuit
or is there something, what's a--
- [Commentator] I think it could be a kind of a misreading.
- [Michael] And were you pretty comfortable
with saying that--
- [Chris] That it's looking good for Lee Sedol?
- [Michael] Good for Lee Sedol.
- Why is it playing in there for?
- 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.
- The whole game we thought AlphaGo was wrong
about the board position and we were super worried
that it's gonna play garbage.
It's going to be like losing in a very embarrassing way.
And this continued for the whole game.
- 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.
- This one looks like white is winning.
Aah!
- We all say some of AlphaGo's 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 dan play looks like.
It looks weird and we don't quite understand it.
- I think it is important to study more
about AlphaGo's mistake-like moves.
And maybe we can adjust our knowledge of AlphaGo.
- 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 gonna 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 how much are we talking?
Two points? - One and a half.
- One and a half points.
- Of course, Go is just a game.
But we could learn important lessons
from a computer being so successful at Go.
Machines will have the capability,
not only to crunch through 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 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 Sedol, I think white
might have a slight advantage here.
- Who told us that?
- Someone, I don't know.
- Winning, okay, not won.
- That's what she said.
- No, not really.
- We don't know the score.
We have no idea what's going on, right.
(crowd clapping)
- I think it just really is a once-in-a-lifetime thing.
I would say it's the most amazing thing I've experienced.
You know, for us, it's the culmination of a 20-year dream.
- It started as a pure research endeavor.
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 many people would discourage me.
They would say 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, (speaking in foreign language)
- 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'd 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 in Lee Sedol,
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, in particular,
the technology 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.