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(dramatic music)
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Downloaded from
YTS.MX
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Official YIFY movies site:
YTS.MX
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It's intensely contemplative.
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It is almost hypnotic.
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It's like putting your hand
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on the third rail
of the universe.
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If you play Go seriously,
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there is a chance that
you will get exposed
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to this experience
that is kind of like
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nothing else on the planet.
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Go is putting you in a
place where you're always
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at the very farthest
reaches of your capacity.
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There's a reason that
people have been playing Go
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for thousands and
thousands of years, right?
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It's not just that they
wanna understand Go.
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They wanna understand
what understanding is.
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And maybe that is truly
what it means to be human.
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When I was a kid I
loved playing games.
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I started off with
board games like chess
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and then I bought my first
computer when I was eight
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with winnings from
a chess tournament.
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Ever since then, I felt that
computers were this sort
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of magical device that could
extend the power of your mind.
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Virtual environments in games.
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We think they're
the perfect platform
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for developing and
testing AI algorithms.
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Games are very convenient, in
that a lot of them have scores
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so it's very easy to measure
incremental progress.
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I'm gonna show you a few videos
of the A-Jen system, the AI.
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Let's start off with Break Out.
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So here you control the bat
and ball and you're trying
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to break through this
rainbow-colored wall.
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The A-Jen system has to
learn everything for itself,
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just from the raw pixels,
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doesn't know what
it's controlling,
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doesn't even know what
the object of the game is.
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Now, the beginning,
after a hundred games,
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you can see the A-Jen
is not very good.
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It's missing the ball
most of the time,
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but it's starting to
get the hang of the idea
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that the bat should
go towards the ball.
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Now, after 300 games,
it's about as good
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as any human can play
this and pretty much
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gets the ball back every time.
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We thought, well,
that's pretty cool,
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but we left the system
playing for another 200 games.
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And it did this amazing thing.
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It found the optimal
strategy was to dig a tunnel
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around the side and put the ball
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around the back of the wall.
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The researchers working on
this are amazing AI developers,
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but they're not so
good at Break Out
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and they didn't know
about that strategy,
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so they learned something
from their own system,
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which is pretty funny and
quite instructive, I think,
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about the potential
for general AI.
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So, for us, what's
the next step now?
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Go is the most complex game
pretty much ever devised by man.
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Beating a professional
player at Go
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is a longstanding, grand
challenge of AI research.
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(bells tolling)
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Wow.
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Dear Mr Fan, my name
is Demis Hassabis.
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I run an artificial
intelligence company
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based in London called DeepMind.
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As the strongest Go
player in Europe,
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we would like to invite you
to our offices in London
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both to meet you in person
and to share with you
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an exciting Go project
that we're working on.
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If you would be interested
in coming to visit us,
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please let us know.
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Many thanks, kind
regards, Demis.
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We needed to get
Fan Hui to DeepMind
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to see we were a
serious operation
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and we were serious people
doing proper research.
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And the search time is
getting better and better
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as we go from, for
example, one to eight
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and any one of these.
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It always goes up.
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We think of DeepMind
as kind of like
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an Apollo program effort for AI.
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Our mission is to fundamentally
understand intelligence
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and recreate it artificially.
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And then, once we've done
that, we feel that we can use
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that technology to help society
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solve all sorts
of other problems.
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If you search
through the actual game
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we can see kind of how
an algorithm thinks.
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What's the most likely variation
that it thinks will happen.
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[Demis] We've been working
on AlphaGo and our program
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to play Go for just
under two years now.
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All the little patterns
cascade together,
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layer after layer after
layer after layer.
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I started talking
about the game of Go
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with Demis more
than 20 years ago.
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And so, this has been
a really long journey.
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The game of Go is the holy grail
of artificial intelligence.
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For many years, people
have looked at this game
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and they thought, "Wow,
this is just too hard."
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Everything we've
ever tried in AI,
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it just falls over when
you try the game of Go
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and so that's why
it feels like a real
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litmus test of progress.
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If we can crack Go, we know
we've done something special.
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So, with Fan Hui, we
started talking around
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what the real purpose
of the visit was.
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It wasn't just a Go project
we wanted him to help with.
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That actually we
wanted to play him
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and we had a very
strong program.
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A lot of people have thought
that it was decades away.
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Some people thought it would
be never because they felt
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that to succeed at Go you
needed human intuition.
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Go is the world's oldest,
continuously played board game
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and, in some sense, it
is one of the simplest
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and also most abstract.
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There's only
one type of piece.
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There's only one type of move.
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You just place that
piece on the board
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and then your goal is
to create a linked group
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of your stones that surrounds
some empty territory.
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And, when you surround enemy
stones, you capture them
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and remove them from the board.
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You earn points by
surrounding territory
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and, at the end of
the game, the person
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with the most territory wins.
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It seems really simple, but
then you sit down to play
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and you realize right
away, it's like, well,
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I technically know
what I'm allowed to do,
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but I have no clue
what I should do.
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Go's incredibly challenging
for computers to tackle
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because compared, to say, chess,
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the number of possible moves
in a position is much larger.
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In chess it's about 20.
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In Go it's about 200.
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And the number of possible
configurations of the board
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is more than the number
of atoms in the universe.
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So, even if you took all
the computers in the world
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and ran them for a million
years, that wouldn't be enough
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compute power to calculate
all the possible variations.
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If you ask a great Go
player why they played
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a particular move, sometimes
they'll just tell you
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it felt right.
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So we have to come up with
some kind of clever algorithm
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to mimic what people do
with their intuition.
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- Nice to meet you.
- Oh, hello.
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Nice meet you too.
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[Demis] So with Fan Hui, we
agreed a best of five match
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and we agreed it
would be filmed.
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You know, we would treat
it as a serious match.
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In that first match, I think
something clicked for him
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that this wasn't an
ordinary Go program.
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We weren't just doing the
same as everyone else,
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that something
new was happening.
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After losing, losing, losing,
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you can feel his pressure is
getting heavier and heavier.
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And several times
after the game he said,
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he wanted to go
out for fresh air.
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I said, "Oh, I can go
with you and have a chat."
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He said, "No, I
want to go myself."
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I worried whether
he'd even come back.
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You know, he seemed
very low and he spent
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about an hour away
from the office.
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He came back completely changed.
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Artificial intelligence
researchers have solved
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the game of Go a decade
earlier than expected.
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The computer named
AlphaGo was able
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to beat the European
human champion.
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[Reporter] Artificial
intelligence researchers
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have made a significant
breakthrough.
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It really is a
big leap forward.
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There's a big difference
between the way the IBM computer
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beat Kasparov, which
was programed by
expert chess players,
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and the way the
Go-playing computer
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more or less learned itself.
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The way we start off training
AlphaGo is by showing it
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a 100,000 games that
strong amateurs have played
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that we downloaded
from the internet.
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And we first, initially,
get AlphaGo to mimic
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the human player and
then, through self-playing
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reinforcement learning, it
plays against different versions
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of itself many millions of times
and learns from its errors.
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These specific ideas
that are driving AlphaGo
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are gonna drive our future.
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The technologies at
the heart of AlphaGo,
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they're what are called
deep neural networks
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which, essentially,
mimic the web
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of neurons in the human brain.
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It's a very old idea, but
recently, due to increases
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in computing power, these
neural networks have become
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extremely powerful,
almost overnight.
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Big neural networks
that operate on big data
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can achieve surprising things.
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AlphaGo found a way how
to learn how to play Go.
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Learning is the key thing here.
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It's machine learning.
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The whole beauty of
these types of algorithms
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is that, because they're
learning for themselves,
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they can go beyond what
we as the programmers
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know how to do and allow us
to make new breakthroughs
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in areas of science
and medicine.
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So AlphaGo is one
significant step
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towards that ultimate goal.
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The Go world were
skeptical about how strong
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really was AlphaGo and how
much further did it need
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to get to beat the
top professionals.
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Our program is improving
over time and we want to push
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the AI algorithm to the
limit and see how far
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this kind of self-improving
process can go.
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So we needed to look for
an even greater challenge.
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[Reporter] A match
like no other is about
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to get underway in South Korea.
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[Reporter] Lee Sedol, the
long-reigning global champ.
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[Reporter] This
guy is a genius.
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[Reporter] He will take on
artificial intelligence program
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00:14:07,398 --> 00:14:11,599
AlphaGo, in the ultimate human
versus machine smack down.
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This is a huge moment
for both the world
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00:14:13,703 --> 00:14:17,671
of artificial intelligence
and, I think, the world of Go.
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So far, AlphaGo has beaten
every challenge we've given it,
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but we won't know its true
strength until we play
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somebody who is at the top
of the world like Lee Sedol.
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We chose Lee Sedol
because we wanted
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00:14:30,484 --> 00:14:32,984
a legendary, historic player.
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Somebody who has
been acknowledged
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as the greatest player
of the last decade.
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[Translator] I will
not be too arrogant,
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but I don't think that it
will be a very close match.
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The level of the player
that AlphaGo went against
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in October is not
the same level as me.
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So, given that a couple
of months was only passed,
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I don't think that
it is enough for it
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to be able to catch up with me.
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My hope is that it will
be either five-zero for me
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or maybe four to one.
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So the critical point for me
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is to make sure I
do not lose one.
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(speaking in foreign language)
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We don't know how well
our system will play
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against someone as
creative as Lee Sedol.
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Also, he's very famous for
very creative fighting play
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so this could be difficult
for us, but we'll see.
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Maybe in some ways he's the most
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difficult opponent
we could pick.
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There was still so much of a
question about whether or not
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they could beat
someone like Lee Sedol.
246
00:15:39,009 --> 00:15:41,442
Fan Hui is a good
player, but he's nothing
247
00:15:41,444 --> 00:15:43,544
like the very top players.
248
00:15:43,546 --> 00:15:46,146
Lee Sedol is a nine
dan professional.
249
00:15:46,148 --> 00:15:47,514
Nine dan professional
is the highest rank
250
00:15:47,516 --> 00:15:51,217
you can achieve in Go,
the ranking system.
251
00:15:51,219 --> 00:15:53,152
Fan Hui, who's the
European champion,
252
00:15:53,154 --> 00:15:55,320
is just a two dan professional.
253
00:15:55,322 --> 00:15:57,755
On the other hand, at
the very top, Lee Sedol
254
00:15:57,757 --> 00:15:59,757
is nine dan professional.
255
00:15:59,759 --> 00:16:02,593
Lee Sedol is to Go what
Roger Federer is to tennis.
256
00:16:02,595 --> 00:16:04,595
He's playing in Wimbledon
to win the Grand Slam
257
00:16:04,597 --> 00:16:06,063
and it's not just this year.
258
00:16:06,065 --> 00:16:08,031
He'll be there next year
and the year after that
259
00:16:08,033 --> 00:16:10,099
and the year after that.
260
00:16:24,447 --> 00:16:27,682
(children chattering)
261
00:16:38,627 --> 00:16:40,628
Go is taken
seriously in Korea.
262
00:16:40,630 --> 00:16:43,430
It's so much part of the
culture like breathing
263
00:16:43,432 --> 00:16:47,667
or, you know, like taking
swimming lessons or something.
264
00:17:01,381 --> 00:17:04,549
In ancient China,
Japan, Korea,
265
00:17:04,551 --> 00:17:08,586
Go is one of the four noble
things for accomplishment
266
00:17:10,322 --> 00:17:14,124
for literati with music,
poetry and painting.
267
00:17:15,726 --> 00:17:18,494
So people think the Go players
268
00:17:19,629 --> 00:17:22,197
are very smart and very noble.
269
00:17:27,669 --> 00:17:31,138
Mr Kwon started this
school so that he could
270
00:17:31,140 --> 00:17:34,274
produce great player in Korea.
271
00:17:34,276 --> 00:17:38,244
Lee Sedol, when he was age
of eight, he came in here
272
00:17:38,246 --> 00:17:42,681
attending class nine a.m
until nine p.m. seven days.
273
00:17:42,683 --> 00:17:45,250
And then he stay with Mr Kwon.
274
00:18:03,569 --> 00:18:07,271
Lee Sedol was a little
boy that I remember
275
00:18:07,273 --> 00:18:09,539
when I was a
student studying Go.
276
00:18:09,541 --> 00:18:12,642
He was very young
and rural enough
277
00:18:12,644 --> 00:18:15,745
to think that pizza
grew on trees.
278
00:18:37,534 --> 00:18:41,169
Lee Sedol plays things
that are interesting
279
00:18:41,171 --> 00:18:43,638
where you felt like he's
beyond winning and losing.
280
00:18:43,640 --> 00:18:45,840
He wants to do something
that's innovative
281
00:18:45,842 --> 00:18:47,708
or takes things
to the next level.
282
00:18:47,710 --> 00:18:51,244
So every Go player
study his game, for sure.
283
00:18:51,246 --> 00:18:54,747
Roughly, 10 years, he dominates
the professional Go world.
284
00:18:54,749 --> 00:18:57,316
He win 18 World Championships.
285
00:19:10,596 --> 00:19:14,798
Definitely, Lee Sedol is
gonna win the game, five all.
286
00:19:14,800 --> 00:19:16,866
Yeah, all game.
287
00:19:16,868 --> 00:19:19,468
He's gonna win all game.
288
00:19:19,470 --> 00:19:22,571
We had our evaluation
match last week.
289
00:19:22,573 --> 00:19:24,506
We won a game and
we lost a game.
290
00:19:24,508 --> 00:19:26,341
And we lost a game in a
way that would have made us
291
00:19:26,343 --> 00:19:29,677
look extremely foolish if
that happened publicly.
292
00:19:29,679 --> 00:19:31,712
It means that we
still have work to do
293
00:19:31,714 --> 00:19:33,680
and we need to take
this really seriously.
294
00:19:33,682 --> 00:19:37,716
It's just too much risk that
actually we could lose overall.
295
00:19:38,818 --> 00:19:40,785
Not only that, but we
could lose in a way
296
00:19:40,787 --> 00:19:42,720
that makes us look rather silly.
297
00:19:42,722 --> 00:19:43,854
So I guess...
298
00:19:44,755 --> 00:19:45,888
Yeah, Aja, did you
want to say anything
299
00:19:45,890 --> 00:19:46,989
about what you're trying?
300
00:19:46,991 --> 00:19:48,690
Um, I'm working hard.
301
00:19:48,692 --> 00:19:52,293
(group laughing)
302
00:19:52,295 --> 00:19:54,228
[Demis] So we're working
around the clock at the moment,
303
00:19:54,230 --> 00:19:55,829
training our algorithms further,
304
00:19:55,831 --> 00:19:57,897
trying to incrementally
keep on improving,
305
00:19:57,899 --> 00:20:00,532
right up to the moment
where we have the match.
306
00:20:00,534 --> 00:20:01,933
We've collected
together people
307
00:20:01,935 --> 00:20:04,568
with different skills
sets onto the same team.
308
00:20:04,570 --> 00:20:08,805
So we have researchers,
engineers, valuation guys.
309
00:20:13,810 --> 00:20:15,510
[Man] We don't see it.
310
00:20:15,512 --> 00:20:16,410
Okay.
311
00:20:20,648 --> 00:20:23,650
[David] Aja is the
lead programmer and built
312
00:20:23,652 --> 00:20:25,551
the original search engine.
313
00:20:25,553 --> 00:20:27,452
[Demis] So Aja's
responsibility is
quite a big one.
314
00:20:27,454 --> 00:20:29,954
He'll be the one sitting
opposite Lee Sedol
315
00:20:29,956 --> 00:20:33,757
and actually playing
the moves AlphaGo makes.
316
00:20:33,759 --> 00:20:35,658
I'm feeling excited.
317
00:20:37,460 --> 00:20:39,761
Lee Sedol, he's a great player
318
00:20:39,763 --> 00:20:42,830
and I feel honored
to play with him.
319
00:20:44,032 --> 00:20:46,533
Many of my friends, they are
very excited about the match.
320
00:20:46,535 --> 00:20:49,802
They keep telling me that
the whole world is watching.
321
00:20:49,804 --> 00:20:51,837
Just prepare AlphaGo.
322
00:20:52,705 --> 00:20:53,671
Hello.
323
00:20:53,673 --> 00:20:55,039
Hello, Demis, can you hear us?
324
00:20:55,041 --> 00:20:56,540
Yes, I can hear you guys.
325
00:20:56,542 --> 00:20:58,041
Can you hear me okay?
326
00:20:58,043 --> 00:20:59,809
Yes, perfect.
327
00:20:59,811 --> 00:21:03,612
I was curious to meet you,
such an amazing developer
328
00:21:03,614 --> 00:21:05,714
who made AlphaGo.
329
00:21:05,716 --> 00:21:07,282
It's very nice to meet you.
330
00:21:07,284 --> 00:21:08,016
Thank you, thank you.
331
00:21:08,018 --> 00:21:09,817
So likewise.
332
00:21:09,819 --> 00:21:12,386
It's a real pleasure
to meet you.
333
00:21:12,388 --> 00:21:13,820
I love the game of Go.
334
00:21:13,822 --> 00:21:17,790
I'm not very good, but I
don't know if you know,
335
00:21:17,792 --> 00:21:19,992
but we actually have
something in common.
336
00:21:19,994 --> 00:21:23,595
I actually also trained
at a game at a young age.
337
00:21:23,597 --> 00:21:26,731
I used to be, when I was young,
a professional chess player.
338
00:21:26,733 --> 00:21:29,800
(speaking in foreign language)
339
00:21:29,802 --> 00:21:32,869
I used to play for
the England team
340
00:21:32,871 --> 00:21:36,905
and then I stopped playing
when I was about 14.
341
00:21:36,907 --> 00:21:38,873
When I was 13, I was
the second highest
342
00:21:38,875 --> 00:21:40,774
rated player in the world.
343
00:21:40,776 --> 00:21:43,009
[Translator] After the
match, I would like to propose
344
00:21:43,011 --> 00:21:45,711
that I give you one
teaching game of Go
345
00:21:45,713 --> 00:21:48,680
and you give me one
teaching game of chess.
346
00:21:48,682 --> 00:21:49,747
How does that sound?
347
00:21:49,749 --> 00:21:50,981
That sounds very good.
348
00:21:50,983 --> 00:21:53,583
I would be very
honored to do that.
349
00:21:53,585 --> 00:21:57,486
I'm not sure it's okay
to ask you this question,
350
00:21:57,488 --> 00:22:01,089
but I saw the games against
Fan Hui and I didn't think
351
00:22:01,091 --> 00:22:04,425
it was quite at the
level to play with me.
352
00:22:04,427 --> 00:22:07,594
But I heard that it's
getting really stronger.
353
00:22:07,596 --> 00:22:10,697
Can I ask how much it
got stronger since then?
354
00:22:10,699 --> 00:22:13,599
(Demis laughing)
355
00:22:13,601 --> 00:22:17,502
Um, uh, I can't say
too much, of course,
356
00:22:17,504 --> 00:22:21,505
but it's definitely got
significantly stronger.
357
00:22:22,807 --> 00:22:25,709
With more time, I
think a logical approach
358
00:22:25,711 --> 00:22:29,012
would be to follow up
on Aja's local search.
359
00:22:29,014 --> 00:22:31,848
Run that in AlphaGo,
generate a whole new data.
360
00:22:31,850 --> 00:22:33,049
[Man] Exactly.
361
00:22:34,117 --> 00:22:35,050
But we're just
out of time for that
362
00:22:35,052 --> 00:22:36,951
so we have to be realistic.
363
00:22:36,953 --> 00:22:39,720
We realized that if
we wanted to prepare
364
00:22:39,722 --> 00:22:42,956
for a mammoth task like
taking on Lee Sedol,
365
00:22:42,958 --> 00:22:46,526
there would be nothing better
than talking to a professional
366
00:22:46,528 --> 00:22:50,762
and we couldn't have picked
a better person that Fan Hui.
367
00:22:52,731 --> 00:22:55,232
[Aja] We invite
him as an advisor
368
00:22:55,234 --> 00:22:57,100
because, during
the match, we found
369
00:22:57,102 --> 00:22:59,202
he is a man of good spirit.
370
00:22:59,204 --> 00:23:00,136
[Woman] Welcome back.
371
00:23:00,138 --> 00:23:01,837
Thank you very much.
372
00:23:01,839 --> 00:23:05,140
It's very precious that
we have Fan Hui with us.
373
00:23:06,709 --> 00:23:09,977
He was crushed by AlphaGo, but
then he became very positive
374
00:23:09,979 --> 00:23:12,012
and a big help to us.
375
00:23:49,983 --> 00:23:53,518
The superheroes always have
a hidden vulnerability, right.
376
00:23:53,520 --> 00:23:55,887
And the same is true of AlphaGo.
377
00:23:55,889 --> 00:23:59,089
It's unbelievably
superhuman in general,
378
00:24:00,658 --> 00:24:04,060
but it has some particular
weaknesses in some situations.
379
00:24:04,062 --> 00:24:05,795
We can think of
that being the space
380
00:24:05,797 --> 00:24:07,229
of all the things
it knows about.
381
00:24:07,231 --> 00:24:09,664
And it knows about most
of it extremely well,
382
00:24:09,666 --> 00:24:11,966
but then there'll be these
tricky lumps of knowledge
383
00:24:11,968 --> 00:24:14,969
that it just
understands very poorly
384
00:24:14,971 --> 00:24:17,004
and it's really hard
for us to characterize
385
00:24:17,006 --> 00:24:19,072
when it's going to enter
into one of these lumps.
386
00:24:19,074 --> 00:24:21,307
But, if it does, it could
be completely delusional
387
00:24:21,309 --> 00:24:23,208
thinking it's alive on
one part of the board
388
00:24:23,210 --> 00:24:25,977
when, in fact, it's
dead or vice-versa.
389
00:24:25,979 --> 00:24:28,779
So there is a real risk that
we could lose the match.
390
00:24:39,089 --> 00:24:41,990
[Woman] We've got version 18
in the pipeline, haven't we?
391
00:24:41,992 --> 00:24:43,591
Well, we'll only
go for version 18
392
00:24:43,593 --> 00:24:45,159
if it makes a
significant improvement
393
00:24:45,161 --> 00:24:47,961
which we're having to
rerun all the tests
394
00:24:47,963 --> 00:24:49,996
cuz they went wrong
unfortunately.
395
00:24:49,998 --> 00:24:52,131
So we're basically a day behind
396
00:24:52,133 --> 00:24:54,633
in our evaluation
because of that.
397
00:24:54,635 --> 00:24:56,067
Well, maybe we just
need to be realistic
398
00:24:56,069 --> 00:24:58,135
that we've tried
a bunch of things
399
00:24:58,137 --> 00:24:59,535
and we've come to the
point where we said
400
00:24:59,537 --> 00:25:01,571
we would actually
start freezing the code
401
00:25:01,573 --> 00:25:05,641
and saying, "Look, it's
actually not panning out."
402
00:25:08,044 --> 00:25:10,078
These delusions are
still a realistic
403
00:25:10,080 --> 00:25:12,046
possibility for the match.
404
00:25:12,048 --> 00:25:15,049
We have some weaknesses
that I don't think
405
00:25:15,051 --> 00:25:18,052
we're going to fix
fully before the match
406
00:25:18,054 --> 00:25:21,921
so that's causing us a
little bit of anxiety.
407
00:25:21,923 --> 00:25:24,590
(upbeat music)
408
00:25:27,160 --> 00:25:30,061
[Reporter] Lee Sedol is
getting ready to rumble.
409
00:25:30,063 --> 00:25:32,229
On Wednesday live
across the internet,
410
00:25:32,231 --> 00:25:34,731
this professional
South Korean Go player
411
00:25:34,733 --> 00:25:38,968
will take on artificial
intelligence program AlphaGo.
412
00:25:44,206 --> 00:25:46,140
[David] Tomorrow,
Julian and George,
413
00:25:46,142 --> 00:25:48,909
they pack up version 18,
they stick it on a laptop
414
00:25:48,911 --> 00:25:51,177
and they fly out to Seoul.
415
00:25:51,179 --> 00:25:54,180
(dramatic music)
416
00:25:54,481 --> 00:25:57,516
(overlapping chatter)
417
00:26:08,994 --> 00:26:12,229
Is everything all set for
the victory against Lee Sedol?
418
00:26:12,231 --> 00:26:15,098
Everything is set, I think,
but when I get to the hotel,
419
00:26:15,100 --> 00:26:16,799
I'm gonna catch
up with the team.
420
00:26:16,801 --> 00:26:19,635
What we should do in the
time remaining is list things
421
00:26:19,637 --> 00:26:22,070
that could go wrong in the
solidity of the system.
422
00:26:26,108 --> 00:26:28,809
[Woman] All right, rehearsal,
let's go, please folks.
423
00:26:34,148 --> 00:26:36,883
Yes, there is a terrace
and we will have security
424
00:26:36,885 --> 00:26:39,218
so he'll be able to go up
there and be by himself.
425
00:26:50,763 --> 00:26:53,364
When I got here I didn't
expect the attention on the man.
426
00:26:53,366 --> 00:26:55,766
It was literally
front page news.
427
00:26:55,768 --> 00:26:58,769
About eight million
Koreans play the game of Go
428
00:26:58,771 --> 00:27:01,138
and, even those who don't
recognize Lee Sedol,
429
00:27:01,140 --> 00:27:03,373
he's a national figure.
430
00:27:03,375 --> 00:27:04,874
And so there's that, right.
431
00:27:04,876 --> 00:27:06,275
There's some national
pride involved,
432
00:27:06,277 --> 00:27:08,076
but it's more than that.
433
00:27:08,078 --> 00:27:11,345
Just the very thought of
a machine playing a human
434
00:27:11,347 --> 00:27:13,447
at something like this,
I think is inherently
435
00:27:13,449 --> 00:27:15,248
intriguing to people.
436
00:27:18,218 --> 00:27:21,220
(crowd chattering)
437
00:27:21,222 --> 00:27:24,223
(cameras clicking)
438
00:28:08,768 --> 00:28:11,069
[David] I just really
hope we win this first game.
439
00:28:11,071 --> 00:28:12,270
If you lose the first
game, you literally
440
00:28:12,272 --> 00:28:14,505
have to win three out of four
441
00:28:14,507 --> 00:28:16,139
which is hard work.
442
00:28:16,141 --> 00:28:17,507
[Demis] Where are you
gonna be?
443
00:28:17,509 --> 00:28:18,774
I'll start in the match room
444
00:28:18,776 --> 00:28:19,508
and then I'm gonna come in here,
445
00:28:19,510 --> 00:28:20,909
make sure everything's sound.
446
00:28:20,911 --> 00:28:23,944
Yeah, you should
probably be in there.
447
00:28:26,447 --> 00:28:27,814
I know you're nervous.
448
00:28:27,816 --> 00:28:29,515
Yeah, I'm nervous.
449
00:28:29,517 --> 00:28:30,782
I'm nervous.
450
00:28:32,217 --> 00:28:33,050
How are you?
451
00:28:33,052 --> 00:28:34,084
You're not nervous?
452
00:28:34,086 --> 00:28:35,184
- A bit.
- A little bit, yeah?
453
00:28:35,186 --> 00:28:39,021
It's good to have a
little bit of nerves.
454
00:28:39,023 --> 00:28:40,255
It'll be fine.
455
00:28:42,157 --> 00:28:44,024
Be fine, be fine.
456
00:28:44,026 --> 00:28:47,260
Hello and welcome to
the DeepMind challenge,
457
00:28:47,262 --> 00:28:50,830
game one, round one, live
from the Four Seasons
458
00:28:50,832 --> 00:28:53,265
here in Seoul, Korea.
459
00:28:53,267 --> 00:28:56,167
I am Chris Garlock of the
American Go E-Journal.
460
00:28:56,169 --> 00:28:59,203
I'm here with Michael Redman
nine dan professional.
461
00:28:59,205 --> 00:29:00,337
Welcome, Michael.
462
00:29:00,339 --> 00:29:02,072
Want to give a shout out to all
463
00:29:02,074 --> 00:29:04,374
the folks watching
around the world.
464
00:29:04,376 --> 00:29:06,175
[Man] Well, the excitement
is pretty palpable
465
00:29:06,177 --> 00:29:07,075
here in the hotel.
466
00:29:07,077 --> 00:29:10,245
I've never seen a crush
of interested reporters
467
00:29:10,247 --> 00:29:12,146
from around the world.
468
00:29:18,786 --> 00:29:20,052
[Announcer] All right, folks,
469
00:29:20,054 --> 00:29:21,053
you're here, you're gonna
see history made.
470
00:29:21,055 --> 00:29:22,154
Stay with us.
471
00:29:22,156 --> 00:29:23,922
[Man] Five minutes, guys.
472
00:29:23,924 --> 00:29:25,056
Five minutes.
473
00:29:33,498 --> 00:29:36,433
I just thought we should
take a moment together
474
00:29:36,435 --> 00:29:40,803
and just think about
what's about to happen.
475
00:29:40,805 --> 00:29:42,371
Extremely excited to be here.
476
00:29:42,373 --> 00:29:45,374
Extremely proud of everyone
of you and what we've done
477
00:29:45,376 --> 00:29:48,076
and, win or loss, I think it's
just amazing that we're here.
478
00:30:01,523 --> 00:30:04,491
(cameras clicking)
479
00:30:05,326 --> 00:30:08,027
(soft music)
480
00:30:51,370 --> 00:30:54,205
(dramatic music)
481
00:32:00,138 --> 00:32:02,105
[David] We had worked
so hard to make sure
482
00:32:02,107 --> 00:32:05,541
that this would go
technically smoothly.
483
00:32:05,543 --> 00:32:08,977
We tested it and
tested it and tested it
484
00:32:08,979 --> 00:32:13,380
and still, there comes that
moment, when you're live,
485
00:32:13,382 --> 00:32:16,716
all the TV cameras are
broadcasting everything
486
00:32:16,718 --> 00:32:20,853
and now it has to do the
thing you built it to do.
487
00:32:34,233 --> 00:32:37,235
(cameras clicking)
488
00:32:52,250 --> 00:32:55,085
(dramatic music)
489
00:33:09,400 --> 00:33:11,434
[Aja] I was a bit nervous.
490
00:33:11,436 --> 00:33:14,303
It's the first time
that I sit in front
491
00:33:14,305 --> 00:33:17,272
of a world class Go player.
492
00:33:17,274 --> 00:33:20,475
And I actually can feel
the spirit and courtesy
493
00:33:20,477 --> 00:33:23,478
of a great Go player
like Lee Sedol
494
00:33:23,480 --> 00:33:25,046
because I think it
is the first time
495
00:33:25,048 --> 00:33:27,581
he face a strange opponent.
496
00:33:27,583 --> 00:33:30,750
I think it's not a
human, has no emotion.
497
00:33:30,752 --> 00:33:33,585
It's cold, but he
stay very calm.
498
00:33:35,020 --> 00:33:37,787
And I can feel his
mental strength.
499
00:33:40,223 --> 00:33:42,524
(soft music)
500
00:33:48,530 --> 00:33:49,630
- Oh!
- Oh.
501
00:34:05,413 --> 00:34:06,379
I'm Andrew Jackson.
502
00:34:06,381 --> 00:34:07,379
With me here is Myungwan Kim,
503
00:34:07,381 --> 00:34:10,383
a nine dan prof from the
Korean Baduk Association.
504
00:34:10,385 --> 00:34:12,518
We are here live at
the Four Seasons Hotel
505
00:34:12,520 --> 00:34:13,819
on the 21st floor.
506
00:34:13,821 --> 00:34:14,653
What are we looking at?
507
00:34:14,655 --> 00:34:16,687
How's the game going?
508
00:34:19,157 --> 00:34:20,624
From the very beginning?
509
00:34:20,626 --> 00:34:21,524
Yeah, yeah.
510
00:34:21,526 --> 00:34:25,728
AlphaGo play very well, just
like a top professional.
511
00:34:25,730 --> 00:34:27,564
Just like a top professional?
512
00:34:27,566 --> 00:34:30,767
[Myungwan] Yeah,
it's very aggressive.
513
00:34:38,875 --> 00:34:41,543
Now, the fight is
getting really complicated.
514
00:34:41,545 --> 00:34:44,779
This is actually the first
time I've seen AlphaGo
515
00:34:44,781 --> 00:34:48,783
playing a game that has
this difficult a fight.
516
00:35:10,705 --> 00:35:13,373
[Michael] I just saw him
looking at his opponent's face
517
00:35:13,375 --> 00:35:15,274
and that's just a
kind of a habit.
518
00:35:15,276 --> 00:35:17,509
[Chris] Just an instinct
as a player to look
519
00:35:17,511 --> 00:35:19,511
at the person across
the board from you.
520
00:35:19,513 --> 00:35:22,614
[Michael] It's sort of like
something Lee Sedol would do
521
00:35:22,616 --> 00:35:25,283
when he was wondering how
his opponent was feeling.
522
00:35:25,285 --> 00:35:26,684
It's just a habit.
523
00:35:26,686 --> 00:35:30,587
So, it's not as if Aja Huang
is gonna do any giveaway
524
00:35:30,589 --> 00:35:33,556
cuz Aja Huang isn't
AlphaGo, right.
525
00:35:39,763 --> 00:35:40,596
- Oo.
- Oh!
526
00:35:40,598 --> 00:35:41,563
[Man] Oo.
527
00:36:19,835 --> 00:36:22,336
(soft music)
528
00:37:04,011 --> 00:37:05,378
It's hard to know where to be.
529
00:37:05,380 --> 00:37:06,779
All the different
rooms are like exciting
530
00:37:06,781 --> 00:37:08,413
in a different way.
531
00:37:09,748 --> 00:37:11,949
Like nice to be here at
the heart of the operation.
532
00:37:11,951 --> 00:37:14,952
[Demis] Yeah,
I feel safe here.
533
00:37:19,857 --> 00:37:21,791
Yes, go for it.
534
00:37:21,793 --> 00:37:23,325
[Demis] It's done it.
535
00:37:23,327 --> 00:37:24,492
It's gone in.
536
00:37:24,494 --> 00:37:27,895
Ooh, look at his
face, look at his face!
537
00:37:27,897 --> 00:37:29,696
That is not a confident face.
538
00:37:29,698 --> 00:37:32,632
He's pretty horrified by that.
539
00:37:32,634 --> 00:37:35,934
I can't believe
what I see right now.
540
00:37:36,835 --> 00:37:40,037
She thought, you know,
she's only a bit behind.
541
00:37:40,039 --> 00:37:42,639
It's made a very
aggressive move here.
542
00:37:42,641 --> 00:37:44,574
It make it very complicated.
543
00:37:44,576 --> 00:37:48,077
I think Lee Sedol, if he
doesn't respond mentally,
544
00:37:48,079 --> 00:37:49,912
then he can collapse.
545
00:38:05,761 --> 00:38:07,394
[Man] That's
the maximum number
546
00:38:07,396 --> 00:38:08,795
of moves ahead that AlphaGo
547
00:38:08,797 --> 00:38:11,898
is looking from the
current game position.
548
00:38:11,900 --> 00:38:14,100
It's typically over 50.
549
00:38:14,102 --> 00:38:15,935
It's often over 60.
550
00:38:17,070 --> 00:38:20,639
In the games we see often,
about move a hundred and fifty,
551
00:38:20,641 --> 00:38:22,073
AlphaGo goes for the kill.
552
00:38:22,075 --> 00:38:23,941
We're move a hundred
and fifteen now
553
00:38:23,943 --> 00:38:26,977
so we're going to
that critical point.
554
00:38:29,080 --> 00:38:33,650
We are all astonished, just
in the middle of the game,
555
00:38:33,652 --> 00:38:38,087
because AlphaGo seems to
be doing a much better job
556
00:38:38,089 --> 00:38:40,389
than we all thought it would.
557
00:38:40,391 --> 00:38:42,991
I thought that Lee
Sedol would be leading
558
00:38:42,993 --> 00:38:45,893
the game confidently,
but it turned out
559
00:38:45,895 --> 00:38:47,995
that he's struggling
at the moment.
560
00:38:47,997 --> 00:38:51,898
But I think eventually
he will prevail, I hope.
561
00:38:51,900 --> 00:38:57,970
I was more five to zero, but
now I'm not sure about that.
562
00:39:51,057 --> 00:39:53,224
Myungwan, it looks
like you've gotta count.
563
00:39:53,226 --> 00:39:56,961
- Yeah, right.
- What do you think?
564
00:39:56,963 --> 00:39:59,530
White won a lot at this
time, if you check that.
565
00:39:59,532 --> 00:40:01,698
If it's like this,
white has won by a lot.
566
00:40:14,011 --> 00:40:16,479
Wow, it's so shocking.
567
00:40:16,481 --> 00:40:19,882
I expected AlphaGo
to win only one game.
568
00:40:26,756 --> 00:40:27,655
Oh.
569
00:40:33,595 --> 00:40:35,996
[Aja] I can feel his pain.
570
00:40:37,164 --> 00:40:38,631
He couldn't believe, you know.
571
00:40:38,633 --> 00:40:39,965
He couldn't accept it.
572
00:40:39,967 --> 00:40:43,902
It takes time for him
to accept the outcome.
573
00:41:08,961 --> 00:41:12,663
[Aja] I think he resigned
in a very polite way.
574
00:41:12,665 --> 00:41:16,566
Lee Sedol, he's black,
but he put white stone.
575
00:41:23,840 --> 00:41:26,041
[Man] I think he resigned.
576
00:41:27,543 --> 00:41:28,709
Oh my gosh.
577
00:41:30,778 --> 00:41:32,211
Yeah, time has stopped.
578
00:41:32,213 --> 00:41:33,111
Wow.
579
00:41:33,946 --> 00:41:36,814
(upbeat music)
580
00:41:43,120 --> 00:41:45,154
[Woman] Congratulations.
581
00:41:47,190 --> 00:41:48,690
[David] I feel really good.
582
00:41:48,692 --> 00:41:51,692
I feel like I really
believe in AlphaGo.
583
00:41:53,094 --> 00:41:54,961
Of course, it's natural that
humans want humans to win.
584
00:41:54,963 --> 00:41:56,996
I mean I think that's
a natural response.
585
00:41:56,998 --> 00:42:00,132
But AlphaGo is human-created
and I think that's the ultimate
586
00:42:00,134 --> 00:42:02,868
sign of human ingenuity
and cleverness.
587
00:42:02,870 --> 00:42:05,837
Everything that AlphaGo
does, it does because a human
588
00:42:05,839 --> 00:42:08,973
has either created the
data that it learns from,
589
00:42:08,975 --> 00:42:11,842
created the learning algorithm
that learns from that data,
590
00:42:11,844 --> 00:42:14,211
created the search algorithm,
all of these things
591
00:42:14,213 --> 00:42:16,313
have come from humans.
592
00:42:16,315 --> 00:42:19,683
So, really, this is
a human endeavor.
593
00:42:27,624 --> 00:42:30,592
(cameras clicking)
594
00:42:34,096 --> 00:42:35,996
[Reporter] In the battle
between man versus machine,
595
00:42:35,998 --> 00:42:37,931
a computer just
came out the victor.
596
00:42:37,933 --> 00:42:40,633
[Reporter] DeepMind put its
computer program to the test
597
00:42:40,635 --> 00:42:43,636
against one of the brightest
minds in the world and won.
598
00:42:43,638 --> 00:42:45,938
[Reporter] AlphaGo beat
a professional player
599
00:42:45,940 --> 00:42:49,274
who has 18 Go World
Championships under his belt.
600
00:42:49,276 --> 00:42:51,242
The victory is
considered a breakthrough
601
00:42:51,244 --> 00:42:53,777
in artificial intelligence.
602
00:43:46,663 --> 00:43:49,131
[David] In research,
we normally work
603
00:43:49,133 --> 00:43:50,732
to produce an academic paper.
604
00:43:50,734 --> 00:43:52,734
It gets published and maybe
we get to talk about it
605
00:43:52,736 --> 00:43:55,269
in a conference, if we're lucky.
606
00:43:56,104 --> 00:43:58,171
This is not normal for research.
607
00:43:58,173 --> 00:44:01,107
In fact, I've never
experienced any media attention
608
00:44:01,109 --> 00:44:02,975
remotely close to this.
609
00:44:02,977 --> 00:44:04,910
So it's a special
moment for us all
610
00:44:04,912 --> 00:44:08,280
and we're just enjoying
it while it lasts.
611
00:44:12,451 --> 00:44:13,951
[Reporter] In a
match up between man
612
00:44:13,953 --> 00:44:15,752
and machine, who wins?
613
00:44:15,754 --> 00:44:17,687
Well, so far, it's the machine.
614
00:44:17,689 --> 00:44:21,090
In Seoul, South Korea,
the artificially
intelligent computer
615
00:44:21,092 --> 00:44:23,859
defeated the global
champion in the ancient
616
00:44:23,861 --> 00:44:26,228
Chinese board game Go.
617
00:44:26,230 --> 00:44:28,897
Lee Sedol lost the
first match up,
618
00:44:28,899 --> 00:44:30,665
but he's got four more chances.
619
00:44:46,114 --> 00:44:48,148
It is a bit strange
being on the front cover
620
00:44:48,150 --> 00:44:50,350
and everything as a
computer scientist.
621
00:44:50,352 --> 00:44:52,919
Nobody used to learn codes.
622
00:44:52,921 --> 00:44:54,854
Nobody really knows about it.
623
00:44:54,856 --> 00:44:56,822
Perhaps heard the
joke, how can you tell
624
00:44:56,824 --> 00:44:59,224
that a computer
scientist is an extrovert
625
00:44:59,226 --> 00:45:01,125
and not an introvert?
626
00:45:01,127 --> 00:45:03,026
If he's an extrovert,
he looks at your shoes
627
00:45:03,028 --> 00:45:07,162
when he's talking to you
instead of at his own.
628
00:45:07,164 --> 00:45:09,797
[Julian] Like if you
look at Aja, he avoids
629
00:45:09,799 --> 00:45:12,132
all the cameras like crazy.
630
00:45:12,134 --> 00:45:13,867
He's like, "The game
is finished,"
631
00:45:13,869 --> 00:45:17,403
and he's like, "I'll
go back in his room."
632
00:45:17,405 --> 00:45:21,406
And I think a lot of computer
scientists would be like that.
633
00:45:21,408 --> 00:45:23,441
We're more about doing our work
634
00:45:23,443 --> 00:45:26,744
than standing in the spotlight.
635
00:45:26,746 --> 00:45:29,413
[Announcer] Hello and
welcome to game two,
636
00:45:29,415 --> 00:45:34,184
round two in the Google
DeepMind challenge throw down
637
00:45:34,186 --> 00:45:36,319
between man and machine.
638
00:45:36,321 --> 00:45:40,222
Game one, the machine
takes down a man.
639
00:45:40,224 --> 00:45:41,823
Huge shock.
640
00:45:41,825 --> 00:45:43,391
Headlines around the world.
641
00:45:43,393 --> 00:45:45,159
[Man] The reactions
on the ground here
642
00:45:45,161 --> 00:45:47,494
from the folks in Korea
were just stunned.
643
00:45:47,496 --> 00:45:49,095
They estimate 60 million people
644
00:45:49,097 --> 00:45:51,163
watched the game in China alone.
645
00:45:51,165 --> 00:45:53,765
It's probably bringing up
to maybe 80 million people
646
00:45:53,767 --> 00:45:55,333
watched this game worldwide.
647
00:45:55,335 --> 00:45:57,201
It was just incredible
and, if anything,
648
00:45:57,203 --> 00:46:00,971
today is probably even
more of a madhouse.
649
00:46:00,973 --> 00:46:03,506
So Lee Sedol knows today,
he knows that this is just
650
00:46:03,508 --> 00:46:05,241
a really important game, right.
651
00:46:05,243 --> 00:46:06,375
He's gotta win.
652
00:46:25,327 --> 00:46:27,895
[Michael] Lee Sedol on white.
653
00:46:27,897 --> 00:46:31,265
I think probably looking
for a little payback.
654
00:46:31,267 --> 00:46:33,000
[Chris] My impression
is that maybe
655
00:46:33,002 --> 00:46:36,903
he underestimated AlphaGo and
he's gonna change his tactics.
656
00:46:41,308 --> 00:46:42,207
Yeah.
657
00:46:44,410 --> 00:46:46,177
He's playing at half
his speed actually.
658
00:46:59,390 --> 00:47:01,257
[Michael] Well, if I
say anything about AlphaGo
659
00:47:01,259 --> 00:47:04,360
that is not normal, is maybe
the way it handles a game
660
00:47:04,362 --> 00:47:06,395
when it thinks its ahead.
661
00:47:06,397 --> 00:47:07,495
We're actually
gonna have a visit
662
00:47:07,497 --> 00:47:10,265
from one of the team and
we'll talk about exactly
663
00:47:10,267 --> 00:47:11,899
that point from the inside.
664
00:47:11,901 --> 00:47:13,233
Thanks so much for coming by.
665
00:47:13,235 --> 00:47:14,333
I really appreciate it.
666
00:47:14,335 --> 00:47:19,238
Can you sort of share a bit of
what is going on in AlphaGo.
667
00:47:19,240 --> 00:47:22,574
So AlphaGo has these
three main components.
668
00:47:22,576 --> 00:47:25,577
There's the Policy
Network which was trained
669
00:47:25,579 --> 00:47:30,147
on high level games to
imitate those players.
670
00:47:30,149 --> 00:47:32,082
And then we have a
second component,
671
00:47:32,084 --> 00:47:35,251
we call this the Value
Net and it can evaluate
672
00:47:35,253 --> 00:47:38,220
the board position and say
what is the probability
673
00:47:38,222 --> 00:47:41,190
of winning in this
particular position.
674
00:47:41,192 --> 00:47:44,059
And the third component
is the Tree Search
675
00:47:44,061 --> 00:47:47,729
where it would look through
different variations of the game
676
00:47:47,731 --> 00:47:52,166
and try to figure out what
will happen in the future.
677
00:47:53,668 --> 00:47:56,403
So, if we now take a
position like this,
678
00:47:56,405 --> 00:48:00,173
first the Policy Network
will scan the position
679
00:48:00,175 --> 00:48:04,343
and come up with what would be
the interesting spots to play
680
00:48:05,445 --> 00:48:08,246
and it builds up a
tree of variations.
681
00:48:08,248 --> 00:48:12,616
And then employs this Value
Net that tells it how promising
682
00:48:12,618 --> 00:48:16,552
is the outcome of this
particular variation.
683
00:48:18,521 --> 00:48:22,556
So AlphaGo tries to maximize
its probability of winning,
684
00:48:23,658 --> 00:48:26,126
but it doesn't care at
all about the margin
685
00:48:26,128 --> 00:48:27,560
by which it wins.
686
00:48:27,562 --> 00:48:29,461
Okay, so when you
see a slow-looking move
687
00:48:29,463 --> 00:48:31,429
that's maybe an
indication that AlphaGo
688
00:48:31,431 --> 00:48:33,464
thinks it has a
good chance to win.
689
00:48:33,466 --> 00:48:36,300
Yeah, that is a
little giveaway.
690
00:48:36,302 --> 00:48:38,068
A little tell, we're
looking for a tell.
691
00:49:08,131 --> 00:49:10,098
[Man] Oh, looks
like Lee is taking
692
00:49:10,100 --> 00:49:12,166
a little bit of a break.
693
00:49:14,269 --> 00:49:16,536
(soft music)
694
00:49:45,498 --> 00:49:48,466
(speaking in foreign language)
695
00:49:51,837 --> 00:49:53,603
The value, uh...
696
00:49:55,672 --> 00:49:58,640
That's a very surprising move.
697
00:49:58,642 --> 00:50:01,776
[Chris] I thought
it was a mistake.
698
00:50:21,562 --> 00:50:25,631
So coming on top of a fourth
line zone is really unusual.
699
00:50:25,633 --> 00:50:27,332
[Chris] Yeah, that's
an exciting move.
700
00:50:27,334 --> 00:50:30,501
I think we're seeing
an original move here.
701
00:50:30,503 --> 00:50:34,538
That's the kind of move
that you play Go for.
702
00:50:36,541 --> 00:50:37,607
[Man] Hey.
703
00:50:39,643 --> 00:50:41,310
Interesting stuff.
704
00:50:41,312 --> 00:50:43,712
This fifth line
shoulder hit is uh...
705
00:50:43,714 --> 00:50:46,314
[Michael] I wasn't
expecting that.
706
00:50:46,316 --> 00:50:47,515
I don't really
know if it's a good
707
00:50:47,517 --> 00:50:49,283
or bad move at this point.
708
00:50:49,285 --> 00:50:52,419
[David] The professional
commentators almost unanimously
709
00:50:52,421 --> 00:50:54,187
said that not a
single human player
710
00:50:54,189 --> 00:50:56,489
would have chosen move 37.
711
00:50:56,491 --> 00:50:58,657
So I actually had a
poke around in AlphaGo
712
00:50:58,659 --> 00:51:00,692
to see what AlphaGo thought.
713
00:51:00,694 --> 00:51:03,895
And AlphaGo actually agreed
with that assessment.
714
00:51:03,897 --> 00:51:07,565
AlphaGo said it was a
one in 10,000 probability
715
00:51:07,567 --> 00:51:11,135
that move 37 would have been
played by a human player.
716
00:51:11,137 --> 00:51:13,704
So it knew that this was
an extremely unlikely move.
717
00:51:13,706 --> 00:51:17,474
It went beyond its human
guide and it came up
718
00:51:17,476 --> 00:51:20,777
with something new and
creative and different.
719
00:51:20,779 --> 00:51:23,613
I am very much
watching the game
720
00:51:23,615 --> 00:51:25,781
through these commentators.
721
00:51:25,783 --> 00:51:27,716
That's the way it works,
so when they're confused
722
00:51:27,718 --> 00:51:29,350
I'm certainly confused.
723
00:51:29,352 --> 00:51:31,251
At the same time, I'm
latching onto the fact
724
00:51:31,253 --> 00:51:32,752
that they are confused, right.
725
00:51:32,754 --> 00:51:34,787
That is an interesting moment.
726
00:51:34,789 --> 00:51:36,221
When everyone else is confused,
727
00:51:36,223 --> 00:51:39,324
who's not confused
besides the machine?
728
00:51:51,870 --> 00:51:54,705
[Chris] He's
back, Lee is back.
729
00:51:58,876 --> 00:52:01,811
(dramatic music)
730
00:53:07,576 --> 00:53:08,943
Go is like geopolitics.
731
00:53:08,945 --> 00:53:10,811
Like something small
that happens here
732
00:53:10,813 --> 00:53:14,780
can have a ripple effect
hours down the road
733
00:53:14,782 --> 00:53:16,815
in a different
part of the board.
734
00:53:16,817 --> 00:53:20,852
The game kind of turned on
its axis at that moment.
735
00:53:51,916 --> 00:53:54,284
[Michael] This is a
tough game for Lee Sedol.
736
00:53:54,286 --> 00:53:58,487
AlphaGo is just not letting
Lee Sedol do what he wants.
737
00:53:58,489 --> 00:54:00,322
Black has almost 60 points.
738
00:54:00,324 --> 00:54:01,556
That's a lot.
739
00:54:01,558 --> 00:54:04,825
[Andrew] That's
not a good sign.
740
00:54:04,827 --> 00:54:08,694
Lee Sedol just slapped himself
on the side of the head.
741
00:54:08,696 --> 00:54:10,829
[Myungwan] Oh wow.
742
00:54:10,831 --> 00:54:13,832
I think black's
ahead at this point.
743
00:54:13,834 --> 00:54:14,766
It's looking good, ain't it?
744
00:54:14,768 --> 00:54:17,535
We're on that steady path now.
745
00:54:33,751 --> 00:54:36,018
(soft music)
746
00:54:48,431 --> 00:54:50,365
Oh, he resigned.
747
00:54:50,367 --> 00:54:53,935
It looks like Lee Sedol
has just resigned.
748
00:55:21,396 --> 00:55:25,632
There was this heavy
sadness over that whole floor.
749
00:55:25,634 --> 00:55:26,766
You could feel it
during the game.
750
00:55:26,768 --> 00:55:28,634
I felt it during the game.
751
00:55:28,636 --> 00:55:31,436
And I'm leaving the
commentary room to go
752
00:55:31,438 --> 00:55:33,938
to the press conference and
I was stopped by someone,
753
00:55:33,940 --> 00:55:35,606
another technology reporter.
754
00:55:35,608 --> 00:55:38,075
At first, all he wanted to
talk about was the technology
755
00:55:38,077 --> 00:55:39,543
and how great this was.
756
00:55:39,545 --> 00:55:41,978
But then even he kind of
slipped into this moment
757
00:55:41,980 --> 00:55:45,648
of melancholy where
he was upset as well.
758
00:55:52,889 --> 00:55:54,656
I am quite speechless.
759
00:55:54,658 --> 00:55:58,092
I admit that it was a very
clear loss on my part.
760
00:55:58,094 --> 00:55:59,960
From the very
beginning of the game,
761
00:55:59,962 --> 00:56:01,962
there was not a moment
in time that I felt
762
00:56:01,964 --> 00:56:04,464
that I was leading the game.
763
00:56:04,466 --> 00:56:08,034
You feel elated and you
feel a little bit scared.
764
00:56:08,036 --> 00:56:11,103
There is something, I
think, frightening to people
765
00:56:11,105 --> 00:56:14,039
about a machine that
learns on its own.
766
00:56:14,041 --> 00:56:17,809
For us, AlphaGo was obviously
just some computer program,
767
00:56:17,811 --> 00:56:20,678
but looking at the
commentary on the internet,
768
00:56:20,680 --> 00:56:22,946
I already saw the
commentators call AlphaGo
769
00:56:22,948 --> 00:56:26,983
like he and she during the
games, completely unconsciously.
770
00:56:28,986 --> 00:56:31,520
AlphaGo is really a very,
very simple program.
771
00:56:31,522 --> 00:56:34,055
It's not anywhere close
to full AI and we already
772
00:56:34,057 --> 00:56:38,492
see that happening, so I
found that very interesting.
773
00:56:41,562 --> 00:56:43,996
The tendency to
anthropomorphize AI systems
774
00:56:43,998 --> 00:56:47,666
is one of the big obstacles
in the way of actually trying
775
00:56:47,668 --> 00:56:51,102
to understand how AI might
impact the world in the future.
776
00:56:51,104 --> 00:56:53,571
For example, the conversation
is about what could go wrong,
777
00:56:53,573 --> 00:56:55,573
like what the risks
are and invariably
778
00:56:55,575 --> 00:56:57,007
you see this Terminator picture.
779
00:56:57,009 --> 00:56:59,843
Every single time, there are
these red, glowing eyes, right?
780
00:56:59,845 --> 00:57:01,778
We're really closer to a smart
781
00:57:01,780 --> 00:57:03,946
washing machine than Terminator.
782
00:57:03,948 --> 00:57:09,184
If you look at today's AI,
we are really very nascent.
783
00:57:09,952 --> 00:57:13,987
I'm extremely excited and
passionate about AI's potential,
784
00:57:15,155 --> 00:57:19,157
but AI is still very
limited in its power.
785
00:57:19,159 --> 00:57:21,993
I think that people
are right to think
786
00:57:21,995 --> 00:57:24,962
that there is a danger that,
as we continue to improve
787
00:57:24,964 --> 00:57:28,165
these systems that we might
misstep that threshold
788
00:57:28,167 --> 00:57:31,034
where we do cross
over into danger.
789
00:57:31,036 --> 00:57:32,935
But the good news is
there are already people
790
00:57:32,937 --> 00:57:34,469
thinking about those dangers.
791
00:57:34,471 --> 00:57:35,803
You know, there's
a lot of talk now
792
00:57:35,805 --> 00:57:37,203
and we're leading the
discussion on this,
793
00:57:37,205 --> 00:57:39,573
that maybe there should be
a kind of cross industry,
794
00:57:39,575 --> 00:57:41,975
best practices working
group or something
795
00:57:41,977 --> 00:57:44,811
where the leaders of
the research teams
796
00:57:44,813 --> 00:57:47,046
in those organizations,
you know, the big ones
797
00:57:47,048 --> 00:57:50,482
that are working on AI, IBM,
Microsoft, so on, come together
798
00:57:50,484 --> 00:57:54,252
and make sure that AI is used
ethically and responsibly.
799
00:57:54,254 --> 00:57:57,555
I think what is important is
that there is this community
800
00:57:57,557 --> 00:58:01,658
of people who are leading
the cutting edge of AI,
801
00:58:03,027 --> 00:58:05,795
who are interacting
with academics and
already are thinking
802
00:58:05,797 --> 00:58:09,598
about the longterm
and how we can ensure
803
00:58:09,600 --> 00:58:12,033
that innovation is
responsible as the power
804
00:58:12,035 --> 00:58:15,102
of these machines
gets even greater.
805
00:58:16,037 --> 00:58:18,071
This is it, folks.
806
00:58:18,073 --> 00:58:20,206
Day three, game three.
807
00:58:20,208 --> 00:58:24,142
Lee Sedol, Go master,
back to the wall.
808
00:58:24,144 --> 00:58:26,544
He's down two-zero.
809
00:58:26,546 --> 00:58:29,413
He's got to win today
to keep hope alive.
810
00:58:44,028 --> 00:58:47,963
I heard that four
pros went to visit him
811
00:58:47,965 --> 00:58:50,799
to console him into
a review after--
812
00:58:50,801 --> 00:58:51,633
Console him?
813
00:58:51,635 --> 00:58:53,534
You think he's upset?
814
00:58:53,536 --> 00:58:54,935
I mean Lee Sedol is upset.
815
00:58:54,937 --> 00:58:56,603
Yeah.
816
00:58:56,605 --> 00:58:59,105
In the beginning, there
was a forceful fight.
817
00:58:59,107 --> 00:59:03,809
And AlphaGo play very well, so
he secure a very early lead.
818
00:59:03,811 --> 00:59:07,179
From (mumbles) the window
was very high already.
819
00:59:07,181 --> 00:59:10,949
It was climbing towards
a hundred percent.
820
00:59:55,761 --> 00:59:57,895
It's looking good for us.
821
00:59:57,897 --> 01:00:00,764
That black ruby is huge
and it's got nowhere to go
822
01:00:00,766 --> 01:00:03,599
and it's gonna be
running around.
823
01:00:04,667 --> 01:00:07,135
(soft music)
824
01:00:12,175 --> 01:00:15,243
[Commentator] I don't know
how to describe this situation.
825
01:00:15,245 --> 01:00:17,979
If I were black, I will resign.
826
01:00:17,981 --> 01:00:21,282
He should admit that we
are facing the strongest
827
01:00:21,284 --> 01:00:23,984
existence ever in the
Go history.
828
01:00:25,086 --> 01:00:26,853
There's no point in
playing out the end game
829
01:00:26,855 --> 01:00:29,221
when you're gonna lose, right.
830
01:00:32,091 --> 01:00:34,258
[Chris] Even if black can
live there, oh, he resigned.
831
01:00:34,260 --> 01:00:35,259
[Michael] It's
done, it's done.
832
01:00:35,261 --> 01:00:37,060
- Okay.
- Wow.
833
01:00:37,062 --> 01:00:37,960
Wow.
834
01:00:39,329 --> 01:00:42,364
You saw history
made here tonight.
835
01:00:42,366 --> 01:00:44,366
[Chris] AlphaGo has won
again, three straight wins.
836
01:00:44,368 --> 01:00:46,801
[Michael] Three straight
wins, has won the match.
837
01:01:09,957 --> 01:01:11,757
[Demis] You know, certainly,
I feel a bit ambivalent
838
01:01:11,759 --> 01:01:13,425
about it given
I'm a games player
839
01:01:13,427 --> 01:01:16,394
and Go is the pinnacle
of board games.
840
01:01:16,396 --> 01:01:17,828
But I really like the statement
841
01:01:17,830 --> 01:01:20,363
one of the top Chinese
professionals said,
842
01:01:20,365 --> 01:01:24,066
"If AlphaGo wins, maybe
we'll really start
843
01:01:24,068 --> 01:01:27,802
to get to see what
this game is about."
844
01:01:27,804 --> 01:01:29,770
[Maddy] I couldn't celebrate.
845
01:01:29,772 --> 01:01:32,305
It was fantastic
that we had won,
846
01:01:32,307 --> 01:01:36,208
but there was such a big
part of me that saw this man
847
01:01:36,210 --> 01:01:39,878
trying so hard and
being so disappointed.
848
01:03:58,416 --> 01:04:01,184
(dramatic music)
849
01:04:08,025 --> 01:04:10,026
[Cade] You can see
that he was more relaxed
850
01:04:10,028 --> 01:04:12,395
after he had lost
three games in a row.
851
01:04:12,397 --> 01:04:14,697
That said, the stakes
were still high.
852
01:04:14,699 --> 01:04:18,534
You know, in the end,
it isn't about pride.
853
01:04:23,605 --> 01:04:27,607
[Chris] Can Lee Sedol
find AlphaGo's weakness?
854
01:04:27,609 --> 01:04:29,675
Is there, in fact, a weakness?
855
01:04:29,677 --> 01:04:31,977
I was thinking I'd
just pull the plug.
856
01:04:31,979 --> 01:04:33,178
- You'd just pull the plug?
- Yeah.
857
01:04:33,180 --> 01:04:35,346
Everyone's still
cheering for Lee Sedol
858
01:04:35,348 --> 01:04:38,415
and, yeah, it's not
going very well.
859
01:04:49,993 --> 01:04:53,228
It feels pretty good
for black at this point.
860
01:04:53,230 --> 01:04:54,862
It feels pretty
good for black, yes.
861
01:05:37,471 --> 01:05:39,405
[Michael] It's
developing into a very,
862
01:05:39,407 --> 01:05:41,073
very dangerous fight.
863
01:05:41,075 --> 01:05:43,508
This is really Lee
Sedol's type of game.
864
01:05:43,510 --> 01:05:45,343
He likes this kind of fight.
865
01:05:45,345 --> 01:05:47,511
White has to find something
inside black's territory.
866
01:05:47,513 --> 01:05:49,446
[Commentator] I think
he is already planning
867
01:05:49,448 --> 01:05:50,513
on trying something.
868
01:05:56,186 --> 01:05:57,452
Yes, yes.
869
01:05:57,454 --> 01:05:59,520
There is a little
potential there.
870
01:05:59,522 --> 01:06:02,089
And I think maybe he's
gonna try to do something.
871
01:06:02,091 --> 01:06:03,923
[Andrew] Lee Sedol magic.
872
01:06:06,459 --> 01:06:08,526
Lee Sedol, he's
running short on time,
873
01:06:08,528 --> 01:06:11,262
but he's gonna have to
use up all his time.
874
01:06:11,264 --> 01:06:13,497
[Commentator] He just burned
like seven or eight minutes
875
01:06:13,499 --> 01:06:14,931
just on this move already.
876
01:06:18,035 --> 01:06:19,502
We can't find anything.
877
01:06:23,273 --> 01:06:25,140
[Chris] What is
Lee Sedol up to here?
878
01:06:25,142 --> 01:06:26,808
[Michael] Yeah, he's
really concentrating.
879
01:06:26,810 --> 01:06:28,509
[Chris] He really
is, look at that.
880
01:06:52,667 --> 01:06:55,301
[Chris] This is the
hinge of the game.
881
01:06:55,303 --> 01:06:57,169
Oh, look at that move.
882
01:06:57,171 --> 01:06:58,703
That's an exciting move.
883
01:06:58,705 --> 01:07:01,205
- Look.
- Oh, he found the wedge.
884
01:07:01,207 --> 01:07:02,406
[Chris] Whoa.
885
01:07:02,408 --> 01:07:04,641
[Michael] It's gonna
change the equation
886
01:07:04,643 --> 01:07:06,542
because now black cannot escape.
887
01:07:06,544 --> 01:07:09,577
That would be so
cool if that works.
888
01:07:12,380 --> 01:07:13,279
Ooh!
889
01:07:15,415 --> 01:07:16,782
[Commentator]
AlphaGo has just played
890
01:07:16,784 --> 01:07:19,251
something maybe unusual.
891
01:07:19,253 --> 01:07:20,585
[Michael] You know,
I'm not actually sure
892
01:07:20,587 --> 01:07:22,720
what AlphaGo is
trying to do here.
893
01:07:22,722 --> 01:07:24,154
[Chris] What's that about?
894
01:07:24,156 --> 01:07:25,588
[Michael] I don't
really understand it.
895
01:07:25,590 --> 01:07:26,322
Well, well.
896
01:07:36,832 --> 01:07:40,267
This could be that it actually
can't find a way through.
897
01:07:40,269 --> 01:07:43,270
I think this is it's looked
far enough ahead to see
898
01:07:43,272 --> 01:07:45,338
that it doesn't work and
now maybe it's on tilt?
899
01:07:45,340 --> 01:07:46,672
I don't know.
900
01:07:46,674 --> 01:07:48,340
There it comes.
901
01:07:50,109 --> 01:07:53,511
It's like it's
fallen off a cliff.
902
01:07:53,513 --> 01:07:55,613
Yeah, it's made a mistake.
903
01:07:55,615 --> 01:07:57,848
Did anything strange
happen in the...
904
01:07:57,850 --> 01:07:59,516
[Man] No, it
all looked normal.
905
01:07:59,518 --> 01:08:02,685
Well, we can definitely
say, well, there's a weakness.
906
01:08:02,687 --> 01:08:05,654
Well, we definitely
say it's a mistake.
907
01:08:05,656 --> 01:08:09,391
[David] I felt this
mixture of a sinking feeling
908
01:08:09,393 --> 01:08:11,559
in my stomach where I
was wondering if AlphaGo
909
01:08:11,561 --> 01:08:13,894
is becoming delusional in this
situation where I could see
910
01:08:13,896 --> 01:08:16,296
that it was starting
to play strangely.
911
01:08:16,298 --> 01:08:18,197
And, at the same time,
relief that Lee Sedol,
912
01:08:18,199 --> 01:08:21,767
that he was actually
in with a chance now.
913
01:08:26,873 --> 01:08:31,576
I knew after move 78,
after like 10 or 20 moves,
914
01:08:31,578 --> 01:08:34,178
I saw AlphaGo strange moves.
915
01:08:35,380 --> 01:08:37,614
I know AlphaGo
somehow became crazy,
916
01:08:37,616 --> 01:08:39,415
but I didn't realize why.
917
01:08:39,417 --> 01:08:40,315
Whoa!
918
01:08:41,150 --> 01:08:43,317
We slipped from 95 ahead.
919
01:08:44,419 --> 01:08:46,553
At the point, where
we made the mistake?
920
01:08:46,555 --> 01:08:48,388
I think that
something went wrong.
921
01:08:48,390 --> 01:08:51,357
That's the longest we've
searched this entire game.
922
01:08:51,359 --> 01:08:56,227
I think it's searched so
deeply it's confused itself.
923
01:08:56,229 --> 01:08:57,661
[Michael] I do get the
impression that AlphaGo
924
01:08:57,663 --> 01:08:59,829
is sort of gone
off on a tangent.
925
01:08:59,831 --> 01:09:01,397
What are you doing now?
926
01:09:01,399 --> 01:09:02,731
Maybe it has a master plan?
927
01:09:02,733 --> 01:09:05,600
No, it doesn't even
think it has, does it?
928
01:09:05,602 --> 01:09:06,934
So it knows it's made a mistake.
929
01:09:06,936 --> 01:09:09,603
It starts evaluating
it the other way.
930
01:09:09,605 --> 01:09:11,371
Look, look, Lee's so confused.
931
01:09:11,373 --> 01:09:12,372
He's like what is it doing?
932
01:09:12,374 --> 01:09:13,673
That's not a I'm
scared confused.
933
01:09:13,675 --> 01:09:15,074
That's a what is it doing?
934
01:09:16,609 --> 01:09:18,576
You know, you asked
if it was a bug.
935
01:09:18,578 --> 01:09:22,746
I've said before that if
DeepMind has figured out
936
01:09:24,248 --> 01:09:26,916
how to write code
that doesn't have bugs
937
01:09:26,918 --> 01:09:29,551
that is a bigger news
story than AlphaGo.
938
01:09:29,553 --> 01:09:31,586
Oh, you're kidding me.
939
01:09:31,588 --> 01:09:34,521
This next move we're gonna play,
940
01:09:35,789 --> 01:09:37,723
I think they're gonna laugh.
941
01:09:37,725 --> 01:09:39,791
Everybody's gonna laugh.
942
01:09:47,365 --> 01:09:48,431
[Commentator] Oh, oh, oh!
943
01:09:54,471 --> 01:09:55,704
[Man] I don't really know
944
01:09:55,706 --> 01:09:57,939
what AlphaGo is
trying to do here.
945
01:09:57,941 --> 01:09:59,707
That's the
understatement of the year.
946
01:10:01,643 --> 01:10:02,843
[Andrew] No, no,
that's the move.
947
01:10:02,845 --> 01:10:05,645
Aja Huang makes no misclicks.
948
01:10:05,647 --> 01:10:07,713
Lee Sedol is very confused.
949
01:10:07,715 --> 01:10:09,648
These are not human moves.
950
01:10:09,650 --> 01:10:12,884
This move, also,
sort of inexplicable.
951
01:10:12,886 --> 01:10:16,687
[Chris] I mean you can
clearly call those the saves.
952
01:10:16,689 --> 01:10:17,888
[Michael] Yes, of course.
953
01:10:17,890 --> 01:10:19,756
But it's the first
time in the four matches
954
01:10:19,758 --> 01:10:21,758
that we've seen moves like that.
955
01:10:21,760 --> 01:10:24,460
Oh, the value
dropped even more.
956
01:10:24,462 --> 01:10:25,794
That's weird.
957
01:10:32,968 --> 01:10:34,969
[Andrew] Come on, Lee Sedol.
958
01:10:34,971 --> 01:10:36,804
This unbelievable.
959
01:10:36,806 --> 01:10:37,704
All right!
960
01:10:37,706 --> 01:10:40,707
I was so confident
that this black mire
961
01:10:40,709 --> 01:10:42,775
would just be
consolidated by black
962
01:10:42,777 --> 01:10:43,775
and there's nothing there.
963
01:10:43,777 --> 01:10:47,279
And, somehow, he's just
erased it all, like it's gone.
964
01:10:47,281 --> 01:10:48,713
So he's found his weakness?
965
01:10:48,715 --> 01:10:51,148
That wedge move
probably surprised it.
966
01:10:52,650 --> 01:10:54,484
AlphaGo seemed to
have such a good game
967
01:10:54,486 --> 01:10:57,687
and then this whole
sequence in the center
968
01:10:57,689 --> 01:10:58,821
sort of changed that.
969
01:10:58,823 --> 01:11:00,889
He pulls off a miracle.
970
01:11:00,891 --> 01:11:02,790
He managed to make
it so complicated
971
01:11:02,792 --> 01:11:06,360
that the artificial intelligence
doesn't evaluate it.
972
01:11:06,362 --> 01:11:08,830
I think it looks like Aja
Huang maybe sitting there
973
01:11:08,832 --> 01:11:11,365
also knows that
the game is over.
974
01:11:15,936 --> 01:11:17,802
[Andrew] Now, I haven't
seen him smile yet.
975
01:11:20,105 --> 01:11:21,738
[Andrew] He's so serious.
976
01:11:21,740 --> 01:11:23,706
He wants to be careful.
977
01:11:40,956 --> 01:11:43,757
(dramatic music)
978
01:11:47,828 --> 01:11:51,130
[Man] There you
go, AlphaGo resigned.
979
01:11:52,866 --> 01:11:54,800
Looks like AlphaGo
has resigned.
980
01:11:54,802 --> 01:11:56,568
[Chris] Wow.
981
01:11:56,570 --> 01:11:58,636
The most amazing game,
982
01:12:00,005 --> 01:12:01,438
I'm almost gonna tear up,
983
01:12:01,440 --> 01:12:04,974
was game four where he
comes back and wins.
984
01:12:07,610 --> 01:12:10,411
(crowd cheering)
985
01:12:54,188 --> 01:12:55,888
I heard from so many people
986
01:12:55,890 --> 01:12:59,590
saying they were running
out in the street.
987
01:12:59,592 --> 01:13:01,158
They were so happy.
988
01:13:01,160 --> 01:13:02,993
They were chanting,
they were celebrating.
989
01:13:02,995 --> 01:13:07,197
Especially after a
zero-three down, at the time,
990
01:13:07,199 --> 01:13:11,534
seems to be hopeless that the
end of the world is coming,
991
01:13:11,536 --> 01:13:13,002
but we see the light.
992
01:13:13,004 --> 01:13:18,006
Usually, I'm happy when I
win not like my colleague wins.
993
01:13:18,974 --> 01:13:22,076
But this time it
felt like my win.
994
01:13:37,091 --> 01:13:39,959
(upbeat music)
995
01:13:46,899 --> 01:13:49,734
(crowd clapping)
996
01:14:34,178 --> 01:14:37,680
My question is
about number 78 move,
997
01:14:37,682 --> 01:14:41,083
Chinese top Go player
(mumbles) it was a God play,
998
01:14:41,085 --> 01:14:43,018
what were you thinking
when you made that play?
999
01:14:43,020 --> 01:14:43,985
Thank you.
1000
01:14:59,667 --> 01:15:01,134
[Demis] It does leave
me a little bit in awe
1001
01:15:01,136 --> 01:15:02,935
of the human brain's
power, in particular,
1002
01:15:02,937 --> 01:15:06,338
Lee's amazing ability to
cause AlphaGo problems
1003
01:15:06,340 --> 01:15:09,140
and find something
seemingly out of nothing.
1004
01:15:09,142 --> 01:15:12,243
And so we really want to
understand what had happened.
1005
01:16:05,630 --> 01:16:07,297
(upbeat music)
1006
01:16:07,299 --> 01:16:09,832
[Announcer] Welcome
back to the Four Seasons.
1007
01:16:09,834 --> 01:16:12,801
World champion, Lee
Sedol, went looking
1008
01:16:12,803 --> 01:16:17,172
for AlphaGo's weakness in
game four and he found it.
1009
01:16:17,174 --> 01:16:20,108
Today, last round,
he's looking to see
1010
01:16:20,110 --> 01:16:21,809
if he can repeat that.
1011
01:16:21,811 --> 01:16:22,809
We'll see what happens.
1012
01:16:22,811 --> 01:16:24,878
[Commentator] The place
is a madhouse downstairs.
1013
01:16:24,880 --> 01:16:27,714
There may be as many, if nor
more, journalists here today
1014
01:16:27,716 --> 01:16:30,316
than there were for game one.
1015
01:16:30,318 --> 01:16:33,118
[Maddy] We were really
excited for the fifth match
1016
01:16:33,120 --> 01:16:34,352
to see what would happen.
1017
01:16:34,354 --> 01:16:36,087
Was this going to
be a three-two thing
1018
01:16:36,089 --> 01:16:38,089
or was it going to
be a four-one thing?
1019
01:16:38,091 --> 01:16:39,390
And, you know, there's
a different message
1020
01:16:39,392 --> 01:16:41,225
with both of those.
1021
01:17:08,786 --> 01:17:12,021
You weren't crazy about
the timing on this move.
1022
01:17:12,023 --> 01:17:13,222
No, yeah.
1023
01:17:13,224 --> 01:17:15,724
And now, you don't
approve of this?
1024
01:17:15,726 --> 01:17:18,193
Yeah, I'm sort of
thinking that maybe AlphaGo
1025
01:17:18,195 --> 01:17:20,261
hasn't recovered
from game four yet.
1026
01:17:24,699 --> 01:17:25,432
Oh no, I hope it doesn't...
1027
01:17:25,434 --> 01:17:28,201
Oh no, it needs to play the...
1028
01:17:37,977 --> 01:17:40,845
[Chris] Are we seeing
another short circuit
1029
01:17:40,847 --> 01:17:42,913
or is there
something, what's a--
1030
01:17:42,915 --> 01:17:45,916
[Commentator] I think it
could be a kind of a misreading.
1031
01:17:45,918 --> 01:17:47,984
[Michael] And were
you pretty comfortable
1032
01:17:47,986 --> 01:17:48,884
with saying that--
1033
01:17:48,886 --> 01:17:50,886
[Chris] That it's
looking good for Lee Sedol?
1034
01:17:50,888 --> 01:17:53,354
[Michael] Good for Lee Sedol.
1035
01:17:55,223 --> 01:17:56,422
Why is it playing
in there for?
1036
01:17:56,424 --> 01:17:59,159
There's no reason for white
to be playing that move.
1037
01:17:59,161 --> 01:18:01,194
It's a bad move
and, in some cases,
1038
01:18:01,196 --> 01:18:03,829
it's going to lose a point too.
1039
01:18:12,872 --> 01:18:15,106
The whole game we
thought that AlphaGo was wrong
1040
01:18:15,108 --> 01:18:17,274
about the board position
and we were super worried
1041
01:18:17,276 --> 01:18:19,175
that it's gonna play garbage.
1042
01:18:19,177 --> 01:18:21,210
It's going to be like losing
in a very embarrassing way.
1043
01:18:21,212 --> 01:18:23,445
And this continued
for the whole game.
1044
01:18:29,184 --> 01:18:30,951
Well, that we don't know,
but we're not good enough
1045
01:18:30,953 --> 01:18:32,018
Go players to know that, right?
1046
01:18:32,020 --> 01:18:32,818
Yeah.
1047
01:18:32,820 --> 01:18:35,354
As it turned out, none
of us know Go well enough
1048
01:18:35,356 --> 01:18:37,356
to accurately judge
what AlphaGo is doing.
1049
01:18:39,292 --> 01:18:42,260
This one looks like
white is winning.
1050
01:18:42,262 --> 01:18:43,861
Aah!
1051
01:18:43,863 --> 01:18:46,930
We all say some of
AlphaGo's moves are so weird
1052
01:18:46,932 --> 01:18:49,465
and strange and maybe mistakes.
1053
01:18:49,467 --> 01:18:52,234
But, after a game is finished,
1054
01:18:53,236 --> 01:18:57,172
we have to doubt
ourselves, our judgment.
1055
01:18:57,174 --> 01:19:00,975
AlphaGo making another
kind of nonsensical throw in.
1056
01:19:00,977 --> 01:19:02,375
We're not really sure
what that's about.
1057
01:19:02,377 --> 01:19:04,912
This is what 10 or maybe
11 dan play looks like.
1058
01:19:04,914 --> 01:19:07,514
It looks weird and we
don't quite understand it.
1059
01:19:07,516 --> 01:19:11,050
I think it is
important to study more
1060
01:19:11,052 --> 01:19:14,553
about AlphaGo's
mistake-like moves.
1061
01:19:14,555 --> 01:19:18,856
And maybe we can adjust
our knowledge of AlphaGo.
1062
01:19:18,858 --> 01:19:20,357
To me the most amazing
thing to come out
1063
01:19:20,359 --> 01:19:23,193
of my understanding of Go,
as a result of watching
1064
01:19:23,195 --> 01:19:26,996
AlphaGo play, are the
infamous slack moves.
1065
01:19:26,998 --> 01:19:29,231
Well, there's something
strange about the way
1066
01:19:29,233 --> 01:19:31,032
it's playing because
it's playing some moves
1067
01:19:31,034 --> 01:19:32,967
that are not really necessary.
1068
01:19:32,969 --> 01:19:34,201
Right.
1069
01:19:34,203 --> 01:19:37,103
A slack move is a
move that looks lazy.
1070
01:19:37,105 --> 01:19:39,171
You can see these
other better moves
1071
01:19:39,173 --> 01:19:40,872
and AlphaGo is rejecting them.
1072
01:19:40,874 --> 01:19:44,141
But what I think
AlphaGo is teaching us
1073
01:19:44,143 --> 01:19:47,444
is that we've been
using score as a proxy
1074
01:19:48,345 --> 01:19:50,245
for chance of winning.
1075
01:19:50,247 --> 01:19:53,214
So the bigger my
margin of territory,
1076
01:19:53,216 --> 01:19:55,382
the more confident I
am that I'm gonna win.
1077
01:19:55,384 --> 01:19:57,283
And AlphaGo is
saying no, no, no.
1078
01:19:57,285 --> 01:19:59,118
It shouldn't matter
how much you win by.
1079
01:19:59,120 --> 01:20:01,220
You only need to win
by a single point.
1080
01:20:01,222 --> 01:20:03,388
Why should I be seizing
all this extra territory
1081
01:20:03,390 --> 01:20:04,588
when I don't need it.
1082
01:20:04,590 --> 01:20:06,924
The lessons that
AlphaGo is teaching us
1083
01:20:06,926 --> 01:20:10,827
are going to influence
how Go is played
1084
01:20:10,829 --> 01:20:12,728
for the next thousand years.
1085
01:20:16,199 --> 01:20:18,266
By how much are we talking?
1086
01:20:18,268 --> 01:20:19,333
Two points?
One and a half.
1087
01:20:19,335 --> 01:20:20,400
One and a half points.
1088
01:20:23,237 --> 01:20:24,503
Of course, Go is just a game.
1089
01:20:24,505 --> 01:20:26,571
But we could learn
important lessons
1090
01:20:26,573 --> 01:20:29,307
from a computer being
so successful at Go.
1091
01:20:29,309 --> 01:20:31,375
Machines will have
the capability,
1092
01:20:31,377 --> 01:20:34,611
not only to crunch through
huge amount of data,
1093
01:20:34,613 --> 01:20:37,347
but also to analyze
it intelligently.
1094
01:20:37,349 --> 01:20:40,116
Just as in the case
of the Go games,
1095
01:20:40,118 --> 01:20:43,552
the machine made moves that
surprised even experts.
1096
01:20:43,554 --> 01:20:46,421
And, eventually, the machines
will gain our confidence
1097
01:20:46,423 --> 01:20:48,589
because we will see
that very, very often
1098
01:20:48,591 --> 01:20:53,026
they make a better guess than
we could have made as humans.
1099
01:21:23,357 --> 01:21:26,525
Unfortunately for Lee
Sedol, I think white
1100
01:21:26,527 --> 01:21:29,494
might have a slight
advantage here.
1101
01:21:36,935 --> 01:21:38,101
Who told us that?
1102
01:21:38,103 --> 01:21:39,168
Someone, I don't know.
1103
01:21:52,381 --> 01:21:54,382
Winning, okay, not won.
1104
01:21:54,384 --> 01:21:56,550
That's what she said.
1105
01:22:16,170 --> 01:22:17,436
No, not really.
1106
01:22:24,476 --> 01:22:25,642
We don't know the score.
1107
01:22:25,644 --> 01:22:27,677
We have no idea what's
going on, right.
1108
01:23:17,126 --> 01:23:19,727
(crowd clapping)
1109
01:23:24,499 --> 01:23:28,602
I think it just really is
a once-in-a-lifetime thing.
1110
01:23:28,604 --> 01:23:33,273
I would say it's the most
amazing thing I've experienced.
1111
01:23:33,275 --> 01:23:36,442
You know, for us, it's the
culmination of a 20-year dream.
1112
01:23:36,444 --> 01:23:39,845
It started as a pure
research endeavor.
1113
01:23:39,847 --> 01:23:41,313
We just wanted to understand
1114
01:23:41,315 --> 01:23:43,381
can neural networks
play the game of Go?
1115
01:23:43,383 --> 01:23:44,715
And, from there, it went on
1116
01:23:44,717 --> 01:23:47,717
to a level that
I never expected.
1117
01:23:49,386 --> 01:23:52,687
And I'm unbelievably
proud of the team.
1118
01:23:53,755 --> 01:23:56,423
When I started doing
artificial intelligence,
1119
01:23:56,425 --> 01:23:58,591
it was four or five years ago
1120
01:23:58,593 --> 01:24:00,693
and I was really
interested in that.
1121
01:24:00,695 --> 01:24:02,695
But many people
would discourage me.
1122
01:24:02,697 --> 01:24:04,563
They would say
there is no future.
1123
01:24:04,565 --> 01:24:08,166
So actually seeing
that within five years
1124
01:24:08,168 --> 01:24:11,702
we are at this stage right
now it's amazing by itself.
1125
01:24:11,704 --> 01:24:16,139
Everybody say, (speaking
in foreign language)
1126
01:24:17,407 --> 01:24:19,441
There are so many
possible application domains
1127
01:24:19,443 --> 01:24:22,744
where creativity in a different
dimension to what humans
1128
01:24:22,746 --> 01:24:25,613
could do could be
immensely valuable to us.
1129
01:24:25,615 --> 01:24:27,581
And I'd just love to have
more of those moments
1130
01:24:27,583 --> 01:24:29,182
where we look back
and say, "Yeah,
1131
01:24:29,184 --> 01:24:30,616
that was just like move 37."
1132
01:24:30,618 --> 01:24:32,918
Something beautiful
occurred there.
1133
01:24:32,920 --> 01:24:36,588
At least in a broad
sense, move 37 begat move 78
1134
01:24:36,590 --> 01:24:39,857
begat a new attitude
in Lee Sedol,
1135
01:24:39,859 --> 01:24:42,626
a new way of seeing the game.
1136
01:24:42,628 --> 01:24:45,628
He improved through
this machine.
1137
01:24:46,696 --> 01:24:49,431
His humanness was
expanded after playing
1138
01:24:49,433 --> 01:24:52,233
this inanimate creation.
1139
01:24:52,235 --> 01:24:55,603
And the hope is that that
machine, in particular,
1140
01:24:55,605 --> 01:24:58,672
the technology behind it,
can have the same effect
1141
01:24:58,674 --> 01:25:00,206
with all of us.
1142
01:25:01,308 --> 01:25:03,575
I remember hearing
a talk by Kasparov
1143
01:25:03,577 --> 01:25:07,645
who says that a good
human plus a machine
1144
01:25:07,647 --> 01:25:09,813
is the best combination.
1145
01:27:02,058 --> 01:27:05,126
(melodic music)