Name: AI対人間：史上最高の囲碁大会 (AI vs. Human: The Greatest Go Tournament Ever)
Uploaded: 2021-01-14T07:51:10.000Z
Duration: 4 min 7 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

For fans of artificial intelligence, the past
few weeks have been very exciting.

Last October, for the first time ever, an
AI built by Google, known as AlphaGo, beat

a professional human player at the incredibly
complex board game Go.

And then, in this last week, it went on to
beat one of the best players in the world

When engineers talk about artificial intelligence,
they don't mean sentient humanoid robots

conversing with us, talking to us, becoming
feeling, then taking over the world destroying

AI is really just a way of programming computers
to do things that humans normally do.

See, computer programs follow a specific list
of instructions to complete tasks, so they

struggle with situations that have lots of
options and require decision-making on the

Including playing complicated board games,
like Go.

The basic objective of Go is to get as many
points as possible, either by capturing the

other player's pieces or by claiming areas
of the board with black or white stones.

And a big part of the winning strategy for
any game is the ability to think a few moves

ahead, taking into account what the other
player might do each time you make a move.

We humans can use our past experiences with
the game to figure out the best moves, and

But it's hard to build that kind of pattern
recognition into a computer program.

So generally, computers play board games -- like
chess -- by searching through all the possible

combinations of moves to find the one that
means it's most likely to win.

The problem is, Go is played on a huge 19-by-19
grid -- and there are hundreds of possible

moves that a player might make in every turn.

In fact, there are more ways for a game of
Go to play out than there are atoms in the

So if it's that difficult to program an
AI to beat humans at Go, how did engineers

Well, instead of having the AI search through
all the possible combinations of moves they

tried to help it understand the difference
between a good move and a bad one.

To do that, the engineers first fed AlphaGo
30 million combinations of moves, taken from

Then, AlphaGo played thousands of matches
against itself, to learn new strategies.

All that knowledge, plus some clever programming,
helps the AI decide on the best next move.

Instead of having to consider every single
possible move, which would take a really long

time, it can quickly narrow down the few,
most relevant options.

And so far, this strategy has worked really
well against us humans.

A few months ago, AlphaGo played a 5-match
tournament against Fan Hui, the European Go

champion, and won every single game -- the
first time a computer had ever won against

Then, Google decided that it was time to test
the AI against Lee Sedol, a South Korean who's

been the top Go player in the world for the
past decade.

They livestreamed all five matches, and uploaded
15-minute summaries -- which are all linked

And -- spoiler alert -- AlphaGo won the first
three, so best out of three of five: it won

So it was pretty clear that the way the engineers
programmed and trained the AI did work.

But AlphaGo and Sedol were still set to play
the last two games in the series.

And Sedol actually won the fourth game -- which
was a huge deal, because it showed that the

AI still isn't perfect at choosing the best
moves.

A big turning point in this game was when
Sedol played a move known as a wedge -- one

Basically, he was trying to confuse the AI
by giving it too many options to explore.

And that seems to have worked, even after
all that training.

After the wedge, the game went downhill for
AlphaGo, until its internally-calculated chances

of winning went below 20% -- at which point
it's programmed to resign.

Game 5 turned out to be a very close game,
with AlphaGo making a mistake early on, but

So AlphaGo might not be the best Go player
in the world right now -- but it'll just

keep getting better from here, so odds are,
eventually, it will be.

Either way, it's a huge step forward for
artificial intelligence.

Thank you for watching this episode of SciShow
News, and thank you especially to all of our

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