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  • 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

  • four times.

  • Which is a really big deal.

  • And let us explain to you why.

  • 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

  • us.

  • 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

  • fly.

  • 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

  • how our opponents might respond to them.

  • 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

  • universe.

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

  • teach AlphaGo to do it?

  • 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

  • real games with expert human players.

  • 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

  • a professional Go player at all.

  • 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

  • in the description below.

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

  • the tournament.

  • 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

  • that has lots of possible responses.

  • 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

  • eventually winning.

  • 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

  • patrons on Patreon who make this all possible.

  • Thank you so much for being a patron if you are.

  • If you want to become one of those people you can go to patreon.com/scishow­ there's

  • a bunch of cool things you can get there as well.

  • And don't forget to go to youtube.com/scishow and subscribe!

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

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AI對戰人類:史上最偉大的圍棋比賽 (AI vs. Human: The Greatest Go Tournament Ever)

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