Alphago on big screen
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AlphaGo’s win is a victory for humans, not machines

Google’s stream of the 5-game Go series between DeepMind’s AlphaGo and Lee Sedol was odd. It put little vector-graphic landmarks from Seoul opposite little vector-graphic landmarks from London. But I never once heard it suggested that this was a battle between Korea and the UK. Maybe it would have been more appropriate to put a brain on one side and a processor on the other, but that’s equally inaccurate. It may not seem it at first, but AlphaGo and its victory represents human effort and human progress. While we still have “the machines” under control, they are tools for our…

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Just what are we losing to Google’s AlphaGo?

In Tang dynasty China, Go was one of the skills socially required of a certain class of educated elite—along with calligraphy, painting, and the ability to play the stringed guqin, it was part of a kind of artistic quadrivium. The art and beauty of the game are present in the way it is played, but also in descriptions and metaphors for the shapes that appear on the board during play. One of the first shapes shown to new players is the “eye.” If a group of white stones is surrounded by black stones on all sides, it is captured. The…

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This Go student has become the Go master—and it’s a computer

If Go is mentioned in the US, it’s in the context of complicated games, or hard games, or games with some element of “purity.” It’s just white stones and black stones on a nineteen by nineteen board. You play by putting stones down, not moving them, if you surround your opponent’s stones they are “captured,” and that’s more or less it. Ostensibly, no game could be simpler. But if you’ve ever tried to learn how to play Go, you’ll know it feels a lot more like the spoiled-for-choice paralysis of staring at a blank page The board has 361 spaces,…

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It will be an awful long time before coders come close to cracking Go

Go is an ancient contest of meditative strategy, but in the present day another deeper meta-game of cracking its mastery with algorithms is going on. Yet the way the mind of a Go player works continues to elude programmers. Computers are no match. Wired has a pretty fascinating feature on the subject of how code just can’t grasp Go. Says one cognitive scientist and complex systems theorist who studied the pros: The result was totally unexpected. Moves became steadily more predictable until players reached near-professional level. But at that point, moves started getting less predictable, and we don’t know why.…