What Google DeepMind Means for A.I.
J Thoendell stashed this in AI
Whipping humanity’s ass at Fishing Derby may not seem like a particularly noteworthy achievement for artificial intelligence—nearly two decades ago, after all, I.B.M.’s Deep Blue computer beat Garry Kasparov, a chess grandmaster, at his own more intellectually aspirational game—but according to Zachary Mason, a novelist and computer scientist, it actually is. Chess, he noted, has an extremely limited “feature space”; the only information that Deep Blue needed to consider was the positions of the pieces on the board, during a span of not much more than a hundred turns. It could play to its strengths of perfect memory and brute-force computing power. But in an Atari game, Mason said, “there’s a byte or so of information per pixel” and hundreds of thousands of turns, which adds up to much more and much messier data for the DeepMind A.I. to process. In this sense, a game like Crazy Climber is a closer analogue to the real world than chess is, and in the real world humans still have the edge. Moreover, whereas Deep Blue was highly specialized, and preprogrammed by human grandmasters with a library of moves and rules, DeepMind is able to use the same all-purpose code for a wide array of games.