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I really liked Jeff Atwoods explanation [0], and the DeepMinds CEO talk referenced in his post [1] [0] http://blog.codinghorror.com/thanks-for-ruining-another-

• thomasahle 11y ago
  I'm not sure Atwoods whole point about computation power: If AlphaGo was intimidating today, having soundly beaten the best human Go player in the world, it'll be no contest after a few more years of GPUs doubling and redoubling their speeds again. In the AlphaGo paper they said their cluster version (with the 170 GPUs Atwoods mention) were the limit of what hardware could do for their algorithms. They tried using much larger clusters, but it didn't really improve performance. This actually fits his point that for chess, most of the performance gain over the last ten years has come from better algorithms. In particular for chess, better tuning of variables, through projects like fishtest (http://stockfishchess.org/ http://stockfishchess.org/) It seems like many of these problems can only be solved using algorithms with require a certain amount of computing power. However once we've reached that particular amount of power, further progress really lies in the algorithms.