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Go might be a complex game, but in the grand scheme of things it is a trivial problem to solve, very narrow in scope. You perform an infinitely more complex task everyday when you make breakfast. AlphaGo's achievement is that it learned how to open the fridge with great efficiency.

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Go play a single game of Go and tell me how it goes.

I don't think you understand how machine learning works. Better not to opine on something you don't understand.

It is a narrow application of general purpose machine learning approaches. Convolutional neural networks, supervised/reinforcement learning are not limited to Go. They've found success in a variety of applications.

And while those applications are narrow, they're significant progress in a short period of time.

In this game from only 4 years ago you could see one of the state of the art bots getting humilliated by an anonymous professional player: http://gosensations.com/?id=2&server_id=1&new_id=1392

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