Unscathed, you try playing yourself against the master. You lose again, again, and again. Gino silently makes his moves and swiftly corners you each time. In a while, you manage not to lose right away, but your defeat still comes pretty quickly, and your progress in defeat-time is biblically slow. It seems like you would need to play an incredibly large number of matches to get to a decent level.
This is reinforcement learning, and it worked out spectacularly for AlphaGo (having to operate in a much greater search space than chess, BTW). In more constrained problem spaces, which in my mind include most of “knowledge work” / desk jobs, the amount of labeled data needed seems to be in the order of 00s of 000s.
This is reinforcement learning, and it worked out spectacularly for AlphaGo (having to operate in a much greater search space than chess, BTW). In more constrained problem spaces, which in my mind include most of “knowledge work” / desk jobs, the amount of labeled data needed seems to be in the order of 00s of 000s.