Machine Learning and the value of (human) knowledge
Recently Google Deepmind announced in a paper in Nature that it has produced an even better version of their Go playing AI, and that this time the AI, pretty much, taught itself. It was told the rules of the game, of course, but after that it simply played against itself millions of times and reached a level of play that surpasses anything else that came before it. Let's go to the original paper for a discussion of what this might mean for the future ... a pure reinforcement learning approach requires just a few more hours to train, and achieves much better asymptotic performance, compared to training on human expert data. Using this approach, AlphaGo Zero defeated the strongest previous versions of AlphaGo, which were trained from human data using handcrafted features, by a large margin. Humankind has accumulated Go knowledge from millions of games played over thousands of years, collectively distilled into patterns, proverbs and books. In the space of a few days, start