Any actual chess knowledge in Deep Blue was an optimization. The fundamental algorithm is alpha-beta search, which can learn to play many, many games of strateg

Any actual chess knowledge in Deep Blue was an optimization. The fundamental algorithm is alpha-beta search, which can learn to play many, many games of strategy. Not Go, as we know now, but the exceptions are few. This is an algorithm that is very adaptable and very good at learning to play games based on a heuristic for whether you are winning. The DeepMind implementation learns how to play Atari games. You could even say that it's learning how to play one game, where your opponent chooses the game cartridge and your goal is to increment the score counter. You would absolutely need to redesign DeepMind to play Super Mario Bros. When you give DeepMind credit for designing itself, you are glossing over the fact that it was programmed by people, most likely for long hours.