![]() ![]() What's important, beyond the win, is the how said Hassabis. Unlike chess, which is played strategically, Go often relies on intuition.Įssentially, it trained a supervised learning policy network to mimic human players, and then allowed the program to play against itself, improving itself through reinforcement learning. Go, Hassabis said, is the "most complex professional game man has ever devised." Why? It has simple rules, yet a huge number of potential moves. SEE: How Google's AI breakthroughs are putting us on a path to narrow AI There's unlimited training data, no testing bias, parallel testing, and you can record measurable progress."Īlthough there are other ways to reach AI goals, Hassabis believes we have much to learn from the brain, which, he said, is the "only existing proof we have that general intelligence is possible." So he's looked for inspiration from neuroscience-and, it should be noted, has personal experience in studying the hippocampus.Īnd although we're nowhere near complete knowledge about the brain, the "exponential increase in understanding the brain," in areas like optogenetics, connectomics, and two-photon microscopy, "allow a wealth of new ways to understand the mind." Games, Hassabis said, "are the perfect platform for testing AI algorithms. In Deep Blue, "you program in the heuristics and rules and strategies," Hassabis said. That's different from how Deep Blue worked, which was programmed specifically for chess. ![]()
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