Impressive work by Google research team. I'm both impressed and scared.
This is our Deep Blue moment folks. a history is made.
This is our Deep Blue moment folks. a history is made.
This time the computer did not win out of pure bruteforce. Deep Blue relied on an opening book and massive computational power to explore the game tree. After the opening it was pretty much on its own, bruteforcing moves.
This technology used a neural network trained with hundreds of thousands of games which provided the pattern matching aspect, combined with the bruteforce move sequence reading, the montecarlo tree search... and 1200 CPUs + 600 GPUs.
Note though that AlphaGo almost certainly uses single precision arithmetic -- for neural networks even single precision is overkill.
Also the Top500 list is based on Linpack, which measures performance for computations that are pretty strongly interconnected across the different processors of the system. AlphaGo's Monte Carlo tree search problem is more embarrasingly parallel, with evaluation of different positions really being independent computations.
It is much easier to make systems that can handle embarrasingly parallel loads than the highly interconnected loads handled by the top500 supercomputers. So even though the flops are comparable, the systems are not.
While DNN+RL+Tree search is cool, the hardware requirements for AlphaGo to play at this level are staggering and only supported by large marketing budgets :)
IBM lost in 1996, 2-4, and then won in 1997, 3.5-2.5. If they had played a third match with Kasparov, especially a longer match, it is not at all clear that they would have won.
Kasparov asked for a third match of 10 games, to be played over 20 days, but IBM would not give it to him.
Of course, you can change rules as much as you want and generate new marketing events. Personally, I would like a match where the AI is only allowed the energy a human uses. I guess, AlphaGo would lose with only 2000 kcal (2.3 kWh). Not sure about chess.
Pocket Fritz (HIARCS) was winning Grandmaster tournaments and got rated at 2800-2900 Elo - on a smartphone in 2009 using 1W worth of power without offloading to a GPU. The GPU in a more modern phone like the Samsung Galaxy S5 can crunch 140 GFLOPS - an order of magnitude more than Deep Blue (11 GFLOPS). Allowing 200W of power draw raises your computation power into the TFLOPS area (using a PS4, say). No contest - even without two decades of chess engine improvement over Deep Blue.