[Cybiote]

According to the old paper (AlphaGo has seen significant improvement in efficiency and algorithm so this might be outdated), the distributed version with 1900 CPUs and 280 GPUs defeated the version with 48 CPU and 8 GPUs 81% of the time.

Non-distributed Alpha Go won 99% of the time versus just the value network and policy network with no rollouts. That AI was estimated as having a 2177 Elo rating, which is not very strong and much weaker than Sedol.

Even with a TPU, a human is more efficient. That neural net pair used 8 GPUs. At a generous 200 watt per GPU that's 1.6 kW, 10% of which is 160 watts. A human brain does all higher level reasoning and uses ~20 Watts. A human is not devoting 100% of its computational power on Go. It is likely just a fraction of that.

But if we look at Chess, Chess engines that run on mobile phones are possibly about or maybe slightly more efficient.

[Houshalter]

I believe I was remembering this from wikipedia:

>In a similar matchup, AlphaGo running on multiple computers won all 500 games played against other Go programs, and 77% of games played against AlphaGo running on a single computer.

But you are right, the full version running on thousands of computers is much stronger than that.

Still, the fact that the non-distributed version is so strong even without tree search is pretty amazing. With algorithmic advances and more training it may eventually catch up to best human players. It's only the first generation of deep learning based Go bots.

And I believe the policy network only takes a few milliseconds to compute a move. So even if the TPU consumes hundreds of watts at full use, it doesn't need to run at full use for long.