Ask HN: Is Alpha-Go winning due to improvements in AI or raw computing power?

Does it have to be one or the other? I imagine AlphaGo is too complex to have ever been effectively on, say, a 486, so without advances in hardware and networking it wouldn't work. At the same time AlphaGo is solving the sort of problem that no throw-more-computers-at-the-problem would have solved things either.

We live in a world of subtly and nuance. It's rare that there's a simple 'black or white' answer to a question.

It's both. Most of the Reinforcement and Deep Learning techniques used in AlphaGo have been around for many years and while there are a couple of novel algorithms many overestimate their impact. It's most a mix & match of techniques that hasn't really been done before. Plus good engineering.

IMO compute power (GPUs) played the bigger role. DeepMind themselves say that training AlphaGo wouldn't have been possible without access to Google's large-scale infrastructure. They've been training it on thousands of machines simultaneously. That's not to be confused with the hardware necessary to play the game, which isn't much and can be done on a single machine. Only the training phase has these extreme hardware requirements.