Behind the boom in machine learning

How machine learning has grown since NIPS' start in the '80s: "Over that period what happened was a convergence of a number of different factors, one of them being the fact that computers got a million times faster. Back then we could only study little toy networks with a few hundred units. But now we can study networks with millions of units. The other thing was the training sets -- you need to have examples of what it is you're trying to learn. The internet made it possible for us to get millions of training examples relatively easily, because there's so many images, abundant speech examples, and so forth, that you can download from the internet. Finally, there were breakthroughs along the way in the algorithms that we used to make them more efficient. We understood them a lot better in terms of something called regularization, which is how to keep the network from memorizing -- you want it to generalize."