Comment by porcoda

As others pointed out, the explosion of interest started with the deep convolutional networks that were applied in image problems. What I always thought was interesting was that prior to that, NNs were largely dismissed as interesting. When I took a course on them around the year 2000 that was the attitude most people took. It seems like what it took to spark renewed interest was ImageNet and seeing what you get when you have a ton of training data to throw at the problem and fast processors to help. After that the ball kept rolling with the subsequent developments around specific network architectures. In the broader community AlexNet is viewed as the big inflection point, but in the academic community you saw interest simmering a couple years earlier - I began to see more talks at workshops about NNs that weren’t being dismissed anymore, probably starting around 2008/09.