A Brief History of Deep Learning (Part Two) - Bulletproof

In part one of this series we covered some of the history and theoretical basics of Artificial Neural Networks (ANNs). Now it's time to look at what changed to lead us to where we are today. In the pre-cloud era, time, cost and computational constraints meant that large scale research was prohibitively difficult. It was also unclear exactly how to scale ANNs out to hundreds of layers and thousands of neurons. And even if it was possible, could you get any results worth using? So given how difficult it was, it's worth asking what the motivation was in the first place.