The incredible breakthroughs we saw in 2017 for deep learning will carry over in a very powerful way in 2018. As I did last year, I’ve compiled a list of predictions for where deep learning will go in 2018. Many deep learning hardware startup ventures will begin to finally deliver their silicon in 2018. Deep learning needs researchers coming from complexity theory, but there are very few of these kinds of researchers. Deep learning research papers will perhaps triple or quadruple in 2018. The road to more predictable and controlled development of deep learning systems is through the development of embodied teaching environments.
Expect to see more companies revealing their internal infrastructure that explains how they deploy deep learning at scale.