A Functional Reboot for Deep Learning
Invited talk for Summer BOB 2019 in Berlin.
In this talk, I want to begin a conversation about what is the essence of deep learning and how we can optimally support this essence in the form of a programming interface or language. I'll give you my own impressions, and I hope to provoke an ongoing conversation. Despite the phenomenal success of deep learning, it's my sense that most of the choices made in the theory and practice of deep learning are nonessential and even harmful (unnecessarily complex and limited). I'll suggest that a very small addition to a modern typed functional programming language such as Haskell yields an ideal basis for deep learning that is much simpler, more general, and more rigorous that currently popular approaches.