Neural Networks, Types, and Functional Programming -- colah's blog

Deep learning, despite its remarkable successes, is a young field. While models called artificial neural networks have been studied for decades, much of that work seems only tenuously connected to modern results. It's often the case that young fields start in a very ad-hoc manner. Later, the mature field is understood very differently than it was understood by its early practitioners. For example, in taxonomy, people have grouped plants and animals for thousands of years, but the way we understood what we were doing changed a lot in light of evolution and molecular biology. In chemistry, we have explored chemical reactions for a long time, but what we understood ourselves to do changed a lot with the discovery of irreducible elements, and again later with models of the atom.