Every year, more than 10,000 papers report solutions to electronic
structure problems using Kohn-Sham density functional theory (DFT). But
all such calculations are limited by the accuracy of our functional
approximations which rely on decades of human insight, intuition, and
trial-and-error. On the other hand, Machine Learning (ML) is a powerful
technology for discovering statistical structure in data. ML has
enabled both science and industry to accelerate scientific discovery and
generate novel products and services. I will report results from
an unholy alliance of DFT with ML.