Fundamental Sciences and Engineering have been using numerical simulation methods for decades, accelerating the discovery of knowledge and the development of new technologies. At the same time, the Artificial Intelligence and Machine Learning communities were busy developing methods that replicate human capabilities of perception, pattern recognition and reasoning. In recent years, we are witnessing a confluence of the fields: Machine Learning is being used, in many different ways, to expand the boundaries of what Scientific Computing can do. In this talk we will give an overview of current trends, and some of the open questions for the future.