Universes as Bigdata: Physics, Geometry and Machine-Learning

The search for the Theory of Everything has led to superstring theory, which then led physics, first to algebraic/differential geometry/topology, and then to computational geometry, and now to data science.
With a concrete playground of the geometric landscape, accumulated by the collaboration of physicists, mathematicians and computer scientists over the last 4 decades, we show how the latest techniques in machine-learning can help explore problems of interest to theoretical physics and to pure mathematics.
At the core of our programme is the question: how can AI help us with mathematics?

81T30, 81-XX, 14-XX