one day, mathematicians started thinking really hard about moving piles of dirt around, and the wasserstein distance was born. it measures the difference between two probability distributions, in a way that is different (and sometimes better) than entropy and the l^p metrics.  in this talk, i will introduce the field known as optimal transport, and talk about some applications, mainly to machine learning.