Distance covariance is a way to measure how two sets of random data are related. Researchers have found a new, more flexible method to calculate this by using Lévy measures instead of weight functions. This new approach allows for easier conditions on the data and lets us use different distance measures. It also sets the stage for a new method called distance multivariance, which can measure relationships between multiple sets of random data.