We've reported on Gaia's incredible data-collection abilities in the past. Recently, it released DR3, its latest data set, with over 1.8 billion objects in it. That's a lot of data to sift through, and one of the most effective ways to do so is through machine learning. A group of researchers did just that by using a supervised learning algorithm to classify a particular type of object found in the data set. The result is one of the world's most comprehensive catalogs of the type of astronomical object known as variables.