"In the latest paper, Yehudayoff and his collaborators define learnability as the ability to make predictions about a large data set by sampling a small number of data points. The link with Cantor’s problem is that there are infinitely many ways of choosing the smaller set, but the size of that infinity is unknown."
Reading this got me wondering about more philosophical aspects, such as the relation of this conclusion to to the process of human learning and prediction (which obviously works) and whether it's somehow tied in some way to the problem of induction. Could be nonsense, but I'll be putting some more thought into the meaning of this