Given two sets A, B R n , a measure of their correlation is given by the expected squared inner product between random x A and y B. We prove an inequality showing that no two sets of large enough Gaussian measure (at least e - n for some constant > 0) can have correlation substantially lower than would two random sets of the same size. Our proof is based on a concentration inequality for the overlap of a random Gaussian vector on a large set.