  The Vapnik-Chervonenkis (VC) dimension of a collection of subsets of a set is
an important combinatorial concept in settings such as discrete geometry and
machine learning. In this paper we prove that the VC dimension of the family of
$d$-dimensional cubes in $\mathbb R^d$ is $\lfloor(3d+1)/2\rfloor$.
