in this talk, we will explore the problem of the largest singular value of a random sign matrix. we will use the method of $\epsilon$-nets to show that there exists a $c>0$ so that the largest singular value of a random sign matrix of size $n$ is at least $c \sqrt{n}$ with exponentially high probability. while this is a highly combinatorial problem, the method of $\epsilon$-nets could of interest to those in other fields. this talk is based off tao's book on random matrix theory and a recent talk he gave at the 27th annual pcmi summer session on random matrices.