Logarithmic Sobolev inequalities (LSIs) show up in several areas of analysis; in particular, in probability. In this talk I will give some background and applications of LSIs. I will also discuss some recent work and show how LSIs can be used to give a new proof of the classical result that the empirical law of eigenvalues of a sequence of random matrices converges weakly to its mean in probability.