The slice sampler is a recent example of a Markov chain Monte Carlo (MCMC) algorithm, designed to approximately sample from a given probability distribution. In this talk, we will review recent work (joint with G.O. Roberts) on the convergence properties of this algorithm. A particular variant, the polar slice sampler, will be shown to have strikingly good convergence rate for a large class of distributions.