We study a simple model of search where the searcher undergoes normal diffusion, but once in a while resets to its initial starting point stochastically with rate r. The effect of a finite resetting rate r turns out to be rather drastic. It leads to finite mean search time which, as a function of r, has a minimum at an optimal resetting rate r_c. This makes the search process efficient. We then generalize this model to study multiple searchers. Resetting alters fundamentally the late time decay of the survival probability of a stationary target when there are multiple searchers: while the typical survival probability decays exponentially with time, the average decays as a power law with an exponent depending continuously on the density of searchers. We also consider various generalisations of this simple model. Refs: M.R. Evans and S.N. Majumdar, "Diffusion with Stochastic Resetting", Phys. Rev. Lett. 106, 160601 (2011). M.R. Evans and S.N. Majumdar, "Diffusion with Optimal Resetting", J. Phys. A-Math. & Theor. 44, 435001 (2011).