The central limit theorem ensures that the sum of many independent random variables converges to a Gaussian distribution, even if the underlying distribution is uniform or other shapes, and this convergence happens very quickly (by 3 samples for uniform distribution you see non-flat distribution, by 10 samples you are approaching Gaussian).