pseudo-random numbers, since they’re technically less random, but feel

They’re also more useful in a lot of cases, because with pseudorandom number generation, you can certify constraints on the distributions that you’re sampling from and guarantee a certain level of stability of the behavior of the algorithm. As a result, there are a few settings where we can get higher entropy pseudorandom numbers than what we can get out of truly random samples of external processes.