Most scientists don’t need truly random numbers. I used pseudo-random numbers for years and they work great. In fact, the idea that you can reliably get the same random sequence over and over by setting the same seed is a big help in testing. You only want the results to change if you change the algorithm, not if you are just changing the how it is input or stored. It’s a great way to find bugs.
Pseudorandom is all you need for scientific problems like diffusion, Monte Carlo, injecting noise, etc.
I understand the need for truly random in security and encryption applications but even then a simple blowfish encryption with the password set to the CEO’s daughter’s middle name spelled backwards in camelcase and hexencoded is usually plenty. You’ll need more if you work at a bank of course, but the banks hire out for that.
It is a super fun topic that computer scientists like to talk about at lunch, but you’ll rarely use it unless you specialize in hyper-secure encryption.
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