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A pseudorandom number generator (PRNG) is an algorithm for generating a sequence of numbers that approximates the properties of random numbers. The sequence is not truly random in that it is completely determined by a relatively small set of initial values, called the PRNG's state.
Most computer "random number generators" are not hardware devices, but are software routines implementing generator algorithms. They are often supplied as library routines in programming language implementations, or as part of the operating system. These are more properly called pseudo-random number generators, since, being deterministic finite-state machines, they cannot produce truly random outputs
One of the only 'true' computerized random number generator i know of uses the radioactive element from a smoke detector and a CMOS camera, and as the substance decays, random pixels are excited on the CMOS sensor; resulting in a physically impossible to predict random number.
At that point though, your 'random number' might as well be a single reading straight off the ADC with some scaling, and if so I might argue it's more fuzzy logic then a 'true' random number.
A PRNG can be started from an arbitrary starting state using a seed state. It will always produce the same sequence thereafter when initialized with that state.
@madsci1016 - Not questioning what you say in 'theory' but sometimes theory can be overkill for practice! And as you say 'TRUE is a thing of myth' - so lets forget it !!
This doesn't happen if I use the ADC to continually change the seed value.
A physical random number generator can be based on an essentially random atomic or subatomic physical phenomenon whose unpredictability can be traced to the laws of quantum mechanics. Sources of entropy include radioactive decay, thermal noise, shot noise, avalanche noise in Zener diodes, clock drift, the timing of actual movements of a hard disk read/write head, and radio noise.However, physical phenomena and tools used to measure them generally feature asymmetries and systematic biases that make their outcomes not uniformly random.