Software generated randoms are not really random, so for the large part of applications they can be treated as true random numbers.

Software generated random numbers are inherently predictable as a consequence of a deterministic computation based on Turing machine or any its analogs.

Quantum computing will decide this problem due to fundamentally probabilistic behavior of quantum systems.

Some hardware developers produce physical random generators based on the fluctuation of some physical parameters like temperature, pressure etc.

Physical phenomenon used in such an applications should be expected to be random.

For most precise random number generation it should be essentially random atomic or subatomic phenomena obeying the laws of quantum mechanics.

Such generators often produce not uniformly distributed random numbers (due to peculiarities of certain physical phenomenon or a construction of certain device), but that non-uniformity can be accounted and corrected.

So they are true random numbers.

As I know - the most precisely measurable physical quantity is time which can be measured with quantum mechanics based atomic and quantum clocks.

Certainly, they are not random number generators, but an excellent example of power of quantum physical phenomena we can use today

The term pseudo-random is often used to highlight the fact that a computational procedure that is repeatable is typically at work. Moreover, good pseudo-random number generators will pass many statistical tests for randomness and so are well-suited for use in most simulations. The property of being able to generate the same stream of numbers to drive simulation runs with differing parameter settings is generally a good thing, since it removes one source of variation in results between runs. This is invaluable, for example, in simulation optimization.

While we may assert that some random number generators are not random (because we know the underlying generating function and we know how it behaves), it is more difficult to catalog events as random with certainty. All we can do is say that the suite of tests for randomness have been passed.

The question still remains if we could one day achieve true random function generators because of the nature of randomness

Here are a few items I was able to gather over the years which are important landmarks in the theory of randomness:

1. If you define a random number as a number that is not generated by a program, and by extension, a pseudo-random number as one that is generated by a program, you get into a potential problem if you assume the Deutsch thesis which extends the Church-Turing thesis. The thesis says that any physical process which can occur in nature can be described by a Turing machine. Notice how the I'Ching shares a same philosphical pattern as the approach taken by A. Turing. A. Turing lived for a long time in British India during his childhood.

2. You can define a random number as a number which does not have a programmatic description which is shorter than itself (asymptotically). The measure of the "compressibility" of a sequence of random bits is called the Kolmogorov complexity (or algorithmic complexity). It can be shown that it is not computable in the sense of Turing. But Calude et al. were able to compute its (Omega number) first digits on a particular machine description by defining a probability measure that decreases with length.

Point 2 more or less means that if you are able to determine if a random sequence of bits is truly random, you are also able to enumerate all mathematical truths as the problem is directly related to the Halting problem.

3. The EPR paradox was brought forth by A. Einstein to criticize the random view of the world supported by E. Schrödinger's and W. Heisenberg's quantum mechanics. The famous phrase of Einstein that "God does not play dices" comes from the argument. This philosophical conflict may take more importance when quantum cryptography and communication becomes more practical and widespread.

4. C.E. Shannon states in a post-war paper that there are no mathematically secure cryptographic method except for the one-time pad. The one-time pad uses a sequence of random numbers as long as the message to cipher the message, through addition-modulo for instance.

Those are the classics on random numbers, with a few algorithms such as Blum-Blum-Shub, hardware random number generators (based on quantum phenomena or radioactive decay, etc.)

See you how to define the random number, the use of various forms of equipment to generate random Numbers is essentially different.We study direction is now no matter what you do for a random number generated by the way, how to make use of certain means to be infinitely close to have certain rules to follow in order.