Randomness

[BlackHatCoiner]

Randomness. What exactly is random? Well, it's nothing. It doesn't exist. But let's explain it a bit.

"Random" is an action that no person can predict by himself. Do we agree upon that? Because this is how I'm seeing it. If I roll a dice I cannot know what the result will be, except if I use some advanced physics/maths. In that case I can know the result, but by myself I can't.

Let's take the computer as an example. On random.org you can generate a random number between x and y. I was wondering for a long time how a computer chooses a random number. It doesn't have a "dice" to "roll". And even if it had, it is a machine. Thus, it could calculate the result before the dice finish. I did a research and found this wikipedia link: Hardware random number generator

In computing, a hardware random number generator (HRNG) or true random number generator (TRNG) is a device that generates random numbers from a physical process, rather than by means of an algorithm. Such devices are often based on microscopic phenomena that generate low-level, statistically random "noise" signals, such as thermal noise, the photoelectric effect, involving a beam splitter, and other quantum phenomena. These stochastic processes are, in theory, completely unpredictable, and the theory's assertions of unpredictability are subject to experimental test. This is in contrast to the paradigm of pseudo-random number generation commonly implemented in computer programs.

It says that it creates random numbers from a physical process, rather by means of an algorithm. Now the question comes.

Don't algorithms "read" directly from the hardware? All computers on the world have a piece of hardware that generates random numbers, right? Without it, an algorithm is useless, isn't it?

[odolvlobo]

I think you are confused by the use of the word "algorithm".

A "true" random number generator generates random numbers by sampling an unpredictable physical phenomena. Even though there might be code (which uses an algorithm) to do the sampling and report the values, the source is still unpredictable, and the algorithm for sampling and reporting doesn't affect the predictability.

On the other hand, a "pseudo" random number generator generates random numbers using math (an algorithm). The numbers are unpredictable as long as you don't analyze the algorithm or the values. Here is an example of an algorithm that generates pseudo-random numbers: X_i+1 = ( X_i x 1664525 + 1013904223 ) mod 2³².

[Ucy]

I guess the article is suggesting that randomness generated only via algorithm is weak, limited or not really random, and can possibly be predicted.
Randomness based on those "physical process" described can seem limitless and truely random in behavior hence difficult(not sure about impossible) to predict. I guess you could design an very sophisticated algorithm that can fairly predict the physical processes that seem impossible to predict.

[wonkytonky]

randomness  is cool

statito
@statitoto