How Random Number Generators Actually Work

Software “randomness” is almost never truly random in the strictest physical sense, and that’s completely fine for the overwhelming majority of everyday uses, understanding the distinction just helps set the right expectations.

True Randomness vs Pseudorandomness

True randomness comes from an unpredictable physical process, like radioactive decay or atmospheric noise. Most software instead uses pseudorandom number generation: a deterministic algorithm, seeded with some starting value, that produces a sequence of numbers statistically indistinguishable from true randomness for practical purposes, without actually being unpredictable to someone who knows the algorithm and seed.

Why Pseudorandomness Is Usually Fine

For games, simulations, sampling, and general everyday randomization, a good pseudorandom generator is entirely sufficient, its output passes every practical statistical test for randomness. Only in specific security-critical contexts (generating encryption keys, for example) does the distinction between pseudorandom and cryptographically secure random generation actually matter.

Common Mistakes

• Assuming a “random” result can’t repeat. Randomness doesn’t mean “never the same value twice”; getting the same random number, or even the same sequence, twice is entirely possible and doesn’t indicate a bug.
• Assuming all random number generators are equally suitable for security purposes. A generator that’s perfectly fine for shuffling a game deck may not be suitable for generating something like an encryption key, which needs a cryptographically secure source.
• Expecting a small sample to look perfectly “even.” True randomness produces clumps and streaks over small samples; a genuinely random sequence doesn’t have to alternate evenly to actually be random.

Use the Random Number Generator

The Random Number Generator generates random numbers instantly within any range you specify.