PRNGs aren’t random at all; they produce a deterministic sequence of numbers based on a seed value and an internal counter. Two PRNGs using the same algorithm and seed will produce the same sequence of numbers. The sequence is difficult to predict without knowing the algorithm and seed, and the values are close to evenly-distributed, which is enough like random numbers for a lot of use cases.
If you run this yourself using 142757148148443078663499575299582907518 as the seed, your first two pseudorandom numbers will also be
0.6702742156250219 and 0.9667236181962573, assuming your version of Ruby hasn’t changed its PRNG.
PRNGs aren’t random at all; they produce a deterministic sequence of numbers based on a seed value and an internal counter. Two PRNGs using the same algorithm and seed will produce the same sequence of numbers. The sequence is difficult to predict without knowing the algorithm and seed, and the values are close to evenly-distributed, which is enough like random numbers for a lot of use cases.
Here’s an example in Ruby:
seed = Random.new_seed() => 142757148148443078663499575299582907518 prng_1 = Random.new(seed=seed) prng_1.rand() => 0.6702742156250219 prng_2 = Random.new(seed=seed) prng_2.rand() => 0.6702742156250219 prng_1.rand() => 0.9667236181962573 prng_2.rand() => 0.9667236181962573If you run this yourself using 142757148148443078663499575299582907518 as the seed, your first two pseudorandom numbers will also be 0.6702742156250219 and 0.9667236181962573, assuming your version of Ruby hasn’t changed its PRNG.