How computers generate RANDOMNESS from math

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How computers generate RANDOMNESS from math

Рет қаралды 55,080

Күн бұрын

A computer's just a bunch of wires that can do calculations right? there shouldn't be a way to arbitrarily pick random numbers, because computers are deterministic, and the same calculation should give you the same output each time.
In this video, we'll find out how computers get around this problem.

Пікірлер: 52

@agrimpuriya2585 Жыл бұрын

Absolutely love your video. I was coding in Python, and i was using "random" library when I suddenly realised "How is a computer, the most pattern based machine in the world, able to generate randomness?".

@yOkay_ Жыл бұрын

@@retroguardian4802 so let's program in rust

@egaLwie. Жыл бұрын

@@yOkay_ no let's do it in chicken

@nemiw4429 Жыл бұрын

Same. 0:31 Im watching the video, never looked into it, but Im pretty sure its impossible. 1:07 ok, thought so. U cant explain a machine "give me random".

@KarTandir 11 ай бұрын

i was studying wave function of an electron an suddenly asked myself the same question lol

@ThankYouESM 2 жыл бұрын

I thought it was always from current milliseconds by 32 decimal places.

@king_james_official 2 жыл бұрын

depends what algorithm the software is using. a lot of time it combines time, mouse movement, cpu load, ram usage, maybe even microphone input

@christophertadeo6120 2 жыл бұрын

Pseudo random is what we call it in computer science...

@user-rm2qj2jh4l 8 ай бұрын

This is such a good, brief yet detailed explanation! Thank you!

@MrLottoLife Жыл бұрын

Which means slots are not unpredictable and random. I've been studying slots and patterns and I've noticed patterns that tend to win even amongst all the "randomness."

@ThankYouESM 2 жыл бұрын

I'm trying to find the type that can create organic art very fast... hopefully each out of a billion numbers like perlin noise combined with mandelbrot

@mohammadjadallah9813 2 жыл бұрын

Okay… but where do you get the seeds from? You’re just saying “pick a number”, isn’t that basically random?

@TonyZhang01 2 жыл бұрын

Yeah so the only way to do that is getting it from somewhere else (time of day, temperature, increasing the seed by one each time, etc). Or you can just use the same seed and continue with the sequence of numbers

@talkingmurga5554 Жыл бұрын

Yeah, generally in multiple programs the seed is set by the user. In other cases it is taken from time or/and hardware data.

@Lea-js9jw 15 күн бұрын

Oogwey was right all along

@kkalyan5569 2 жыл бұрын

Hey,nice explanation and i really appreciate your work. Nice rendering of manim ,it would be really helpful if you can share the manim file for the animations in this video.

@TonyZhang01 2 жыл бұрын

Here it is! gist.github.com/Tony1324/7ca1f41b8ab79847f4cd6e77619acab6

@objectivecompleted-9474 2 ай бұрын

Random numbers: Gargoogolchime = 10^2,000 Gogolbong = 10^50,000,000 Guppyminutia = 10^-20 Guppyminex = 10^-10^20 Guppychunk = 10^15

@Rookie_AI 2 жыл бұрын

Mate, you're incredibly good! Thanks a lot and wishing you the best!

@Ish21823 Жыл бұрын

nah

@chandmalsuthar3129 4 ай бұрын

Hello sir (91 club colour predition) a game janrate 0 to 9 rendom number computer method Is it possible to guess what the next number will be?

@amarboldbatzorig7313 Ай бұрын

Great video. I hope you make more!

@BrokenG-String Жыл бұрын

For more secure randomly generated numbers, other than changing the seed, is it possible/wise to also change the mathematical equation every cycle?

@TonyZhang01 Жыл бұрын

I’m pretty sure that the numbers for the algorithm itself are chosen specifically to work well, and it’s pretty easy to accidentally use a equation that just gives the same number over and over. Also just choosing the seed means that you will have an equal distribution of the numbers

@veteransniper6955 2 ай бұрын

Length of random data you feed in determines true randomness of the output. You can reduce true randomness by choosing inappropriate algorithms but can't increase it. If there is desire for more secure random numbers, I think focus should be on getting more randomness from some entropy source(s), while algorithms also important, but they can't do what they can't do, i.e. provide true randomness from nowhere.

@playful1 Жыл бұрын

Lotto results seem to mention Random number generator. Whereas they always are Specific number generators.

@prodoxel9578 2 жыл бұрын

Thanks for the information!

@matiasvlevi6647 3 жыл бұрын

I like the animations very well explained.

@logicmatthewlearning 2 ай бұрын

Thanks! I now understand xor generator :D

@nasrogalili 2 жыл бұрын

Thank you so much for explaining! Can you please tell me what's the name of the texts transition? Like the effect name..

@TonyZhang01 2 жыл бұрын

I used www.manim.community, the same animation thing used by 3 blue 1 brown. I actually made a whole video about it: kzfaq.info/get/bejne/hbWIoMVzkrvVnZc.html

@utarajat 7 ай бұрын

I'm new to programming. So when we use the random() method in python how is the seed determined there?

@Bonjemus 2 жыл бұрын

Nice explanation!

@thekarotte1625 4 ай бұрын

Very good explanation, thanks.

@alessandrorossi1294 2 жыл бұрын

At 3:01 you say Xorshift is “more robust” than a Linear Congruential Generator without defining in what way that you claim Xorshift is “more robust”.

@TonyZhang01 2 жыл бұрын

That's fair, I guess at the time I just meant a more widely used and more complex algorithm

@alessandrorossi1294 2 жыл бұрын

@@TonyZhang01 ok. robustness is defined by asymptotic analysis on an algorithm and is not a synonym for "popular" or "good". it is a property that will be robust with respect to some variation that winds up not effecting the property. this is important since usually some imperfection, randomness, or noise in your initial conditions is considered likely, so you want a property of an algorithm to be "robust" against imperfections in your initial assumptions, as opposed to being "highly sensitive to initial conditions". however for a pseudo-random number generated you don't want the numbers produced to be "robust" you would prefer them to be highly sensitive to initial conditions because you want them to be hard to predict or to say anything else. the only property of a pseudo-random number generator you would want to be robust is its ability to pass statistical randomness tests over multiple trials. check out martin lof randomness

@wilfriedkamdoum Жыл бұрын

The Xorshift is more comprehensive

@iliapopovich Жыл бұрын

Thanks for the video, It's a very good example, but the simplest way in my opinion is using logic gates output from flip flops.

@pwjaiter6277 Жыл бұрын

It always annoyed me in c hoe relatively hard is is to get a random number

@arvin536 2 жыл бұрын

Underrated

@tylerwatrouse8602 2 жыл бұрын

When I realized this concept it kinda led to understand the idea of 'consequenstialism' or whatever. I geuss I believe in destiny

@jacc7203 2 жыл бұрын

Thats determinism. Consequentialism is the idea that what makes an action wrong is its consequences. For example, a consequentialist would say that punching someone is bad because it causes them pain.

@tylerwatrouse8602 2 жыл бұрын

@@jacc7203 oh I see interesting xD. I geuss I'm both! Hope your doing good wherever you come from

@jacc7203 2 жыл бұрын

@@tylerwatrouse8602 you too