Wow! I could use this for a one-time pad encoder and decoder. Since the middle squares method repeats more often, it's probably the right choice because I could send that sequence to another person using one number (seed), and they can decode my message!
Thanks man this explanation has been stellar. I've been wanting to get a grip on procedural generation for a while and only heard vague horror stories about recursive loops and such throwing the organic look off completely. Now I know some official terminology to look out for
a "TRNG" using light is more of just a "CRNG" for a like chaotic random number generator, because it's just something so unpredictable it's hard to figure out. If you had the same light with everything being the same, it would give the same response. hence it not being a true random number generator.
I'm watching this with reversed colors so it isn't so bright and this dude says "it might go all black" @9:25 and I'm like "you trippin dawg, that's white"
Did you really say that Linear Congruential Generators have bad distribution? They literally have perfect distribution in practice. Distribution isnt their flaw. Their primary flaw is that n-tuples of their sequence fall on simple linear n-dimensional hyperplanes. An improvement is to temper the output. The low period of the lower order bits isnt a flaw either. The flaw there is using the entire state. There is no known method of sequence generation that is more efficient than tempered LCG's that also performs better on statistical tests like bigcrush. It is now also known that elaborate chaining of LCG's, like in the case of the Mersenne Twister, is statistically inferior to simple tempered LCG's.
Personally, I want to make an RPG where if the player wanted to, they could predict the RNG with a little effort as the number that affects the seed is a combination of all the character stats that are publicly available.
This has been very helpful. I'm writing dirty JS in html pasted into my blog... 3js is not an option for me to do 'eeal' 3D, but I have been using '2 and a half' D and PR# for procedural world map generation etc. I wish you had a patreon, I'd like to pay you back
a true Random number can actually clump and give a set that is not close to the theological probability. PRNG are actually going to give something closer to the theoretical probability
EXACTLY,,They do.. If you somehow get to know about the parameters (multiplier, increment , modulus and seed) You might get to know about the winning lottery number as well.😁 th-cam.com/video/aZbEF1aduok/w-d-xo.html
Probably. My understanding of hashing is combining existing data with repeatable random data. Hash the same data with the same seed, you get the same result.
slot machines are based on pseudo random generators and "pseudo" because a machine that has a predefined payback rate to the players can by definition not be random. However if you're able to notice or being aware enough to understand that you re in a repeating cycle (bad cycle) then would you be able to apply it to slot machines by leaving a slot machine for another hoping for better winning odds based on the fact that you just left a loosing slot machine (repeating loosing cycles) for another machine that could possible be in a good cycle ? therefore you d have saved money by not feeding a machine that would not have given anything back from the cycle ?
@@kebekbutcher Bro real RNG's are dependant on the hardware. What i meant by that is that there is some kind of special hardware which detects various things like the temperature the radioactive waves etc. These numbers are random,using this they create truly random numbers. Hope that helps!
Wow, this video deserves way more views. This was an awsome + visual explanation. Thanks for taking the time to make this video
Your voice is just perfect for these kind of videos!!!
This is especially useful when you are working with small languages like Scheme which by default do not provide a random number generator.
Why is it so difficult for professors to just teach like this in school
Wow! I could use this for a one-time pad encoder and decoder. Since the middle squares method repeats more often, it's probably the right choice because I could send that sequence to another person using one number (seed), and they can decode my message!
Thanks a lot! This video made the PRNG algorithm much clear for me.
13:37 : are you saying that you can see repeats in a higher dimension? can you emphasis on that idea? Thank you!
So good presentation!!! Thanks!
Thanks man this explanation has been stellar. I've been wanting to get a grip on procedural generation for a while and only heard vague horror stories about recursive loops and such throwing the organic look off completely. Now I know some official terminology to look out for
a "TRNG" using light is more of just a "CRNG" for a like chaotic random number generator, because it's just something so unpredictable it's hard to figure out. If you had the same light with everything being the same, it would give the same response. hence it not being a true random number generator.
brilliant and clear video - super helpful
I'm watching this with reversed colors so it isn't so bright and this dude says "it might go all black" @9:25 and I'm like "you trippin dawg, that's white"
good presentation. i enjoyed the video!
Very useful lesson ! Thanks !
Did you really say that Linear Congruential Generators have bad distribution? They literally have perfect distribution in practice. Distribution isnt their flaw. Their primary flaw is that n-tuples of their sequence fall on simple linear n-dimensional hyperplanes. An improvement is to temper the output. The low period of the lower order bits isnt a flaw either. The flaw there is using the entire state. There is no known method of sequence generation that is more efficient than tempered LCG's that also performs better on statistical tests like bigcrush. It is now also known that elaborate chaining of LCG's, like in the case of the Mersenne Twister, is statistically inferior to simple tempered LCG's.
This is an epic comment. Thanks!
Awesome content. Kudos
great video!
thanks for sharing!
Personally, I want to make an RPG where if the player wanted to, they could predict the RNG with a little effort as the number that affects the seed is a combination of all the character stats that are publicly available.
Sounds interesting.
If only we could harness the chaos of internet conspiracy theorists to seed a random number generator.
Very useful! Particularly that starting to get into openCL and need a PRNG on GPU is important for what I want to do.
How is it determined which of the generated seeds will be returned to the user as the "random number"
What about an app that picks numbers 1 through 75 with 15 lines. How can I tell which line fills up first?
This has been very helpful. I'm writing dirty JS in html pasted into my blog... 3js is not an option for me to do 'eeal' 3D, but I have been using '2 and a half' D and PR# for procedural world map generation etc. I wish you had a patreon, I'd like to pay you back
I wanted random in minecraft.. Put a pressure plate in my cow pen. When the cow happens across it, feels pretty random
can this be applied to MATLAB as well?
How to find the Seed for the first time?
How to do that pattern visualization in python3
a true Random number can actually clump and give a set that is not close to the theological probability. PRNG are actually going to give something closer to the theoretical probability
my question is how did you get those inputs to work. like how did the program you use understand what seed meant for the input value?
seed is just a variable name.. it could have been anything. he was telling the program what to do with it
do lottery machine use this??
EXACTLY,,They do..
If you somehow get to know about the parameters (multiplier, increment , modulus and seed) You might get to know about the winning lottery number as well.😁
th-cam.com/video/aZbEF1aduok/w-d-xo.html
what tool do u use
Thank you sir
shouldnt you be getting an overflow eventually working with an M the size of 2^31?
Isn't the formula used in the Linear Congruential Generator similar to one you may use for hashing?
Probably. My understanding of hashing is combining existing data with repeatable random data. Hash the same data with the same seed, you get the same result.
Yes I've seen something similar except with bitwise operations and modulus.
Awesome.Thanks :)
Whenever I get stuck with something Math, I'm with Keith. So here I am again(⓿_⓿) at stupid o'clock. Hope you are well Keith
i dont rly know how to code but I was wondering if there's a simple way to convert this into python?
20, 8, 6, 15, 35, 6, 10, 5, 20, 23, 14, 28, 28.....
Do you have more sample data?
slot machines are based on pseudo random generators and "pseudo" because a machine that has a predefined payback rate to the players can by definition not be random. However if you're able to notice or being aware enough to understand that you re in a repeating cycle (bad cycle) then would you be able to apply it to slot machines by leaving a slot machine for another hoping for better winning odds based on the fact that you just left a loosing slot machine (repeating loosing cycles) for another machine that could possible be in a good cycle ? therefore you d have saved money by not feeding a machine that would not have given anything back from the cycle ?
cool video
you hacked the eddie
Sir please can I get your email
subscriiiiibing
3:08 so we won't talk about the real RNG??? WTF is this video...
I am still watching the rest of the video, but wtf at that point... I had to make that comment, let's see what is next...
@@kebekbutcher Bro real RNG's are dependant on the hardware.
What i meant by that is that there is some kind of special hardware which detects various things like the temperature the radioactive waves etc. These numbers are random,using this they create truly random numbers.
Hope that helps!
I was the like #999 :(( but super usefull vid