#rng — Public Fediverse posts

Bezpečnostní výzkumník na blogu tmctmt přišel na zajímavou věc o Mullvad VPN, jednom z nejoblíbenějších providerů mezi lidmi, co řeší soukromí. Mullvad totiž nepřiděluje uživatelům exit IP adresy náhodně, ale deterministicky podle WireGuard klíče. To znamená, že se stejným klíčem dostanete na konkrétním serveru vždycky tu samou IP.

Autor si napsal skript, […]

Bezpečnostní výzkumník na blogu tmctmt přišel na zajímavou věc o Mullvad VPN, jednom z nejoblíbenějších providerů mezi lidmi, co řeší soukromí. Mullvad totiž nepřiděluje uživatelům exit IP adresy náhodně, ale deterministicky podle WireGuard klíče. To znamená, že se stejným klíčem dostanete na konkrétním serveru vždycky tu samou IP.

Autor si napsal skript, […]

This (Pseudo) Random Number Generator Does It With Neon

https://fed.brid.gy/r/https://hackaday.com/2026/05/12/this-pseudo-random-number-generator-does-it-with-neon/

This (Pseudo) Random Number Generator Does It With Neon

https://fed.brid.gy/r/https://hackaday.com/2026/05/12/this-pseudo-random-number-generator-does-it-with-neon/

https://www.minenest.com/703641/ How Fast Could YOU Get This Item in Stardew Valley? #stardewvalley #letsplaystardewvalley #gaming #luck #rng #speedrun #StardewValley #StardewValleySpeedrun #StardewValleyVideos

Do your tabletop buddies accuse you of using loaded dice?

☢️ Fear no more! ☢️

GameMaster Dice now comes with True Nuclear Randomness powered by RadPro!

#RadPro #radiation #RNG #DSA #RolePlayingGamesRPGs #TableTop

... but how will they learn otherwise!?

https://piefed.social/c/grimdank/p/1973014/but-how-will-they-learn-otherwise

https://youtu.be/pMnqN2stzOc

Our new plug-in is now available on Itch.

Tired of manually creating randomized sounds AudioStreamPlayer nodes? Well, its automatic now. We wasted a lot of time building this, to save yours! #godot #godotengine #plugin #sfx #rng #audiostreamplayer #randomizer #gdscript #gamedev #indiegamedev #audio #opensource #FOSS #GPLv3

https://youtu.be/pMnqN2stzOc

GUNDAM – Flirtation
#Cuts #Electronic #Grime #RnB #RnG #Stealyogurl #Wifey #bangers #booty #grime #wifey #London
CC BY (#CreativeCommons Attribution) #ccmusic
https://gundamgrime.bandcamp.com/album/flirtation

I added a random number generator (a LFSR using polynomial for n=16 from XAPP052) and a subroutine for PRINT AT to my ZX81 "game".

#zx81 #rng #lfsr

Beat the Eye Ore Grind in The Forge

Stuck on Eye Ore? Learn the fastest farming route, exact drop locations, and smart RNG tips to clear Captain Rowan’s quest without wasting hours in the Ruined Cave.

#TheForge #EyeOre #RobloxGuide #RNG #GamingTips #Roblox #Game

https://www.izoate.com/blog/how-to-get-eye-ore-in-the-forge-roblox-beat-rng-with-fast-farming-drop-locations/

#DouglasAdams has influenced #RandomNumberGeneration for decades to come 🎲 🎲 🎲

#Science #Statistics #MonteCarlo #RNG #TheHitchhikersGuideToTheGalaxy

Just finished up final polish on first release of my anarchy RNG library in Lua! Have you ever wanted an incremental or reversible shuffle? I've got one for you :)

Lua REAME page w/ links: https://cs.wellesley.edu/~pmwh/anarchy/lua/

Main version docs: https://cs.wellesley.edu/~pmwh/anarchy/lua/docs/index.html

Interactive online examples (using equivalent Javascript library): https://solsword.github.io/anarchy/js/examples.html

C, C#/Unity, Python, and Javascript versions are also available.

#coding #rng #random

I absolutely love this one, though I can't remember where I got it from:

Think of a word related to your current number (e.g., "7" → "lucky"), then think of something connected to that word ("lucky" → "horseshoe"), then pull a digit from that new connection ("horseshoe" → 8 letters). This chain of ideas creates unpredictability because each link is unique.

#fedifriends #math #random #rng #entropy

Hey #fedifriends, I’m back to this rabbit hole.

How would you generate a random number using only your mind as a pseudo RNG? Imagine you are going to bed, so you can’t do complex math.

You should be able to keep creating new numbers.

I know various ways to do it, but I trust that you are all smarter than I and will show me something amazing. Please boost!

#math #random #rng #entropy

Random Numbers from Hard Problems: LWE Toy RNG

https://blog.s20n.dev/posts/lwe-rng/

#HackerNews #RandomNumbers #LWE #RNG #HardProblems #ToyRNG #HackerNews

Earlier this month, we posted about some spectacular luck in RuneScape, where we got a very rare, high-value drop. (See post here if you didn't see at the time.)

Even though there's no correlation between loot drop chances within the game (as far as we know), we nonetheless weren't expecting to see anything else like this maybe for a long time, and certainly weren't expecting anything of higher value.

So, last night we were winding down in bed on our tablet, trying to exhaust the last of our mental energy to allow us to sleep. As part of this, we realised we had enough pieces for 3 tetracompasses. We made those, powered them up, and quickly got ourselves 3 ancient caskets.

On opening the 3rd casket, we saw an unusual key in our inventory: it was a shadowy key... which supposedly has a drop rate chance of about 1 in 10000, across 2 loot tables (1 in 1000 then 1 in 10).

We had read about this, but hadn't remembered at the time just how rare it was. We just thought "that's cool" and went to use the key in the display case in the upper floor of the archeology guild to see what was in there.

The display case contained Guildmaster Tony's mattock, which is the highest-level archeology mattock within the game... and has an in-game market value of over 4.8 x 109 coins (4.8 billion) 😶

Probably going to keep and use it until we've either maxed out the archeology skill or really want to get some other expensive items.

#RuneScape #RNG #gaming

Randomly selecting points inside a triangle
https://www.johndcook.com/blog/2025/09/11/random-inside-triangle/
#ycombinator #rng

I made a simple dice roller for web!

You can roll A LOT of dice, of whatever size you need, and then examine all the results and reroll or add new dice.

https://sophiehoulden.com/dice/simple/

#TTRPG #Dice #RNG

I get that lava lamps looks cool, I own one too but… seriously?
"The Randomness Crisis Threatening the Internet"?
… in 2025???

(please note that I have nothing particular against this video, this was mainly the straw that breaks the camel's back and finally led me to rant on the interwebs 🤣)

This problem has long been solved for good, and Yarrow in 1999 put a nail in the coffin for most practical purposes, and Fortuna again in 2003 even removed the need for entropy estimation.

#CSPRNG are real. Are here. Are working. They are fundamentally indistinguishable from real #random numbers (#RNG) for every possible purpose.

“Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin.” (John Von Neumann, 1951)

This is still a cool quote, but it's just that. Funny. Nice. Interesting from an historical point of view. (and only technically still true, not in any practical way)

I get that lava lamps looks cool, I own one too but… seriously?
"The Randomness Crisis Threatening the Internet"?
… in 2025???

(please note that I have nothing particular against this video, this was mainly the straw that breaks the camel's back and finally led me to rant on the interwebs 🤣)

This problem has long been solved for good, and Yarrow in 1999 put a nail in the coffin for most practical purposes, and Fortuna again in 2003 even removed the need for entropy estimation.

#CSPRNG are real. Are here. Are working. They are fundamentally indistinguishable from real #random numbers (#RNG) for every possible purpose.

“Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin.” (John Von Neumann, 1951)

This is still a cool quote, but it's just that. Funny. Nice. Interesting from an historical point of view. (and only technically still true, not in any practical way)

I get that lava lamps looks cool, I own one too but… seriously?
"The Randomness Crisis Threatening the Internet"?
… in 2025???

(please note that I have nothing particular against this video, this was mainly the straw that breaks the camel's back and finally led me to rant on the interwebs 🤣)

This problem has long been solved for good, and Yarrow in 1999 put a nail in the coffin for most practical purposes, and Fortuna again in 2003 even removed the need for entropy estimation.

#CSPRNG are real. Are here. Are working. They are fundamentally indistinguishable from real #random numbers (#RNG) for every possible purpose.

“Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin.” (John Von Neumann, 1951)

This is still a cool quote, but it's just that. Funny. Nice. Interesting from an historical point of view. (and only technically still true, not in any practical way)

I get that lava lamps looks cool, I own one too but… seriously?
"The Randomness Crisis Threatening the Internet"?
… in 2025???

(please note that I have nothing particular against this video, this was mainly the straw that breaks the camel's back and finally led me to rant on the interwebs 🤣)

This problem has long been solved for good, and Yarrow in 1999 put a nail in the coffin for most practical purposes, and Fortuna again in 2003 even removed the need for entropy estimation.

#CSPRNG are real. Are here. Are working. They are fundamentally indistinguishable from real #random numbers (#RNG) for every possible purpose.

“Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin.” (John Von Neumann, 1951)

This is still a cool quote, but it's just that. Funny. Nice. Interesting from an historical point of view. (and only technically still true, not in any practical way)

This year's International RNG Day landed on this Friday, July 11th.

I decided to celebrate this year by building a new random feature to my blog and blogging about it – coming out Friday morning.

https://rngday.com/

#InternationalRNGDay #Random #RNG

Very nice:

"Where Did <random> Go Wrong?", Martin Hořeňovský, CPP Prague, June 2024 [PDF] (https://codingnest.com/files/What%20Went%20Wrong%20With%20_random__.pdf)

Video: https://www.youtube.com/watch?v=rKk6J3CgE80

Via Lobsters: https://lobste.rs/s/l8y8gg/where_did_random_go_wrong

#Random #CPP #STL #Programming #API #RandomNumberGenerator #RNG #Ergonomics #Math

Sometimes the #rng name generator makes me giggle #gameDev

Have I invented perfect random number generation computer chips?

So, last night I slept for a very long time. While I slept, I dreamed that I was explaining to a scientist how to do real random number generation with a computer chip. And, you know what, I think it would actually work.

Computers are not good at randomness

The only thing that computers are good at is giving you the same output for any given input each and every time. It is their predictability that makes them so darn useful.

This is a problem when what you need is randomness.

The closest we have to computer-generated randomness is algorithms that give outputs that are hard for humans to guess. The thing is, for any given seed value, you still get the same output. That’s why Minecraft seeds are a thing.

One of the better algorithms is the Mersenne Twister. This is what powers mt_rand() in PHP.

Nevertheless, this sort of randomness is only pseudorandom. Accidentally use the same input, get the same output.

How can we do better?

One of the best ways to generate cryptographically secure randomness is to use some large external source of chaos. For example, Lavarand. Lavarand is powered by a wall of lava lamps, which the system takes photos of at intervals. The system then extracts some amount of the binary of the image, interprets it however the designers want (all things in computers are just binary, and we only know what sort of thing they are by leaving hints). This data is then used as the seed for pseudorandom generation.

The inclusion of a pseudorandom step means that although the randomness is pretty good in terms of being unguessable, it is still not truly random.

My answer to truly random numbers from a computer

We start with a 64-bit quantum chip. Quantum computing is different from the computing we know now. QBits sit between 1 and 0 until they are read. This allows for some very specific types of computation at speeds that we cannot currently reach with classical computing.

Qbits – quantum bits – suffer from a significant weakness. They are so tiny that a single photon can flip them. Rather than fight this data damage, we can harness it.

We choose 64 because qbits are a bit tricky to make at scale, and 64 bits is what our regular computers use. You could go for a bigger size, say 128, 256, 512, 1024, etc., for cryptographic uses.

One way would be to give the top of the chip a convex glass “lid” that encuredges light into the chip. Another would be to add a layer of tritium and a phosphor, which would glow and send off photons. You could also use some other radioactive matter as long as it gives off something that can flip a bit.

All of these flips are entirely unpredictable and non-repeatable. For the same seed, you will not get the same data.

With this set-up, you could start with a sudorandom seed and prime the quantum chip with it. Wait a reasonable length of time and recover the now changed and truly randomised data.

There are other quantum properties we can use to further enhance our randomness. One such property that creates headaches for classic for modern computing is quantum tunnelling. We are pretty much at the point of the nm scale that if we go much smaller, electrons may just elect to jump to another bit of the chip.

We can use that too. The chip that reads the randomised qbits could itself have a fine enough size that electrons will at times put themselves somewhere unintended. Use that for the data in and the data out, and we now have an array of bits that had three episodes of randomisation. This step is not necessary, but it would speed up the time to true randomness for each set of 64 bits.

The technology exists for true randomness

None of what I have suggested is beyond our current technology level. Other than the very small nm chip design, which might need a little R&D to perfect. We can make this if we want to.

I see a few possible uses for this idea:

1. Cryptography for robust and secure internet connections and the like
2. Gaming, especially for procedurally generated and rough-like games
3. Computer-generated graphics where a certain kind of noise is needed

How to steal this idea

If you are someone with the means to take this idea and turn it into a product, I ask only for accreditation and some company shares as a thank you.

Over to you

I’d love to hear your thoughts and comments. Agree, disagree, or point out a flaw in my thinking – it’s all good. Talk to me.

#flippedBits #MersenneTwister #noise #PHP #quantumComputing #randomness #RNG #Technology

Have I invented perfect random number generation computer chips?

So, last night I slept for a very long time. While I slept, I dreamed that I was explaining to a scientist how to do real random number generation with a computer chip. And, you know what, I think it would actually work.

Computers are not good at randomness

The only thing that computers are good at is giving you the same output for any given input each and every time. It is their predictability that makes them so darn useful.

This is a problem when what you need is randomness.

The closest we have to computer-generated randomness is algorithms that give outputs that are hard for humans to guess. The thing is, for any given seed value, you still get the same output. That’s why Minecraft seeds are a thing.

One of the better algorithms is the Mersenne Twister. This is what powers mt_rand() in PHP.

Nevertheless, this sort of randomness is only pseudorandom. Accidentally use the same input, get the same output.

How can we do better?

One of the best ways to generate cryptographically secure randomness is to use some large external source of chaos. For example, Lavarand. Lavarand is powered by a wall of lava lamps, which the system takes photos of at intervals. The system then extracts some amount of the binary of the image, interprets it however the designers want (all things in computers are just binary, and we only know what sort of thing they are by leaving hints). This data is then used as the seed for pseudorandom generation.

The inclusion of a pseudorandom step means that although the randomness is pretty good in terms of being unguessable, it is still not truly random.

My answer to truly random numbers from a computer

We start with a 64-bit quantum chip. Quantum computing is different from the computing we know now. QBits sit between 1 and 0 until they are read. This allows for some very specific types of computation at speeds that we cannot currently reach with classical computing.

Qbits – quantum bits – suffer from a significant weakness. They are so tiny that a single photon can flip them. Rather than fight this data damage, we can harness it.

We choose 64 because qbits are a bit tricky to make at scale, and 64 bits is what our regular computers use. You could go for a bigger size, say 128, 256, 512, 1024, etc., for cryptographic uses.

One way would be to give the top of the chip a convex glass “lid” that encuredges light into the chip. Another would be to add a layer of tritium and a phosphor, which would glow and send off photons. You could also use some other radioactive matter as long as it gives off something that can flip a bit.

All of these flips are entirely unpredictable and non-repeatable. For the same seed, you will not get the same data.

With this set-up, you could start with a sudorandom seed and prime the quantum chip with it. Wait a reasonable length of time and recover the now changed and truly randomised data.

There are other quantum properties we can use to further enhance our randomness. One such property that creates headaches for classic for modern computing is quantum tunnelling. We are pretty much at the point of the nm scale that if we go much smaller, electrons may just elect to jump to another bit of the chip.

We can use that too. The chip that reads the randomised qbits could itself have a fine enough size that electrons will at times put themselves somewhere unintended. Use that for the data in and the data out, and we now have an array of bits that had three episodes of randomisation. This step is not necessary, but it would speed up the time to true randomness for each set of 64 bits.

The technology exists for true randomness

None of what I have suggested is beyond our current technology level. Other than the very small nm chip design, which might need a little R&D to perfect. We can make this if we want to.

I see a few possible uses for this idea:

1. Cryptography for robust and secure internet connections and the like
2. Gaming, especially for procedurally generated and rough-like games
3. Computer-generated graphics where a certain kind of noise is needed

How to steal this idea

If you are someone with the means to take this idea and turn it into a product, I ask only for accreditation and some company shares as a thank you.

Over to you

I’d love to hear your thoughts and comments. Agree, disagree, or point out a flaw in my thinking – it’s all good. Talk to me.

#flippedBits #MersenneTwister #noise #PHP #quantumComputing #randomness #RNG #Technology

Have I invented perfect random number generation computer chips?

So, last night I slept for a very long time. While I slept, I dreamed that I was explaining to a scientist how to do real random number generation with a computer chip. And, you know what, I think it would actually work.

Computers are not good at randomness

The only thing that computers are good at is giving you the same output for any given input each and every time. It is their predictability that makes them so darn useful.

This is a problem when what you need is randomness.

The closest we have to computer-generated randomness is algorithms that give outputs that are hard for humans to guess. The thing is, for any given seed value, you still get the same output. That’s why Minecraft seeds are a thing.

One of the better algorithms is the Mersenne Twister. This is what powers mt_rand() in PHP.

Nevertheless, this sort of randomness is only pseudorandom. Accidentally use the same input, get the same output.

How can we do better?

One of the best ways to generate cryptographically secure randomness is to use some large external source of chaos. For example, Lavarand. Lavarand is powered by a wall of lava lamps, which the system takes photos of at intervals. The system then extracts some amount of the binary of the image, interprets it however the designers want (all things in computers are just binary, and we only know what sort of thing they are by leaving hints). This data is then used as the seed for pseudorandom generation.

The inclusion of a pseudorandom step means that although the randomness is pretty good in terms of being unguessable, it is still not truly random.

My answer to truly random numbers from a computer

We start with a 64-bit quantum chip. Quantum computing is different from the computing we know now. QBits sit between 1 and 0 until they are read. This allows for some very specific types of computation at speeds that we cannot currently reach with classical computing.

Qbits – quantum bits – suffer from a significant weakness. They are so tiny that a single photon can flip them. Rather than fight this data damage, we can harness it.

We choose 64 because qbits are a bit tricky to make at scale, and 64 bits is what our regular computers use. You could go for a bigger size, say 128, 256, 512, 1024, etc., for cryptographic uses.

One way would be to give the top of the chip a convex glass “lid” that encuredges light into the chip. Another would be to add a layer of tritium and a phosphor, which would glow and send off photons. You could also use some other radioactive matter as long as it gives off something that can flip a bit.

All of these flips are entirely unpredictable and non-repeatable. For the same seed, you will not get the same data.

With this set-up, you could start with a sudorandom seed and prime the quantum chip with it. Wait a reasonable length of time and recover the now changed and truly randomised data.

There are other quantum properties we can use to further enhance our randomness. One such property that creates headaches for classic for modern computing is quantum tunnelling. We are pretty much at the point of the nm scale that if we go much smaller, electrons may just elect to jump to another bit of the chip.

We can use that too. The chip that reads the randomised qbits could itself have a fine enough size that electrons will at times put themselves somewhere unintended. Use that for the data in and the data out, and we now have an array of bits that had three episodes of randomisation. This step is not necessary, but it would speed up the time to true randomness for each set of 64 bits.

The technology exists for true randomness

None of what I have suggested is beyond our current technology level. Other than the very small nm chip design, which might need a little R&D to perfect. We can make this if we want to.

I see a few possible uses for this idea:

1. Cryptography for robust and secure internet connections and the like
2. Gaming, especially for procedurally generated and rough-like games
3. Computer-generated graphics where a certain kind of noise is needed

How to steal this idea

If you are someone with the means to take this idea and turn it into a product, I ask only for accreditation and some company shares as a thank you.

Over to you

I’d love to hear your thoughts and comments. Agree, disagree, or point out a flaw in my thinking – it’s all good. Talk to me.

#flippedBits #MersenneTwister #noise #PHP #quantumComputing #randomness #RNG #Technology

Have I invented perfect random number generation computer chips?

So, last night I slept for a very long time. While I slept, I dreamed that I was explaining to a scientist how to do real random number generation with a computer chip. And, you know what, I think it would actually work.

Computers are not good at randomness

The only thing that computers are good at is giving you the same output for any given input each and every time. It is their predictability that makes them so darn useful.

This is a problem when what you need is randomness.

The closest we have to computer-generated randomness is algorithms that give outputs that are hard for humans to guess. The thing is, for any given seed value, you still get the same output. That’s why Minecraft seeds are a thing.

One of the better algorithms is the Mersenne Twister. This is what powers mt_rand() in PHP.

Nevertheless, this sort of randomness is only pseudorandom. Accidentally use the same input, get the same output.

How can we do better?

One of the best ways to generate cryptographically secure randomness is to use some large external source of chaos. For example, Lavarand. Lavarand is powered by a wall of lava lamps, which the system takes photos of at intervals. The system then extracts some amount of the binary of the image, interprets it however the designers want (all things in computers are just binary, and we only know what sort of thing they are by leaving hints). This data is then used as the seed for pseudorandom generation.

The inclusion of a pseudorandom step means that although the randomness is pretty good in terms of being unguessable, it is still not truly random.

My answer to truly random numbers from a computer

We start with a 64-bit quantum chip. Quantum computing is different from the computing we know now. QBits sit between 1 and 0 until they are read. This allows for some very specific types of computation at speeds that we cannot currently reach with classical computing.

Qbits – quantum bits – suffer from a significant weakness. They are so tiny that a single photon can flip them. Rather than fight this data damage, we can harness it.

We choose 64 because qbits are a bit tricky to make at scale, and 64 bits is what our regular computers use. You could go for a bigger size, say 128, 256, 512, 1024, etc., for cryptographic uses.

One way would be to give the top of the chip a convex glass “lid” that encuredges light into the chip. Another would be to add a layer of tritium and a phosphor, which would glow and send off photons. You could also use some other radioactive matter as long as it gives off something that can flip a bit.

All of these flips are entirely unpredictable and non-repeatable. For the same seed, you will not get the same data.

With this set-up, you could start with a sudorandom seed and prime the quantum chip with it. Wait a reasonable length of time and recover the now changed and truly randomised data.

There are other quantum properties we can use to further enhance our randomness. One such property that creates headaches for classic for modern computing is quantum tunnelling. We are pretty much at the point of the nm scale that if we go much smaller, electrons may just elect to jump to another bit of the chip.

We can use that too. The chip that reads the randomised qbits could itself have a fine enough size that electrons will at times put themselves somewhere unintended. Use that for the data in and the data out, and we now have an array of bits that had three episodes of randomisation. This step is not necessary, but it would speed up the time to true randomness for each set of 64 bits.

The technology exists for true randomness

None of what I have suggested is beyond our current technology level. Other than the very small nm chip design, which might need a little R&D to perfect. We can make this if we want to.

I see a few possible uses for this idea:

1. Cryptography for robust and secure internet connections and the like
2. Gaming, especially for procedurally generated and rough-like games
3. Computer-generated graphics where a certain kind of noise is needed

How to steal this idea

If you are someone with the means to take this idea and turn it into a product, I ask only for accreditation and some company shares as a thank you.

Over to you

I’d love to hear your thoughts and comments. Agree, disagree, or point out a flaw in my thinking – it’s all good. Talk to me.

#flippedBits #MersenneTwister #noise #PHP #quantumComputing #randomness #RNG #Technology

Have I invented perfect random number generation computer chips?

So, last night I slept for a very long time. While I slept, I dreamed that I was explaining to a scientist how to do real random number generation with a computer chip. And, you know what, I think it would actually work.

Computers are not good at randomness

The only thing that computers are good at is giving you the same output for any given input each and every time. It is their predictability that makes them so darn useful.

This is a problem when what you need is randomness.

The closest we have to computer-generated randomness is algorithms that give outputs that are hard for humans to guess. The thing is, for any given seed value, you still get the same output. That’s why Minecraft seeds are a thing.

One of the better algorithms is the Mersenne Twister. This is what powers mt_rand() in PHP.

Nevertheless, this sort of randomness is only pseudorandom. Accidentally use the same input, get the same output.

How can we do better?

One of the best ways to generate cryptographically secure randomness is to use some large external source of chaos. For example, Lavarand. Lavarand is powered by a wall of lava lamps, which the system takes photos of at intervals. The system then extracts some amount of the binary of the image, interprets it however the designers want (all things in computers are just binary, and we only know what sort of thing they are by leaving hints). This data is then used as the seed for pseudorandom generation.

The inclusion of a pseudorandom step means that although the randomness is pretty good in terms of being unguessable, it is still not truly random.

My answer to truly random numbers from a computer

We start with a 64-bit quantum chip. Quantum computing is different from the computing we know now. QBits sit between 1 and 0 until they are read. This allows for some very specific types of computation at speeds that we cannot currently reach with classical computing.

Qbits – quantum bits – suffer from a significant weakness. They are so tiny that a single photon can flip them. Rather than fight this data damage, we can harness it.

We choose 64 because qbits are a bit tricky to make at scale, and 64 bits is what our regular computers use. You could go for a bigger size, say 128, 256, 512, 1024, etc., for cryptographic uses.

One way would be to give the top of the chip a convex glass “lid” that encuredges light into the chip. Another would be to add a layer of tritium and a phosphor, which would glow and send off photons. You could also use some other radioactive matter as long as it gives off something that can flip a bit.

All of these flips are entirely unpredictable and non-repeatable. For the same seed, you will not get the same data.

With this set-up, you could start with a sudorandom seed and prime the quantum chip with it. Wait a reasonable length of time and recover the now changed and truly randomised data.

There are other quantum properties we can use to further enhance our randomness. One such property that creates headaches for classic for modern computing is quantum tunnelling. We are pretty much at the point of the nm scale that if we go much smaller, electrons may just elect to jump to another bit of the chip.

We can use that too. The chip that reads the randomised qbits could itself have a fine enough size that electrons will at times put themselves somewhere unintended. Use that for the data in and the data out, and we now have an array of bits that had three episodes of randomisation. This step is not necessary, but it would speed up the time to true randomness for each set of 64 bits.

The technology exists for true randomness

None of what I have suggested is beyond our current technology level. Other than the very small nm chip design, which might need a little R&D to perfect. We can make this if we want to.

I see a few possible uses for this idea:

1. Cryptography for robust and secure internet connections and the like
2. Gaming, especially for procedurally generated and rough-like games
3. Computer-generated graphics where a certain kind of noise is needed

How to steal this idea

If you are someone with the means to take this idea and turn it into a product, I ask only for accreditation and some company shares as a thank you.

Over to you

I’d love to hear your thoughts and comments. Agree, disagree, or point out a flaw in my thinking – it’s all good. Talk to me.

#flippedBits #MersenneTwister #noise #PHP #quantumComputing #randomness #RNG #Technology

Quantum Random Number Generator Squirts Out Numbers Via MQTT https://hackaday.com/2025/04/26/quantum-random-number-generator-squirts-out-numbers-via-mqtt/ #NetworkHacks #randomness #quantum #random #trng #rng

Quantum Random Number Generator Squirts Out Numbers Via MQTT - Sometimes you need random numbers — and properly random ones, at that. [Sean Boyce... - https://hackaday.com/2025/04/26/quantum-random-number-generator-squirts-out-numbers-via-mqtt/ #networkhacks #randomness #quantum #random #trng #rng

@Walker backdooring open source ai models sounds like something i have heard lately; nist is well know for approving ciphers that are weak sauce #rng #collusion

Cloudflare added another asset to their creative way of generating #entropy. This time, it is a wall of wave machines in different colors in #Lisbon, #Portugal.

More in their blog post Chaos in Cloudflare's Lisbon office.

#Crytpography #crypto #tls #ssl #random #rng

Cloudflare added another asset to their creative way of generating #entropy. This time, it is a wall of wave machines in different colors in #Lisbon, #Portugal.

More in their blog post Chaos in Cloudflare's Lisbon office.

#Crytpography #crypto #tls #ssl #random #rng

Cloudflare added another asset to their creative way of generating #entropy. This time, it is a wall of wave machines in different colors in #Lisbon, #Portugal.

More in their blog post Chaos in Cloudflare's Lisbon office.

#Crytpography #crypto #tls #ssl #random #rng

Cloudflare added another asset to their creative way of generating #entropy. This time, it is a wall of wave machines in different colors in #Lisbon, #Portugal.

More in their blog post Chaos in Cloudflare's Lisbon office.

#Crytpography #crypto #tls #ssl #random #rng

Open-Source Random Numbers https://hackaday.com/2025/02/20/open-source-random-numbers/ #randomnumbergenerator #avalanchebreakdown #electronavalance #avalanchenoise #randomnumber #opensource #randomness #zenerdiode #hardware #entropy #noise #rng

Open-Source Random Numbers https://hackaday.com/2025/02/20/open-source-random-numbers/ #randomnumbergenerator #avalanchebreakdown #electronavalance #avalanchenoise #randomnumber #opensource #randomness #zenerdiode #hardware #entropy #noise #rng

Open-Source Random Numbers https://hackaday.com/2025/02/20/open-source-random-numbers/ #randomnumbergenerator #avalanchebreakdown #electronavalance #avalanchenoise #randomnumber #opensource #randomness #zenerdiode #hardware #entropy #noise #rng

Open-Source Random Numbers https://hackaday.com/2025/02/20/open-source-random-numbers/ #randomnumbergenerator #avalanchebreakdown #electronavalance #avalanchenoise #randomnumber #opensource #randomness #zenerdiode #hardware #entropy #noise #rng

#sydbox started to allow access to getrandom(2) by default as it is soon to be in your #vdso. This means go fast #random numbers but also means full access for your friendly #ransomware to the os #rng. #exherbo #linux #security

#sydbox started to allow access to getrandom(2) by default as it is soon to be in your #vdso. This means go fast #random numbers but also means full access for your friendly #ransomware to the os #rng. #exherbo

#sydbox started to allow access to getrandom(2) by default as it is soon to be in your #vdso. This means go fast #random numbers but also means full access for your friendly #ransomware to the os #rng. #exherbo #linux #security

#sydbox started to allow access to getrandom(2) by default as it is soon to be in your #vdso. This means go fast #random numbers but also means full access for your friendly #ransomware to the os #rng. #exherbo #linux #security

#sydbox started to allow access to getrandom(2) by default as it is soon to be in your #vdso. This means go fast #random numbers but also means full access for your friendly #ransomware to the os #rng. #exherbo #linux #security

Listen to #SustainMyExistence now. It's about the limitations imposed on life by numbers being too low being falsified as a threat. Living how you want to is deliberately impossible.

https://el-has.webflow.io/music-releases/sustain-my-existence

#Music #Metal #FalsifiedNecessity #Money #SelfWorth #RNG #ElHas #Freedom

Money is random meaning­less ELECTRONS. THAT'S HOW DATA IS STORED IN COMPUTERS. YOUR WORTHINESS TO LIVE IS REDUCED DOWN TO AND DETERMINED BY ELECTRONS!!!!

Listen to #SustainMyExistence now. It's about the limitations imposed on life by numbers being too low being falsified as a threat. Living how you want to is deliberately impossible.

https://el-has.webflow.io/music-releases/sustain-my-existence

#Music #Metal #FalsifiedNecessity #Money #SelfWorth #RNG #ElHas #Freedom

Money is random meaning­less ELECTRONS. THAT'S HOW DATA IS STORED IN COMPUTERS. YOUR WORTHINESS TO LIVE IS REDUCED DOWN TO AND DETERMINED BY ELECTRONS!!!!

Listen to #SustainMyExistence now. It's about the limitations imposed on life by numbers being too low being falsified as a threat. Living how you want to is deliberately impossible.

https://el-has.webflow.io/music-releases/sustain-my-existence

#Music #Metal #FalsifiedNecessity #Money #SelfWorth #RNG #ElHas #Freedom

Money is random meaning­less ELECTRONS. THAT'S HOW DATA IS STORED IN COMPUTERS. YOUR WORTHINESS TO LIVE IS REDUCED DOWN TO AND DETERMINED BY ELECTRONS!!!!