So recently a thought struck me that we use random functions in our software all the time right? Either in games or in machine learning models, cry...
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Truly random number generators do not exist, since true randomness is only a theoretical concept.
Well True Random generators do exist, here is a site which let's you generate True Random numbers - random.org/
They have also explained how they are generating these true randoms
The fact that they can explain their method makes them not random. For something to be truly random, it would depend on nothing, and be 'chosen without method'. It's a purely theoretical concept.
Doesn't truly random mean that you can't predict it? What does it have to do with "chosen method"? I mean they are relying on environment and I think that's random enough right?
With enough information, you could predict that. That's the point.
You said it correctly with your phrasing 'random enough' - it's probably beyond the practical reach of anyone to predict it... but that doesn't make it truly random.
random.org seems based on "atmospheric noise" as they said. I didn't check the details, but this seems chaotic enough to make the random sequence be unpredictable in practice.
There is also qrandom.io/, which seems to generate random values based on quantum random generator. These generators are truly unpredictable, even if you know the exact state of the whole universe.
Unfortunately the assumption that all random functions somewhere are PRNGs is wrong. We have true random number generator built into hardware. Since these are usually quite slow they mostly serve as seed input for a PRNGs.
Most likely of your machine can also produce real random numbers using the RDRAND instruction.
Yeah, I agree and that's why I only mentioned the programming language's random functions, although am curious how does hardware generates this random number? Atmospheric noise? I thought for PRNGs we normally use timestamp.
That depends on the hardware RNG - it can be thermal-based / brownian motion, but atmospheric noise or general current fluctuations are also a viable source. There are also more sophisticated methods. In general such hardware RNGs don't give better performance (as mentioned they are quite slow) and are also not used in applications where randomness is crucial (the classic MT19937 is still sufficiently good). They are good, however, for cryptographic applications under certain circumstances (e.g., OpenSSL allows you to use them).
If you refer to timestamps for the seed of a PRNG that can be true (in cases no seed has been given), but then again it fully depends on the framework and usage. Consider
/dev/random- they use a mix of different sources incl.RDRAND(and similar likeRDSEED) if available. Exceptions (based on the used distro) exist.Wow.. I remember using
Random.nextInt()for testing against a test case. I was curious but was too lazy to know what goes underneath. Now, I understand the underlying mechanism.Glad I was able to help you understand something 😁
TLDR; truly random numbers aren't feasible but we do have some ways to create numbers that are "random enough" for most purposes.
Haha, that does sum up the blog
Agreed 💯
It was great
Ho, yeah, the good old Rapid Racer on PS1 and its fractal generator !
Haha never played it but based on your given link it does looks cool, reminds me of boats in GTA vice City
Be like Cloudfare, record bunch of lava lamps and hash the image into numbers.