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by visarga
3498 days ago
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Yes, but this function you defined, that applies tens of judgements to select a "random" number, is based on a random number input itself. The random part is just the seed, it then passes through various neural nets that expand on it and turn it into a plausible answer. Randomness is injected into all brain processes on account that biological neurons are stochastic. So there is an amount of randomness mixed into everything the brain does. Some neural nets can map real images into a Gaussian, and back. That means they disentangle the factors of the image into a mix of independent factors that map into the standard deviation. Any set of random numbers could be converted back into an image, by the reverse process. |
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On what basis do you make this claim? Humans are empirically terrible random number generators. If you ask someone to pick a random number, the result is very not random. Our biases are large and obvious, so it seems faulty to claim that our "seed" number is in any way truly random.
> Randomness is injected into all brain processes on account that biological neurons are stochastic. So there is an amount of randomness mixed into everything the brain does.
There's also some amount of randomness in what happens if you drop a rock but the net result is largely the same: it falls down. The fact that there is some randomness to a process does not mean that the randomness is actually driving the process.
> Some neural nets can map real images into a Gaussian, and back. That means they disentangle the factors of the image into a mix of independent factors that map into the standard deviation. Any set of random numbers could be converted back into an image, by the reverse process.
I don't see how this is relevant.