4 ms·

It's an attractive idea but I believe that probability says "no". Assuming a perfect RNG, the odds are stacked that you can assume any length(index), into the c

It's an attractive idea but I believe that probability says "no". Assuming a perfect RNG, the odds are stacked that you can assume any length(index), into the correct set of data, will be longer than that data you're seeking a location of. More background here: https://math.stackexchange.com/questions/432017/can-random-number-generators-be-used-in-compression https://math.stackexchange.com/questions/432017/can-random-n... I'm sure there may be isolated exceptions where this wouldn't happen and it'd be fascinating to learn about what they'd be. To my knowledge none have been found yet. If you know of any, do share.

nwoli 4y ago
I guess one counter argument is lossy compression. Another argument is to think about how rng generators are constructed in some cases (algebraic curves) and imagine instead of finding a seed, solving for an algebraic curve with the desired properties. More data necessary (the curve data) and tons of compute still (solving multivariate polynomials) but less so than finding a seed. Then there’s also ideas like creating the weights out of another network (basically moving around in that sub space) which is a much more feasible idea and something Hardmaru has a cool article about