How Stanford Engineers Created a Fictitious Compression For HBO
Tekla Perry (3034735) writes Professor Tsachy Weissman and Ph.D student Vinith Misra came up with (almost) believable compression algorithms for HBO's Silicon Valley. Some constraints -- they had to seem plausible, look good when illustrated on a whiteboard, and work with the punchline, "middle out." Next season the engineers may encourage producers to tackle the challenge of local decodability.
Or if you're into math, you invoke the pigeonhole principle
:)
Though technically true, in fairness we need to differentiate between meaningful data and noise. Yes, a universal compressor doesn't care. Human users of compression algorithms, for the most part, do care.
So the limit of useful compression (Shannon aside) comes down to how well we can model the data. As a simple example, I can give you two 64 bit floats as parameters to a quadratic iterator, and you can fill your latest 6TB HDD with conventionally "incompressible" data as the output. If, however, you know the right model, you can recreate that data with a mere 16 bytes of input. Now extend that to more complex functions - Our entire understanding of "random" means nothing more than "more complex than we know how to model". As another example, the delay between decays in a sample of radioactive material - We currently consider that "random", but someday may discover that god doesn't play dice with the universe, and an entirely deterministic process underlies every blip on the ol' Geiger counter.
So while I agree with you technically, for the purposes of a TV show? Lighten up.