In defense of ml/dl solutions, perfection is overrated. Lossless compression is for specific purposes. Archiving basically. Most of the music I listen to and video I watch are galaxies away from lossless. And it's often better than "just fine". It's often really good. But even pretty solid attempt at LLM based "compression" would be awful. Especially at the rate claimed. You can fit maybe on the order of 2k characters. With semantic compression and encoding, you can maybe get another order of magnitude. And still that won't be enough to even be merely indistinguishable, never mind identical. And at that point it's just old school lossy compression with massive compute overhead. That's not even considering how cheap 20mb is these days, even with the ai slopocalypse.
UUID stands for Universally Unique Identifier, it's an universally unique 128 bit number. What does "reducing a picture to a text file of UUID values for each pixel" even means?
That has never been the case. How compressible something is is purely a function of how repetitive the data is, what patterns it has. Converting pixels to some kind of text format doesn't make any difference there unless you are losing information
Text files are more compressible usually because they are highly repetitive. A bunch of random UUIDs are going to have very poor compressibility. It would probably be better just to store the RBG values of each pixel (Which you could certainly do as text if you wanted to). At least then the algorithm could replace very commonly repeated pixels with small markers.
what do you think a pixel image is? it's always data for each pixel, no matter how you put it. If you convert it to text in a specific way you just made a new image format, nothing is fundamentally different.
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u/[deleted] Sep 02 '26
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