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AI language models can exceed PNG and FLAC in lossless compression, says study (arstechnica.com)

submitted 1 year ago by FlickOfTheBean to c/technology

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While LLMs have been used for... a lot, it seems like this use might be one where it's not only reliable but it appears to outperform existing methods of image compression. Being able to cram more data into less space tends to lead to interesting developments, so I will be keeping my eye on this.

What do you guys think? Seem like it's deserving of less hype than I'm giving it? What kind of security holes do you think this could open?

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[–] firenzeleon 5 points 1 year ago (1 children)

That’s not what lossless data compression schemes do:

Yes it is.

You went into a lot of detail about how they do it, but it's still what they do.

[–] BFrizzleFoShizzle@lemmy.nz 2 points 1 year ago

I think the main point they're disagreeing with is this:

you wouldn’t be able to mathematically prove that the signal is perfectly recovered 100% of the time for all possible inputs

They explain why you don't need 100% accuracy - most compression codecs would only use the network for a prediction, which doesn't actually have to be correct. It just has to be "more likely to be correct" than existing algorithms.

If you want to read up more on the context of these prediction functions, the general class of compression algorithms you'd use for this are called prediction wavelet codecs. FLAC and arguably PNG are both prediction wavelet codecs.