he a little confused but he got the right idea. there is a very natural and straightforward application of ML to compression: the better your model of P(data) gets, the better your compression ratio
Silly Image Compression Idea
41–50 of 59 posts
Re: Silly Image Compression Idea
#42While not exactly the idea in your post, this recent paper by Dubois, Bloem-Reddy, Ullrich, and Maddison on "Lossy Compression for Lossless Prediction" ( https://arxiv.org/abs/2106.10800 ) kinda gets at this idea. From the abstract: Most data is automatically collected and only ever "seen" by algorithms. Yet, data compressors preserve perceptual fidelity rather than just the information needed by algorithms performin…
haha! This is exactly what I was going for, thank you :)
Re: Silly Image Compression Idea
#43That's "dictionary" compression still. AI checks for hints to lookup in well... dictionary. If the dictionary changes, your compression results change too.
You could use an English dictionary and compress the image to words. "Cat on laptop" for example.
I mean what the words "cat on laptop" mean to the AI - that "dictionary" - or more like that state of things where F("cat on laptop") returns on specific thing, and then after some time might return another, unless you control that state.
Re: Silly Image Compression Idea
#44Earlier quoted context omitted.
Well there's already speech-oriented codecs that can go down below a kilobyte per second, and there's this one that throws a neural net at the problem to help squeeze bytes: https://ai.googleblog.com/2021/08/soundstream-end-to-end-neu... I don't think I've ever had a functional connection slower than that. You need packets to be making it through in a timely manner if you want a voice conversation, after all.
> I don't think I've ever had a functional connection slower than that. I _may_ still have a 300 baud modem in a box in the garage. Possibly a 1200/75 one too. (1985 sometimes doesn't seem _that_ long ago...)
Well, you could have just talked on the line that modem was using. That's not really the kind of limit I'm worried about.
Re: Silly Image Compression Idea
#45I do wonder if all the new AI-based "upscaling" algorithms, which can fill in detail to make an image larger, can be used to produce a compression-decompression algorithm: Perform a heavily lossy compression, then "upscale" the result and see if it returns to a good-enough match. If so, compress even further, until your upscaling no longer gives you a good-enough match. Like regular JPG encoding, this can be set to a…
Sufficiently good compression is necessarily dimensionality reduction. Out of compression AI can be jerryrigged, and out of AI compression can be jerryrigged. This truth may be relevant to the evolutionary history of natural intelligence.
Re: Silly Image Compression Idea
#46Earlier quoted context omitted.
I've seen worse; someone presented code for decompression of a fictional data format with no plan in sight for compression. When I asked how the compression part would be implemented, the author called me stupid for asking this question and told me the project was inspired by https://en.wikipedia.org/wiki/Sloot_Digital_Coding_System
Reminds me when I as a 14 year old, barely two years after I started learning programming and having just learned about cyclic redundancy check (CRC), wondered why they couldn't be used for compression. Take a block of say 16 bytes, calculate the CRC code and store that. To decompress you then just had to find the string of bytes that generated a matching CRC code. It seemed so brilliant, but something told me it was…
Reminds me of my genius compression algorithm from when I was around 12. Information on the computer is just numbers right? So why not just divide the number by two over and over until its in the single digits. Infinite compression. The only thing left to figure out is how to compress all the remainders from the numbers that aren't divisible by two.
Needless to say, I never could solve that problem.
Re: Silly Image Compression Idea
#47> What would image compression look like if designed around other things perceptions?
For computers, the question is meaningless because they only interact with our outside reality in the form of a "Chinese room" translation task. There's nothing inherently salient about image data to a computer, because the "ground floor" reality of computers is instructions for moving electrical charges around on some chips. But, given computers with built in cameras and having some use for discerning its reality of objects in 3d space, subject to Newtonian physics, and projected down to a 2d CCD array, the ideal compression would be subject to the same pressures as influenced the evolution of the human eyes and brain. Thus it should be similar.
Isn't it funny how similar compression artifacts can be to the visual distortion of psychedelics.
Re: Silly Image Compression Idea
#48> formats like JPEG are designed around human perception
This isn't really true. JPEG is fourier or wavelet based. It will compress any image by discarding fourier coefficients, regardless if the input image makes sense to humans.
Re: Silly Image Compression Idea
#49I do wonder if all the new AI-based "upscaling" algorithms, which can fill in detail to make an image larger, can be used to produce a compression-decompression algorithm: Perform a heavily lossy compression, then "upscale" the result and see if it returns to a good-enough match. If so, compress even further, until your upscaling no longer gives you a good-enough match. Like regular JPG encoding, this can be set to a…
This has been tried in research and works, with typical artefacts such as horses getting zebra-stripes if they stand in tall grass (or something like that ...)
Re: Silly Image Compression Idea
#50> What would image compression look like if designed around other things perceptions? For computers, the question is meaningless because they only interact with our outside reality in the form of a "Chinese room" translation task. There's nothing inherently salient about image data to a computer, because the "ground floor" reality of computers is instructions for moving electrical charges around on some chips. But, g…
> But, given computers with built in cameras and having some use for discerning its reality of objects in 3d space, subject to Newtonian physics, and projected down to a 2d CCD array, the ideal compression would be subject to the same pressures as influenced the evolution of the human eyes and brain. Thus it should be similar.
You have a good point! Though I wouldn't say the 'same' pressures. We can actually identify differences in those pressure, and use those to speculate.
Eg human computational capacity does well in terms of total operations performed, but individual units are really, really slow compared to electronics. That means human hardware can't run anything that requires a lot of 'serial depth', everything has to be almost embarrassingly parallel to work, or involve a lot of lookup from caches.
Also the design of humans is constrained by what evolution can do. Eg we still have blind spots in our eyes, mostly because evolution can only take 'small steps' (small in the space of genes), and inverting the eye so that the light receptive cells are in front instead of behind the nerves and blood vessels is not a small step in that space.
The power constraints on humans and computer are likely to be different. Humans are also not networked with sub-second latencies to the rest of world.
(Just to be clear, the examples I gave are second-order corrections to your much more important first-order idea!)