4 ms·

Sure, but that's just another way of saying SD needs less space than ChatGPT, right? The question is why an image-generating model needs so much fewer paramete

• zamnos 4y ago
  I think that's because the mind can make more sense of a mismash of visual data and see patterns and pictures. Comparatively if drop words here or you can still make sense of what I wrote, but it's much more difficult for the reader to parse what I'm saying if I accidentally a few words. If my drawing has a clearly recognizable human figure but it has 7 fingers, it's still recognizable that it was trying to draw a human. LLMs have been able to generate words for years now. Hell, Tay was back in 2016. Making sure ChatGPT is able to answer the way it does (ie filter out bad things) is part of what makes it hard, and thus bigger, to implement. But having a cohesive readable output is what's hard and takes up more space. Plus, unless I missed it, we don't actually know how many gigabytes the model file for ChatGPT is.
• tomohelix 4y ago
  >images need much more storage space than text to convey similar information That is because an image is a collection of bit that attempt to represent reality as it is. It probably is easier to relates blue as a "color archetype" when you literally have a collection of bits that mean literal "blue" all the time. In languages "blue" doesn't always mean the color. Texts are abstractions/coded form of reality. Your mind itself contains the decryption codes to translate text into what it actually means. That decryption code for text apparently is much bigger and harder for a machine to crack than interpreting images. Also, images are bigger than a text file because of the way data is stored. It probaby has nothing to do with the amount of information stored inside. A book about quantum physics can be smaller than an image of a cat for example.
• famouswaffles 4y ago
  The mistake you're making is thinking of weights as an avenue to store training data. This is wrong. I've hopefully explained it more in another comment but weights/neurons are essentially configuration settings.
• swatcoder 4y ago
  It could suggest that humans have a much more sensitive and expressive sense of language than they do image perception, which seems plausible. We can spot flawed language in more contexts than flawed images, and can produce a bigger range of representation in text and than image. So for a system to produce human-satisfying text, it needs to be far more prepared than one that produces images. Conversely, this may underscore how inefficient pixel-like storage is for communicative and artistic images. Ten years from now, many of those kinds of images may only take a few hundred bytes and a good enough generator model to “decompress” them for display.
  • colechristensen 4y ago
    No it’s just that an image can’t be “false” or “grammatically incorrect”. Anything recognizable can make a satisfying image and people don’t seem too bothered by the kinds of mistakes image generators make. Text generated though we want not to be just a pile of recognizable words but to follow some pretty strict rules and to actually be true. Imagine you insisted stablediffusion only produce photorealistic images and judged it for every inaccuracy.
    • swatcoder 4y ago
      That’s exactly what I said. We have those words (false, grammatically incorrect, etc) because we have a more particular sense of language and identify more nuance in how language fails for us than how images fail for us.
      • hgsgm 4y ago
        It's more that nonsensical language is meaningless, because language has so little content density to begin with, so losing a little loses almost all of it, whereas a mishmashy picture has lots of pieces of meaning, even if the whole is a mess, because images are far more information dense.
  • chaxor 4y ago
    This is the most likely I believe. I expect that the local correlation structure in images is more homogenous than in language, there are more chances to make mistakes (e.g. confusing the intangible and tangible - You can't see green ideas sleeping furiously) and, perhaps, we might even criticise mistakes from long range interactions more in language.
• otabdeveloper4 4y ago
  Text has bigger information complexity than pictures. (So no, a picture isn't worth a thousand words. In reality it's probably the other way around.)
  • startupsfail 4y ago
    A thousand words can certainly be printed on a large enough picture.
  • hgsgm 4y ago
    Why would you say that? Every word can be easily encoded in a tiny picture.
• jffhn 4y ago
  >The question is why Because a word is worth a thousand pictures.
• Closi 4y ago
  I think here we are correlating the size of the input and output here with the size of the machine in the middle that creates it. It's kind of like saying "Why would the factory creating tiny processors for phones (with only tiny bits of raw materials) need to be larger than that other factory that produces loads of big loafs of bread?"
• hgsgm 4y ago
  Images need more space than text because images encode far more non-textual information. Sure, an image of standard font/m face/size/weight/color text has low information, because it's only using asymptotically 0% of it's expressive power. Just look at how a logo conveys more information just by styling text.