How AI Image Generators Work (Stable Diffusion / Dall-E) - Computerphile

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Published 2022-10-04
AI image generators are massive, but how are they creating such interesting images? Dr Mike Pound explains what's going on.

Thumbnail image partly created by DALL-E with the prompt: "Computerphile YouTube Video presenter Mike Pound Explains Diffusion AI methods thumbnail with green computer style title text on a black background with grey binary"

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This video was filmed and edited by Sean Riley.

Computer Science at the University of Nottingham: bit.ly/nottscomputer

Computerphile is a sister project to Brady Haran's Numberphile. More at www.bradyharan.com/

All Comments (21)
  • @InfinityDz
    Glad to have finally found someone I can actually listen to about AI, someone that doesn't hype things up and isn't trying to sell me something.
  • @Qman621
    Stable diffusion doesn't actually actually apply noise to images, it uses a compressed low dimensional latent representation of the image and applies noise to that. The model is running in this abstract latent space, and then the autoencoder recreates the image afterwards.
  • @ayushdhar
    A deep dive on the google colab code would be amazing!
  • @wlockuz4467
    Finally! Ever since Stable Diffusion was released I was looking for an explainer on how it worked that wasn't "Oh it generates images from noise" or something that went too deep into technicals that I didn't understand. Very beautifully explained Dr. Mike Pound! Hope you do another video where you dive into the code where we can see the parts which were visualized here. One thing that's still unclear to me is how was the network trained to relate text with images and how does it utilize this information when actually producing images?
  • @carlborgen
    Would have been nice hear a bit more about the "gpt-style transformer embedding". Wouldn't those classifications have to be included in the training data already?
  • @kgsz
    Came here by accident and man, aren't you the gifted one? I was engrossed in the video knowing barely anything about the technologies and techniques uses, and I don't feel dumber -- that's an achievement :) Thanks again, will pop here often.
  • @aijeveryday_guy
    I couldn't agree more! Since the release of Stable Diffusion, I've been searching for an explanation that strikes the right balance between simplicity and technicality. Your video did an excellent job of providing a clear understanding without overwhelming us with excessive technical details. Dr. Mike Pound, you have a remarkable talent for explaining complex topics in a beautifully straightforward manner!
  • Add noise to images and train a model to undo that addition.. then you have something that maps from noise to images. One thing I find so impressive about these researchers.. is that they would try this. It’s so bizarre.. just because, from a distance, it’s not at all clear that such a task is doable.
  • @dileepvr
    12:58 I'd like to hear more about that GPT-style transformer embedding of text. Was text part of the training set?
  • @beachdancer
    the explanation sounds like magic. It is like a sculptor saying he just chips away pieces of the stone until he finds the horse hidden inside.
  • @mtalsi1
    I love that he's doing all of this on 1980s printer paper. Proper geek
  • @serhat757
    Can't believe Mike can effortlessly make that shape with his hand (little finger) at 5:37
  • @Ultimatro
    So stable diffusion is just the AI version of that sculpting joke: Start with a big block and take away the parts that dont fit
  • @patu8010
    I would love to hear more about the process. Like how does it recognize that the image now looks like a frog on stilts? Seems to me like that's where the real complexity is.
  • @smivan.
    Thank you for covering this topic!
  • @froop2393
    would like to see more details but the explanation was superb for an introduction
  • @Jinjukei
    Thank you so much for talking about this topic! Great and very enjoyable!
  • @lpbaybee4942
    The best compsci content on the internet, period.