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throwaway314155 44 minutes ago

Not directly related, but I'm curious if gwern ever caved on their views about GAN's being "abandoned" for diffusion?

https://gwern.net/gan

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gwern 22 minutes ago | parent [-]

No. I think the need for adversarial losses in order to distill diffusion models into one-step forward passes has provided additional evidence that GANs were much more viable than diffusimaxis loudly insisted.

(Although I'm not really current on where image generation is these days or who is using GAN-like approaches under the hood or what are the current theoretical understandings of GAN vs AR vs diffusion, so if you have some specific reason I should have "caved", feel free to mention it - I may well just be unaware of it.)

	▲	throwaway314155 4 minutes ago \| parent [-]
		"SotA diffusion uses adversarial methods anyways" seems like a bit of a departure from the case you make in the blog post. edit: For what it's worth - I agree. At least some auto-encoders (which will produce latents for diffusion models) use some form of adversarial method. Still, I'm curious if you think GAN models in their more familiar form are going to eventually take on LCM/diffusion models?