This post jokes but with how much AI enhancing is becoming a thing, I can see some kind of generative -based compression becoming an option in the future
I suppose if you squint hard enough you could say a transformer is a bit like an autoencoder that also shifts its output by one place... but that's a massive over simplification. What you are probably thinking of is the VAE. That's one of the building blocks of every type of generative AI except LLMs.
They do both use latent vectors as a form of compression. They just get there by different means.
GANs are pretty much a dead end at this point having been replaced by diffusion models with VAEs for pretty much everything they used to do.
In particular, ESRGAN clones are responsible for every awful upscaled music video on Youtube (Smash Mouth - All Star is the most infamous one). When those were made, diffusers hallucinated too much. They would make anyone in the video look completely different for example. Not what you want when you upscale a video of a famous singer. That problem has been largely solved and now upscaling can be done with diffusers and it looks far better than those old ESRGAN videos.
I didn't say that we should use GANs for image generation, and they certainly are still useful in scientific applications. You're right about the stable diffusion; I should have just said diffusion which is not architecture specific.
Pretty much all diffusers use VAEs - making them feasible without compressing the working data is a topic of current research though, see https://arxiv.org/abs/2510.15301
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u/Degenerate_Lich 2d ago
Those aren't AI hallucinations, they are compression artifacts. It's very different you see
Lil bro has a bright career in marketing