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This was my first thought too. Even if transformers turn out to be the holy grail for LLMs, people are still interested in diffusion models for image generation.

I think we’re about to see a lot of interesting specialized silicon for neural nets in the coming years, but locking yourself into a specific kind of model seems a little too specialized right now.



Diffusion models could actually be implemented with transformers, hypothetically. Their training and inference is what makes diffusion models unique, not the model architecture.




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