Diffusion based image generation is a kind of ‘reversing the embedding’, right? The iterative error correction applied here almost feels like repeated noise re

Diffusion based image generation is a kind of ‘reversing the embedding’, right? The iterative error correction applied here almost feels like repeated noise reduction, too. So does this mean you could use this sort of text recovery to do the same kinds of things image diffusers do, traversing the latent space and recovering images along a path - but instead recovering text that morphs? Could we finally use this to discover the text that lies exactly halfway between the Declaration of Independence and the lyrics of ‘Baby Got Back’? I guess not until it scales to more than 32 tokens. But we can dream.