Generalizing vectors in generative models seems like an incredibly useful thing to know about, if you want to use them more effectively. Blew my mind when I saw

Generalizing vectors in generative models seems like an incredibly useful thing to know about, if you want to use them more effectively. Blew my mind when I saw someone demonstrate doing vector math on a GAN a couple years back to move an "input image" around the space of outputs. Maybe this could be useful for singling out post-LLM text and generating output that excludes it.