People here seem mostly impressed by the high resolution of these examples. Based on my experience doing research on Stable Diffusion, scaling up the resolution is the conceptually easy part that only requires larger models and more high-resolution training data. The hard part is semantic alignment with the prompt. Attempts to scale Stable Diffusion, like SDXL, have resulted only in marginally better prompt understan…
I think one part of the problem is using English (or whatever natural language) for the prompts/training. Too much inherent ambiguity. I’m interested to see what tools (like control nets with SD) are developed to overcome this.