The Inter-Concept Space of Neural Nets

Using Wolf language, we can generate images using a stable diffusion synthesize resource function. We're able to do all sorts of experiments with it that sort of just wouldn't have been possible without that kind of capability. And what's out there in that space of possibilities? For the feature vectors we typically deal with in practice, the space is many thousand dimensional. But we can, for example, look at the sort of nominally straight line from the dog point to the cat point in the space and even generate images of what comes between.