Now, let's be critical of possible reasons for this. It's important to remember two things: 1) Any NN has zero experience with the world beyond its training dat

Now, let's be critical of possible reasons for this. It's important to remember two things: 1) Any NN has zero experience with the world beyond its training data. Things that seem obvious to us from our experience are not obvious to a system that has never experienced those things. And 2) DALL-E 2 was trained on image-caption pairs scraped from the internet, basically. So it's quite possible the reason it doesn't understand things like "X under Y" very well is that its training set doesn't have a lot of captions describing positional information like that, as opposed to any failure in the architecture to even potentially understand these things.