I don't see what's so problematic with it. I doubt the model is actually confusing trees and branches with birds. It has associations, but humans do too. If

I don't see what's so problematic with it. I doubt the model is actually confusing trees and branches with birds. It has associations, but humans do too. If I ask a human to draw a demon, the background would not be an office? Also the complain about 'made of' not being in the training data. Humans who never saw a bird can not draw a bird. Why is that saying something about the model? I'm not saying that diffusion models act like humans. And I was talking specifically about image generation. My usage of the word understanding is in the task of image generation. I'm not even talking about 'made of', or 'birds'. Just 'cats' and 'hats'. If it can understand 1 thing, it can understand others, but they are not always in the training data. This is all a non-problem. It kinda remind me of the discussion of what constitutes a 'male', or 'female'. All i want is to refer this one property that i observe in diffusion models. Which is what language is, reference. If you are so covetous of the word 'understand', then provide an alternative to refer to this property and i will gladly use it. https://imgur.com/a/fuS8kcf https://imgur.com/a/fuS8kcf