Because it’s trained on “real” people, will it be easier to generate ugly people? I have a hard time convincing DALL-E to give me ugly DnD character portraits.
that is a very dated (2008) concept.
the model "understands" that 50% of people are below/above median.
consequently, those that are not "OMG girl ur BEAUTIFUL"-tagged are horse-faced.
It understands that the girl with the profile picture with 200 likes and 2k friends is better looking than the girl with 4 likes and 500 friends.
Unless your model is single focus for humans and faces I find it hard to believe there is specific business logic in the training process around inferring beauty from social engagement. Metas model is general purpose.
I'm not very familiar with model training. How does it understand this? Is such information part of the training data?
In the literature, testing concepts in image generation is asking human graders "which image do you prefer more for this caption?," so the answer is probably no. You could speculate on all the approaches that would help this system learn the concept "ugly," and they would probably work, but it would be hard to measure.