> If 34% of Judges are female you'd expect 34% of the generated images to be perceived as female. That's not what i'd expect, no. I'd expect as it trains it w

> If 34% of Judges are female you'd expect 34% of the generated images to be perceived as female. That's not what i'd expect, no. I'd expect as it trains it would begin to trend towards a median idea of a single judge, an ur-judge if you will. It will represent the median judge. And then with fine-tuning training it would stop making ambiguous characteristics, which would lead it down the most likely path every time. You'd have to intentionally inject some randomness to prevent this. If anything i'm a little surprised they got as much diversity as they did - I can only assume there is some light randomness applied behind the scenes. Note I'm not commenting on "should", but rather what would likely happen given an training dataset that reflects reality