If you're aruging about historical accuracy, but still want accurate looking generated images, I don't know what to say.
But to the technical point, A large part of the training corpus has biases that if left unchecked would cause PR based disasters for the company hosting it. ie the classic black teenager/white teenager.
Now as training of models is not an exact science, and neither is the fine tuning, its analogous to forcing a water balloon into a square box. Its possible but it has odd side effects when you get to the corners.
When making a _product_ you need to choose the least worse failure case. For grok it was for a long time, pandering to the ego of the owner. For Google, who is an advertising company, its about trying not to scare advertisers. This means everthing must be vanilla
If you're aruging about historical accuracy, but still want accurate looking generated images, I don't know what to say.
But to the technical point, A large part of the training corpus has biases that if left unchecked would cause PR based disasters for the company hosting it. ie the classic black teenager/white teenager.
Now as training of models is not an exact science, and neither is the fine tuning, its analogous to forcing a water balloon into a square box. Its possible but it has odd side effects when you get to the corners.
When making a _product_ you need to choose the least worse failure case. For grok it was for a long time, pandering to the ego of the owner. For Google, who is an advertising company, its about trying not to scare advertisers. This means everthing must be vanilla