alt Hacker NewsI see, yeah, I can see how if it's like 100% matching some parts of the style, but then failing completely on other parts, it's a huge pain to deal with. I wonder if a bigger model could loop here - like, have GPT 5.2 compare the fine-tune output and the Nano Banana output, notice that trees + water are bad, select more examples to fine-tune on, and the retry. Perhaps noticing that the trees and water are missing or bad is a more human judgement, though.
Interestingly enough even the big guns couldn't reliably act as judges. I think there are a few reasons for that:
- the way they represent image tokens isn't conducive to this kind of task
- text-to-image space is actually quite finicky, it's basically impossible to describe to the model what trees ought to look like and have them "get it"
- there's no reliable way to few-shot prompt these models for image tasks yet (!!)