I find it very funny that people are so concerned about false positives. Models like these should really only be used as a screening tool to catch things and flag them for human review. In that context, false positives seem less bad than false negatives (although, people seem to demand zero error in either direction, and that’s just silly).

If you don’t mind, I’d be interested to see the images you used. The broad validation tests I’ve done suggest 80-90% accuracy in general, but there are some specific categories (anime, for example) on which it performs kinda poorly. If your test samples have something in common it would be good to know so I can work on a fix.

Friendly reminder that my AI-generated image detector is available to use free of charge here: https://huggingface.co/spaces/umm-maybe/sdxl-detector

Especially since, like, women have been using machines to pleasure themselves for a while now and it’s still kind of a novelty for most het cis men

I remember a beloved fish-and-chips restaurant in the area where I grew up that had, in addition to fun cartoons of a clam introducing various dishes, smoke stains all along the edge of the ceiling. It was that bad… funny to think that it was soon after smoking was banned that the place closed down–maybe it never actually tasted good but nobody could tell??

Running such a bot with an intentionally underpowered language model that has been trained to mimic a specific Reddit subculture is good clean absurdist parody comedy fun if done up-front and in the open on a sub that allows it, such as r/subsimgpt2interactive, the version of r/subsimulatorgpt2 that is open to user participation.

But yeah, fuck those ChatGPT bots. I recently posted on r/AITAH and the only response I got was obviously from a large language model… it was infuriating.