> If you've played with any of these tools for 5-10 minutes, you'll know what to look for to quickly identify purely generated images. I've spent tons of time

> If you've played with any of these tools for 5-10 minutes, you'll know what to look for to quickly identify purely generated images. I've spent tons of time with a wide variety of tools/models, and I disagree. It's easy to spot when anomalies show up, like yes, this weird swirl on someone's ear is clearly a DL artifact, sure; but the images that people will actually take and use elsewhere will be artifact-free (unless that's the purpose of their usage). Take a look here: https://lexica.art/ https://lexica.art/ I would bet anything you could take a handful of current generation stable diffusion-generated images (handpicked for the highest quality, no visible artifacts), mix them with human-created images in shared genres, and in a controlled experiment people would do no better than random in identifying their sources.