It works because SD (and DALLE2) don't only infer from the priors from their image training dataset, they infer and mix up concepts coming from the text embeddi

It works because SD (and DALLE2) don't only infer from the priors from their image training dataset, they infer and mix up concepts coming from the text embedding as well - as this was also trained on images (previously, as CLIP or OpenCLIP). So CLIP can have picked up an association that a named artist usually is synonymous with for example "broad strokes, moody lighting" and then that is fed into the diffusion model, which doesn't know the artist but DOES know what broad strokes and moody lighting is. But sure, if CLIP didn't know about the artist name either it won't work of course. By the way you can still just enter the particulars of the artist you want to mimic by text as well. There is not THAT much information in a style and you won't need to feed an image into the system. I guess all of this with artists trying to protect their online works by watermarking or glazing will only be a very short speedbump for better or worse. If a human can do a 1-shot style transfer by a single glance at a work, the next round of AIs will as well, and won't be hampered by adding noise to the works and you might have "style extraction" tools that could work like chatgpt in that you iteratively instruct by text commands what to do to get closer without ever letting the AI look at an image.