Even when the underlying structure is solid, finer details can go awry in their own ways, said Giovanbattista Califano, a behavioral scientist who studies responses to AI-generated imagery at the University of Naples Federico II in Italy. “Diffusion models are notoriously weak at generating thin, continuous, terminating structures,” he said. “Noodles, strands, and tendrils are exactly the kind of geometry that trips this up, so you get spaghetti-like artifacts bleeding into places with no anatomical or culinary logic.” In other words, once a model starts generating something like this, it can struggle to figure out where it should stop or what it should be attached to. Other repeating textures like bubbles and seeds are similarly hard for diffusion models to contain within sensible boundaries, he added, meaning they often spill into areas they should not be in. That helps explain why so many AI food images are so relentlessly noodly, unsettlingly patterned, and riddled with the kind of clustered holes that can trigger trypophobia.
