Generative AI is entering the design of restaurant menus, but its highly homogenized "perfect aesthetics" has also raised new issues with visual experience. More and more restaurants are using AI-generated images for food menus, which often exhibit overly symmetrical, smooth, and refined characteristics. Some works even show obvious problems such as abnormal food structures, which consumers describe as having a "uncanny valley effect."

Alex Lisle, Chief Technology Officer of Reality Defender, believes this phenomenon is related to the training mechanism of AI models. LLMs and diffusion models need to learn patterns from massive data, and when models frequently refer to similar-style chain restaurant menus, the generated results tend to become similar; if AI-generated content further enters the training data, it may reinforce this style convergence. Lee Renney, Director of the "Center for Imagining Digital Futures" at Elon University, stated that training data usually tends to be aesthetically pleasing and avoids offensive content, which further pushes images and language towards being "rounded off."

This issue may become more apparent with repeated editing. A user found that after continuously modifying an AI-generated menu 100 times in ChatGPT, the food images gradually deviated from their original form. Researchers from the University of Duisburg-Essen previously found that AI-generated food images may produce a negative perception similar to the "uncanny valley."

Industry insiders point out that AI-generated content is entering the real information environment on a large scale, and the data generated by the model itself may in turn affect subsequent training. How generative AI can avoid aesthetic homogenization and maintain the details and diversity of the real world will become an important issue beyond the model's capabilities.