The sameness problem behind those unappetizing AI-generated menus | TechCrunch

In recent months, dining establishments have increasingly turned to artificial intelligence platforms to create their menus and promotional food advertisements.

This shift has resulted in a noticeable influx of unnaturally pristine, perfectly symmetrical, and strangely smooth food illustrations displayed across various platforms. Many customers have reported experiencing a subtle yet distinct sense of unease when viewing these images, which often feel eerily sterile and devoid of the natural imperfections found in real culinary dishes. Industry analysts explain that this phenomenon occurs because the primary generative models are trained on datasets that prioritize an overly polished and idealized aesthetic, which inadvertently strips away the organic textures that make food look genuinely appealing to humans.

Furthermore, technical specialists point to the challenges of model convergence and repeated image editing as major drivers of this visual degradation. When restaurant operators attempt to tweak or adjust these digital menu files multiple times, the underlying AI tools repeatedly process their own outputs, causing the images to look progressively less realistic and increasingly distorted over time. This trend triggers what psychologists refer to as the uncanny valley effect, where computer-generated food that looks nearly authentic actually evokes feelings of distaste and psychological discomfort rather than hunger. Beyond the commercial realm of restaurant dining, this rapid normalization of synthetic visuals highlights broader societal anxieties regarding the erosion of trust in visual media and digital evidence.