Example Concept: AI image generators use deep learning techniques to model complex textures by breaking them down into smaller components. The neural networks learn to recognize and replicate the interplay of light and shadow on different surfaces, enabling them to create detailed textures like fur and fabric. This process involves multiple layers of abstraction, where the model refines its understanding of texture details through iterative training on diverse datasets.