Example Concept: Diffusion models operate by iteratively refining noise into a coherent image, with the model's architecture and training data impacting the quality of the output. For instance, a model trained on high-resolution datasets may produce more detailed images, while one with a focus on artistic styles might excel in generating creative, stylized outputs.