Example Concept: AI image generation typically involves using neural networks, such as Generative Adversarial Networks (GANs) or diffusion models. These networks are trained on vast datasets of images to understand various features and styles. During generation, the AI model takes input parameters or prompts and synthesizes new images by combining learned patterns, ensuring the output aligns with the desired style or subject.