Example Concept: AI models like GANs and transformers are trained on extensive datasets of music or art to learn the underlying patterns and styles. During training, these models adjust their parameters to minimize the difference between their generated outputs and real examples. Once trained, the models can generate new, creative pieces by sampling from the learned distribution, often incorporating randomness or user input to enhance creativity.