Generative adversarial networks (GANs) were used in AI art and photography to understand the fundamentals of AI image generation, before being largely replaced by Diffusion models.
To be an AI photographer, learn what the AI requires to work efficiently, take numerous photographs (500-1500), and capture the space around interesting elements to create patterns.
After obtaining a dataset of images, cropping, rotating, and reversing them can significantly increase the dataset size, leading to different outcomes when training a model, which can be done efficiently using tools like RunwayML.