AI art

AI art is visual or other creative work generated or transformed by artificial intelligence, often in response to user prompts. It ranges from images and music to text and interactive media.

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Text-to-image model: A machine-learning model that generates images from natural-language descriptions. This is the best-known form of prompt-based AI art generation.
Computer art: Art created or substantially shaped using computers. AI art extends a longer history of artists using computation as a creative medium.
Refik Anadol: A media artist known for large-scale installations made with data and machine learning. His immersive installations show how AI-generated imagery can operate beyond a screen.
Copyright of AI-generated works: The legal question of whether and how copyright protects works produced with artificial intelligence. AI art challenges rules that often require human authorship for copyright protection.
Photography: The practice of making images by recording light, usually with a camera. Like AI imagery, photography has prompted disputes about whether new tools diminish artistic skill.
Diffusion model: A generative model that learns to create data by reversing a gradual process of adding noise. Many image generators build pictures by iteratively removing noise.
AARON: A computer program created by Harold Cohen to produce drawings and paintings. AARON generated art decades before modern machine-learning image generators.
Mario Klingemann: A German artist who uses neural networks and code to create generative artworks. His practice helped establish neural-network systems as tools for contemporary art.
Fair use: A legal doctrine permitting certain uses of copyrighted material without permission in the United States. Training on copyrighted artworks has prompted disputes over whether fair use applies.
Digital painting: The creation of painted images using digital tools and software. Digital painting gives artists direct control over marks, unlike prompt-led image synthesis.