Before ChatGPT and other artificial intelligence (AI) large language models exploded on the scene last fall, there were AI art generators, based on many of the same technologies. Simplifying, in the context of art generation, these technologies involve a company first setting up a software-based network loosely modeled on the brain with millions of artificial “neurons.” Then, the company collects millions of data digital images, oftentimes scraped from the web. Finally, it runs the images through the neural network. The network performs billions (or even trillions) of mathematical operations on the data samples, measuring various features of the images and relationships between them, and then updating the values of the artificial neurons based on those calculations. This final step is called “model training” and it enables AI art generators to create entirely new images, typically in response to a user typing in a text prompt, as explained further below. Online digital images used as training data are an indispensable part of this process.
OpenAI, the company behind…