structural:summarization
Generative machine-learning models

Since the mid-2010s, as a result of advances in deep neural networks, models have been created which take as input a natural language description and produces as output an image matching that description. Text-to-image models generally combine a language model, which transforms the input text into a latent representation, and a generative image model, which produces an image conditioned on that representation. The most effective models have generally been trained on massive amounts of image and text data scraped from the web. By 2022, the best of these models, for example Dall-E 2 and Stable Diffusion, are able to create images in a range of styles, ranging from imitations of living artists to near-photorealistic, in a matter of seconds, given powerful enough hardware.