How AI image-generators work
THE FLURRY of images generated by artificial intelligence feels like the product of a thoroughly modern tool. Today “generative AI ” models put brush to virtual paper: publicly available apps, such as Midjourney and OpenAI’s DALL-E, create images in seconds based on text prompts. The models behind image-generators are trained on enormous datasets: LAION-5B, the largest publicly available one, contains 5.85bn tagged images. A model that has learned which types of pixel arrangement correlate to the word “hippopotamus” should be able to sample from its latent space to create a realistic image of the mammal. Adding more detail to the prompt—for example, “a renaissance-era oil painting of a green hippopotamus, somewhere along the river Nile” —requires the model to source additional layers of visual detail, such as image style, texture, colour and location, and to combine them correctly.
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