Other AI learning engines like GPT-3, which generates human-sounding text, are also powerful pieces of technology, but there’s something about DALL-E 2’s visual nature that elicits a particularly potent response. And because DALL-E 2 spits out colorful, detailed, high-resolution images, it’s an especially evocative use case of artificial intelligence, and its effects feel very profound. But big leaps in technology often feel a bit like magic. I know that DALL-E 2 isn’t sentient and what it does isn’t magic. Intellectually, I understand that the pictures the engine returns when you type “full body photo of a horse in a space suit” are just the result of a number of assumptions of a machine that has processed a lot of images and can make connections, as well as replace one or more elements of an image with another. Which is probably why the images that DALL-E 2 generates feel to me like magic. In a great article for IEEE Spectrum, Eliza Strickland described diffusion as a process “which begins with a random pattern of dots and slowly alters the pattern to create an image.”Īll of that makes sense to me in the simplest sense. ![]() I also know that DALL-E 2 uses a process called diffusion to generate images from text. And that it uses that data set to make connections between images and the words that described them. I understand that DALL-E 2 was supposedly trained on roughly 650 million image-text pairs that were scraped from the internet. One reason I feel weird is because I don’t really understand the technology as well as I’d like. If you are unfamiliar, it’s a system that takes written prompts and then can produce at-times stunning high-resolution images in an array of artistic styles. I feel very weird about DALL-E 2, OpenAI’s new text-to-image artificial-intelligence engine.
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