AI image generation — which relies on neural networks to create new images from a variety of inputs, including text prompts — is projected to become a billion-dollar industry by the end of this decade. Even with today’s technology, if you wanted to make a fanciful picture of, say, a friend planting a flag on Mars or heedlessly flying into a black hole, it could take less than a second. However, before they can perform tasks like that, image generators are commonly trained on massive datasets containing millions of images that are often paired with associated text. Training these generative models can be an arduous chore that takes weeks or months, consuming vast computational resources in the process.
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