MIT scientists have just figured out how to make the most popular AI image generators 30 times faster
By Keumars Afifi-Sabet published 4 hours ago
Scientists have built a framework that gives generative AI systems like DALL·E 3 and Stable Diffusion a major boost by condensing them into smaller models — without compromising their quality.
Scientists have devised a technique called "distribution matching distillation" (DMD) that teaches new AI models to mimic established image generators. (Image credit: oxygen/Getty Images)
Popular artificial intelligence (AI) powered image generators can run up to 30 times faster thanks to a technique that condenses an entire 100-stage process into one step, new research shows.
Scientists have devised a technique called "distribution matching distillation" (DMD) that teaches new AI models to mimic established image generators, known as diffusion models, such as DALL·E 3, Midjourney and Stable Diffusion.
This framework results in smaller and leaner AI models that can generate images much more quickly while retaining the same quality of the final image. The scientists detailed their findings in a study uploaded Dec. 5, 2023, to the preprint server arXiv.
"Our work is a novel method that accelerates current diffusion models such as Stable Diffusion and DALLE-3 by 30 times," study co-lead author Tianwei Yin, a doctoral student in electrical engineering and computer science at MIT, said in a statement. "This advancement not only significantly reduces computational time but also retains, if not surpasses, the quality of the generated visual content.
More:
https://www.livescience.com/technology/artificial-intelligence/mit-has-just-worked-out-how-to-make-the-most-popular-ai-image-generators-dall-e-3-stable-diffusion-30-times-faster
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