Image credits: Reproduction/MIT

New method generates AI images 30x faster 

Researchers at the Massachusetts Institute of Technology (MIT) have just introduced a new method called 'Distribution Matching Distillation' – enabling faster generation of artificial intelligence (AI) images while maintaining the quality of the original model.

The DMD, or Dynamic Diffusion Model, significantly speeds up the imaging process by distilling knowledge from multi-step diffusion models such as stable diffusion, in a single fast model.

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This method employs two diffusion models as a reference to train the new model, ensuring stability and consistency. In testing, DMD has been shown to be able to generate images 30 times faster than Stable Diffusion, while maintaining or even surpassing the quality of the results obtained.

By dramatically reducing the computational cost and time required to generate high-quality images, DMD could unlock new possibilities for tools such as real-time visual editing, design tools, drug discovery and 3D modeling applications.

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