Digital Divide

Diffusion Models are a class of generative AI that produce high-quality images by iteratively removing noise from random patterns. Starting with pure noise, they progressively refine the image through a series of learned denoising steps, eventually yielding coherent and detailed visuals. This process mimics biological diffusion, enabling the creation of realistic and diverse images, making them prominent in modern multimedia generation.