Gas Diffusion Models

Gas diffusion models are algorithms used to generate realistic images by gradually transforming random noise into a desired picture. They work by simulating a process akin to how gases spread out and mix over time. Starting with pure noise, the model iteratively refines the image, removing randomness step by step, guided by learned patterns. This process results in detailed, diverse images that match a given description or style. Gas diffusion models are powerful tools in generating high-quality visuals in AI, combining principles of probability, physics, and machine learning to create or improve images effectively.