Stable diffusion can refer to different things depending on the context. In physics, stable diffusion is a process where particles, energy, or other physical quantities are transferred inside a physical system due to two processes: diffusion and convection. Diffusion is the movement of particles from regions of high concentration to regions of low concentration, while convection is the movement of particles due to an external force or a difference in density or temperature. An example of stable diffusion is a drop of ink spreading through water.

In machine learning, stable diffusion is a type of generative model that can create images from text, modify images based on text, or enhance the resolution of images3. It is based on a diffusion model, which is inspired by the physics principle of nonequilibrium thermodynamics. Stable diffusion conducts the diffusion process in the latent space, which is a compressed representation of the image data, and thus it is much faster than a pure diffusion model. It can also accept conditioning inputs such as text, images, semantic maps, etc. to guide the image generation process. Stable diffusion is an open-source model released by Stability AI in 2022.
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