What are the main differences between Stable Diffusion and Unstable Diffusion?
Stable Diffusion is an AI model that uses a diffusion process to generate images, while Unstable Diffusion is an AI model that also uses a diffusion process, but it involves adding noise to the input image.

The main difference between Stable Diffusion and Unstable Diffusion is in how they handle noise during the generation of images. In Stable Diffusion, the noise is added gradually as the image is generated, which helps to create a more natural-looking result. On the other hand, Unstable Diffusion adds noise directly to the input image, which can make some aspects of the image look artificial or inconsistent.

In addition, Stable Diffusion requires significantly less computational power than Unstable Diffusion, making it easier to use on smaller devices such as smartphones and laptops.