I ask an infamous AI chatbot
Q1: briefly in 100 words how diffusion based art generators work ?
Diffusion-based art generators use mathematical algorithms to simulate the diffusion of particles in a two-dimensional space. These particles are represented by pixels or other visual elements, and their movement is controlled by parameters such as velocity and density. As the particles move, they create patterns and textures that evolve over time, resulting in unique and complex visual compositions. The parameters can be adjusted to achieve different effects, such as the speed and direction of diffusion, the size and shape of the particles, and the color palette. The result is a form of generative art that produces a wide range of organic and dynamic images.
All well and good but what does it all mean? If you didn’t study this how it works before, now is your chance. You’ll read that each source image is progressively degraded back to white noise before being brought back. At each degrading step the surviving features are registered in terms of these parameters of velocity and density. With two quite similar images the similar features will be tracking each other. When recovering and/or generating emerging features will follow pathways similar to those already encountered
In the wide world you can see diffusion at work in a latte coffee as the dark espresso floated on top of the milk spreads into the pale white below.
Let us get a definition of diffusion in this context from our chatBot
Q2: in the context of a diffusion based art generator please give a short explanation of diffusion
Diffusion is a physical process that describes the movement of particles from an area of high concentration to an area of low concentration. In the context of a diffusion-based art generator, this process is simulated using mathematical algorithms to create visual patterns and textures.
