latent diffusion models

Latent diffusion models are a type of AI used to generate images or other data by learning complex patterns. Instead of working directly in the high-quality image space, they transform images into a compressed, lower-dimensional form called the "latent space." The model then learns to gradually add and remove noise within this latent space, effectively "diffusing" the data. When generating new images, it starts from noise and iteratively refines it back into a clear image in the latent space, making the process more efficient. This approach enables high-quality results while reducing computational demands.