Latent space

Instead of working with millions of individual pixels, many image models operate in a much smaller latent space. Similar content lies close together there, so styles or facial expressions, for example, can be blended seamlessly.

The principle is closely related to embeddings in language models: meaning is represented as a position in a multidimensional space.