Latent space

Reference to Diffusion

Stable Diffusion, an overview of the inference process

What is the network that sustains this object?

• How does it move from person to person, person to software, to platform, what things are attached to it (visual culture)
• Networks of attachments
• How does it relate / sustain a collective? (human + non-human)

In Stable Diffusion, it was the encoding and decoding of images in so-called ‘latent space’, i.e., a simplified mathematical space where images can be reduced in size (or rather represented through smaller amounts of data) to facilitate multiple operations at speed, that drove the model’s success.

From "Maps": _Secondly, there is a 'latent space'. Image latency refers to the space in between the capture of images in datasets and the generation of new images. It is a algorithmic space of computational models where images are, for instance, encoded with 'noise', and the machine then learns how to how to de-code them back into images (aka 'image diffusion')._

How does it evolve through time?

Evolution of size

How does it create value? Or decrease / affect value?

With its material form: the weights. Gains value with adoption.

Gains value by comparison. Ability to do what cannot be done by others or less well.