Atlas of Perception (2025)
What if everything we see is composed of just a few hundred visual elements? Much like how three primary colors combine to form the vast spectrum we perceive, our visual world might be built from a limited set of fundamental concepts.
The Atlas of Perception reveals these building blocks of visual understanding by exploring the latent space of neural networks. By examining how machines parse our world, we gain insight into the grammar of appearance itself—the modular semantics of vision.
Modern neural networks perceive our world through their own version of visual concepts—elemental patterns that combine to form complex imagery. Through artistic interpretation and mechanistic interpretability techniques, this project makes these hidden elements visible.
Displayed on a continuous circular canvas that has no beginning and no end, these visualizations mirror the formless nature of the abstract feature spaces within AI systems. The radial arrangement invites viewers to consider perception as circular rather than linear—a constellation of interrelated concepts rather than a hierarchy.