The Folded World

"That is the heartbeat of contemporary AI. Data folded into a dense internal landscape where words cluster into something that behaves like understanding. The models are creating meaning, yet their pathways remain opaque. When they hallucinate, they are not simply wrong; they expose the edges of an internal world whose logic we cannot fully trace. The artworks explore that fault line."

"Classical paintings, early computer interfaces, neon vector grids, and digital remnants sit side by side, compressed into a single surface much like features in a neural layer. The small coded labels scattered across the images resemble confidence scores, quiet indicators of the hidden mathematics. Each collage becomes a graphic expression of the model's internal turbulence. Layer sits above layer, and underneath we glimpse not a complete scene but fragments of training data and partial connections, the visual equivalent of a model synthesizing meaning from incompatible sources."

Contemporary AI predicts successive words by folding data into dense internal landscapes where word clusters form structures resembling understanding. Model-generated meaning emerges from internal patterns even though those pathways remain opaque. Hallucinations reveal boundaries of an internal world whose logic resists complete tracing. Visual works place classical paintings, early computer interfaces, neon vector grids, and digital remnants side by side, compressed like neural features. Small coded labels function like confidence scores and hint at hidden mathematics. Collages layer fragments of training data and partial connections to express internal turbulence and the synthesis of meaning from incompatible sources.

Read at Zehfernandes