GAN Pulse

A real-time generative adversarial network that produces an endless stream of synthetic portrait photographs. No two faces are the same — each frame is a novel identity generated from random noise, challenging our assumptions about authenticity and representation.

Premise. What does it mean to look at a face that has never existed? GAN Pulse streams a continuous feed of AI-generated portraits at 24fps, each one unique. The piece runs on a latent-space random walk, ensuring smooth morphological transitions between subjects — a face ages, changes gender, shifts ethnicity, and morphs into the next identity without cuts.

Architecture. StyleGAN3 backbone with a custom latent-space interpolator written in CUDA. The random walk uses Perlin noise in 512-dimensional space to create organic transitions. A separate classifier network filters out low-quality generations in real time, ensuring only convincing portraits reach the screen.

Early training (epoch 50)

Final model (epoch 2000)

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Early training (epoch 50) Final model (epoch 2000)

Installation view — the piece projected on a 4-metre wall in a darkened gallery, creating an endless parade of synthetic faces.

Year

2024