Non-existent people

These 5000 persons created by artificial intelligence called GAN (generative adversarial network), no human was involved in the creation of these work, machine created them by machine learning and artificial intelligence algorithms.

These 5000 portrait collected from that created by Tero Karras, many thanks to him.

Original Work (100×50 persons)
3.125x Zoom (32×16 persons)
6.25x Zoom (16×8 persons)
12.5x Zoom (8×4 persons)
25x Zoom (4×2 persons)
50x Zoom (2 persons)

This collage artwork resolution is 800,000,000 pixels (800 Mega Pixels)

Each artwork is 400 x 400 pixels and the artwork resolution is 40,000 x 20,000 pixels.

“At the end of time I want my art to stand up
and my soul to bow down.”

Rob Ryser, Great Desires for Absent Things

Learn more about


A generative adversarial network (GAN) is a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in 2014. Two neural networks contesting with each other in a game (in the form of a zero-sum game, where one agent’s gain is another agent’s loss). Given a training set, this technique learns to generate new data with the same statistics as the training set.

For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of a generative model for unsupervised learning, GANs have also proven useful for semi-supervised learning, fully supervised learning, and reinforcement learning.