10,000 fake persons
in the peace
created by machine & Ai
A collage of 10,000 unique nonexistent persons generated by the artificial intelligence called GAN (generative adversarial network), no human was involved in the creation of these person images, a machine created them by machine learning and artificial intelligence algorithms.
![10k-persons](https://tohidgolkar.com/wp-content/uploads/2021/05/10k-persons.jpg)
![10k-persons-4](https://tohidgolkar.com/wp-content/uploads/2021/05/10k-persons-4.jpg)
![10k-persons-3](https://tohidgolkar.com/wp-content/uploads/2021/05/10k-persons-3.jpg)
![10k-persons-2](https://tohidgolkar.com/wp-content/uploads/2021/05/10k-persons-2.jpg)
![2x1](https://tohidgolkar.com/wp-content/uploads/2021/04/2x1.jpg)
This collage artwork resolution is 100,000,000 pixels (100 Megapixel)
Each person is 1024 x 1024 pixels originally and in the artwork each image is 100×100 pixels
more peaceful people equals more world peace.”
Richard Branson
Learn more about
GAN
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.