Unlimited Dream Co. is a "collaboration between a UK-based artist and artificial intelligence." They make amazing art, which you can see here. I also follow their Twitter feed, and saw this weird image:

WaifuLabs uses GANs (generative adversarial networks) to create millions of anime portraits, which can be used as avatars or game characters. They made this video and blog post that explains how GANs work.

You can think of it as a pair of AIs that spar against each other in order to learn:

• The first AI is called the Generator.

It used to be that if you wanted to create a fake persona online, you swiped a photo from some hapless person's Facebook page. These days, though, fakers can create "synthetic" images — using "general adversarial network" AI to generate fake faces that look awfully real. — Read the rest

Browse through photos of never-before-seen art at This Artwork Does Not Exist. The site was created by Philip Wang, and uses a generative adversarial network (GAN) to create images of artwork that don't actually exist.

Generative Adversarial Networks, which were invented by Ian Goodfellow and his colleagues in 2014, use machine learning to produce content. — Read the rest

AI artist Mario Klingemann used Generative Adversarial Networks (GANs), one of the primary techniques to create deepfake videos, to make this incredible, unsettling, and wonderful video that facial expressions to music. (Song: "Triggernometry" by Kraftamt, 2014). Check out another deepweirdfake from this series below. — Read the rest

You've seen This Cat Does Not Exist, now behold Hopefully This Cat Does Not Exist, whereby the failings of generative adversarial networks become their horrifying strengths.

I'm a big fan of the ones where GANs try to write meme captions and ends up with this … abyssal syllabary. — Read the rest

These beetles do not exist: Confusing Coleopterists is an AI trained on illustrations from zoological textbooks. The extreme formality of this art genre, and its placement within the public domain, makes it uniquely apt to the medium of generative adversarial networks: "Results were interesting and mesmerising." — Read the rest

Generated Photos is the latest stupid startup that sounds like a joke from "Silicon Valley" that someone took too far. From their announcement on Medium:

Generated Photos is the free resource of 100k faces for you to use however you wish.

Datagrid says, "We have succeeded in generating high-resolution (1024×1024) images of whole-body who don't exist using Generative Adversarial Networks (GANs). We use these images as virtual models for advertising and fashion."

Generative Adversarial Networks use a pair of machine-learning models to create things that seem very realistic: one of the models, the "generator," uses its training data to make new things; and the other, the "discerner," checks the generator's output to see if it conforms to the model.

Mike Solomon, creative director at Hearst Digital Media, created Judge Fake People. Here's what he wrote about it on his website, The Cleverest:

Like many internet addicts, I was blown away by NVIDEO's demo using style-based Generative Adversarial Networks to generate faces.

First, take this quiz to see how good you are at distinguishing between real faces and fake ones made with generative adversarial networks (GANs). Then, read this article that teaches you how to spot the fakes. In a few years AI will be able to generate images that don't have recognizable tells.

Ganbreeder uses a machine learning technique called Generative Adversarial Networks (GANs) to generate images that seem like photos, at least a first glance.

Researchers at NYU and U Michigan have published a paper explaining how they used a pair of machine-learning systems to develop a "universal fingerprint" that can fool the lowest-security fingerprint sensors 76% of the time (it is less effective against higher-security sensors).