What Is A Generative Adversarial Network? A generative adversarial network (GAN) is a type of machine learning model that uses two competing neural networks to generate new data that resembles the ...

We officially can no longer trust anything we see on the internet. From whole-body deep fakes to AI-based translation dubbing, technology is starting to distort reality — all with the help of machine ...

Back in June, an image generator that could turn even the crudest doodle of a face into a more realistic looking image made the rounds online. That system used a fairly new type of algorithm called a ...

This article is part of Demystifying AI, a series of posts that (try) to disambiguate the jargon and myths surrounding AI. Moments of epiphany tend to come in the unlikeliest of circumstances. For Ian ...

What is a Generative Adversarial Network (GAN)? Generative Adversarial Networks, or GANs, are a type of deep learning model made up of two neural networks that are essentially in a creative face-off.

Generative adversarial networks, or GANs, are deep learning frameworks for unsupervised learning that utilize two neural networks. The two networks are pitted against each other, with one generating ...

Nvidia has created the first generative network capable of creating a fully functional video game without an underlying game engine. The project was begun to test a theory: Could an AI learn how to ...