What’s creativity? The most accredited definition is the following:
“Creativity is the capability of creating novel things”
It is considered one of the most important and irreplaceable peculiarities of humankind. But if this is such a special characteristic, it would be impossible for a neural network to imitate it, isn’t it? Well, not exactly. Today we are facing some extraordinary pinpoints in creating a creative AI with generative models, mainly known as Generative Adversarial Networks (GANs). These are considered by one of the fathers of Deep Learning, Yann Le Cunn, the most important breakthrough of the century in the AI field .
Generative Adversarial Networks (GANs)  were presented by Ian Goodfellow in 2014 and were immediately used to perform spectacular and never-explored tasks.
The first and most widely used application is the generation of new images as I showed in my previous article, “How does an AI Imagine the Universe?”  generating images of planets and celestial bodies such as the following:
All of these images represent non-existent objects generated by a neural network, and the same has been done with animals, people, and objects of all shapes and types.
These networks recently have proved capable of performing tasks that are extremely useful such as increasing the resolution of a photo or sometimes quite funny, such as getting Steve Ballmer and Robert Downey Jr. to duet to Bruno Mars’ Uptown Funk!
Although this may seem at first glance fascinating and totally harmless, there are serious implications and dangers lurking around the corner. These models are also used on a daily basis to deceive people or to ruin their reputation, for example through what are called deepfakes.
It is now possible with this technology to transpose the face of a source actor onto the face of a target actor, making it look, speak or move exactly like the source actor. A video deepfake can make people believe that a political leader has made a particularly dangerous statement that fuels hatred between people, or places a person in an unseemly context that he or she has never been in, or these videos can represent bogus evidence during a judicial process.
Like all tools, it is therefore not good or bad, it always depends on how you use it.
But before delving into the heart of this article, a little explanation of the inner workings of Generative…
Continue reading: https://towardsdatascience.com/the-creative-side-of-vision-transformers-e3efa7c4b859?source=rss—-7f60cf5620c9—4