In the era of artificial intelligence, we use computers as tools for  developing our abilities to create , as well as for building collaborative working relationships between people, as well as between a person and a computer.

The impact of neural networks is comparable to the advent of electricity and the Internet. Like other general profile technologies, this technology transforms society at different levels.

One of the most popular examples of how artificial intelligence works is the creation of a new song by popular artists based on the analysis of a large array of data.

Artists working with algorithms, as a rule, do not write neural networks themselves and do not have a special education in the field of IT, but they need to be able to understand the code. 

First of all, an artist working with artificial intelligence must collect a representative amount of data on which he will train the machine.

Artificial intelligence algorithms are actually smart enough to create art without involving human artists, but taking into account human creative products in the learning process.

Generative Adversarial Networks have taken the field of artificial intelligence by storm, generating human fake faces.

Algorithm developers are trying to imitate exactly how people develop art. People are exposed to various types of art throughout their lives, and this is where they make an impression on their new art, this is exactly the workflow that developers want to follow their model.

Creative Adversarial Networks' algorithms are based on the principle, which states that art becomes attractive to viewers by increasing their arousal potential, which pushes it to become addictive.

Art is perceived by the audience when they are presented with something exclusive. But the level of arousal must be controlled and not grow exponentially in order to get a negative reaction.

The goal of Creative Adversarial Networks algorithms is to satisfy the potential that relates to the levels of arousal in humans. 

Images obtained with the help of Creative Adversarial Networks occupy the highest place in terms of potential arousal methods, such as novelty, surprise, ambiguity and complexity. These models better deceived people into believing that art was created by humans.

There is no doubt that artists, critics, art critics and curators need access to the practice of artificial intelligence in contemporary art.

The Art-Intel podcast will provide tremendous support for the formation of such access and the formation of an information platform.

We will tell you about the news and features of the development of this branch of digital art, but also connect actors of contemporary art with carriers of available technologies in the field of artificial intelligence.

Our podcast for those interested in the use of artificial intelligence in contemporary art.

Art-Intel offers to discuss what artificial intelligence can help us  do to work with texts, objects and images.