In the distant 80s the scientist in the field of AI, Hans Moravec, enunciated a paradox: what is easy for humans is difficult for machines.
He spoke of visual and auditory understanding, and it is easy to imagine how right he was considering the machines of the time.
Things have changed a lot since then. AI systems today are much more capable of understanding everything they see or hear. And these are just two of the many parameters on which artificial intelligence is gaining ground on human beings.
When we think of AI we are always led to think that it is pure automation. It is not true at all. Just to name one: do you think AI can't replace photographers and portraitists? Error. He no longer even needs a real-life model to photograph.
Today artificial intelligence is able to "imagine", that is, it can represent things that did not exist before in reality.
This video shows the results obtained by an AI that has learned to generate photos of people who don't exist. In terms of quality, only a few artists in the world are capable of inventing faces with photographic precision.
GAN, the secret of AI
The ability to "imagine" is one of the characteristics provided by Opposing Generative Network (in English GAN), one of the most explored methods in the field of AI. The GANs are partly inspired by neuroscientific research.
In practice, a GAN puts two entities that learn from each other in “competition”: one learns to generate fakes, the other learns to recognize them.
The more the ability to recognize a fake improves, the better the fake generated (which corrects the defects of the previous ones) improves. It is a formidable learning mechanism discovered by neuroscientists and inherent in the human brain that is called actor-critic model.
The imagination will not long be a privilege of the human mind alone: how can we exploit this capacity acquired by artificial intelligence?
Here is an essay of what is happening thanks to GAN in laboratories all over the world.
Turn night into day
Practical implications of the imagination? Being able to represent a subject in a different way or translate one representation into another. For example this AI imagine what the drawing of a photo might look like, or the color version of a black and white photo.
An application of this ability can help us see the world differently, or see beyond what appears visible to us. Take a photo taken at night and turn it into a day photo.
A formidable quality that will be able to assist self-driving cars, allowing them to move precisely even in the dark, in the fog or in other adverse conditions.
These are developments that see (alas, as often happens) the military sector to act as a driving force, with first solutions already developed of AI-assisted night vision devices.
Establish the shape of a person by looking at them dressed
When something is not even visible, the GAN "imagine" (and visually represent) intelligent and ever more precise reconstructions. Let's take the case of the called artificial intelligence BodyNet, able to build a person's build based on a dressed photo of him.
A very useful ability, for example, to design tailored suits without performing manual measurements or body scanners.
See through the walls
Another AI can literally locate and "see" someone even when they are on the other side of a wall. Using a method similar to that of bats, this artificial intelligence interprets a signal (in this case wifi) emitted by a device that bounces off objects.
Discover viruses and antivirus, or disease and medicine
The imaginative skill of AI is not limited to creating images or transforming them. Imagination is the tool that leads us to discover new things, 3d also artificial intelligence is no exception in fields such as computer security or drug development.
Modern cyber security tools include AI that can detect threats in a thousand ways. Researchers have designed a GAN that learns how to generate malicious pieces of code that can hack antivirus. It may seem disturbing, but the good news is that GAN is perfecting the ability to recognize increasingly sophisticated viruses at the same time. This is even more valuable when the "virus" is not a computer, and learning to fight it means developing or finding increasingly effective drugs.
What will all this bring us?
The fourth industrial revolution is not about automation, but about collaboration and the symbiosis between men and machines. GANs are a turning point in the development of artificial intelligence and will help us give real super powers to our mental abilities.
Even if the imagination is not always creativity, it is still a tool that allows us to discover new things: will there ever be something among these that will allow machines to surpass us precisely in creativity?