The amazing features of neural networks 2019
It seems that not a day goes by without a message slipping through the news with the words “artificial intelligence”, “neural network”, “machine learning”. This is not surprising, the algorithms are constantly improving, gaining new knowledge, including information about each of us. And this brings out very interesting future prospects, with personalized goods, food and entertainment. But first things first.
What surprise neural networks?
Some news about the neural networks that appeared in recent months a couple of years ago could safely be sent to the shelf of fantastic stories. But no, this is not fantastic, this is 2019.
Neural networks understand what babies want
Researchers from New Jersey have developed a neural network that can distinguish babies' screams from each other and classify them. Tests with more than a hundred (today) children from 3 to 6 months have shown that in the vast majority of cases the neural network correctly understands what the child wants: eat, sleep, change the diaper, attention, feels pain or other discomfort.
Neural networks revive images
Employees of Samsung AI Center-Moscow and specialists from Skolkovo created a system capable of creating his animation using just a few (from 1 to 8) human images (photographs or even portraits). As a result, we can look at the rather real moving faces of Albert Einstein, Merlin Monroe, Fyodor Dostoevsky, and many others. It looks impressive!
Neural networks create photographic images
This year, several neural networks were presented that could quickly turn human sketches into real-looking images (for example, a house in the form of a square and a triangle or a painted smile on a person’s photo).
Moreover, neural networks appeared independently creating indistinguishable from real faces of people, images of animals, vehicles, living quarters and much more.
Neural networks by voice recreate portraits of people
The Massachusetts Institute of Technology continues to amaze. The Speech2Face neural network represented by this institution creates portraits of people only after hearing a sample of their voice. And just look how accurately in most cases the algorithm shows the gender, nationality and age of people. And the faces themselves in some cases are quite pronounced similar to the original.
Neural networks recognize age by eye movement
And at the University of Minnesota, a neural network was developed, which only by the trajectory of the eyes of children, when they demonstrated various images, could correctly determine the age in 83% of cases. True, only children under 3 years old participated in the studies.
Neural networks write “human” texts
At the beginning of this year, OpenAI announced the creation of a neural network capable of writing text (whether it be a news article or an entire story), indistinguishable from human articles and works. Fearing the ungodly use of the program to create false news notes, the company did not present this neural network to the general public.
Neural networks create false movements of people in the video
The developers at Facebook AI Research taught their neural network to recognize a moving person in a video, replace everything on the video except for the recognized object, and even add new movements to the person in the video. Moreover, a “captured" video image of a person allows a neural network to be controlled using a keyboard, as in a computer game.
Neural networks cancel photoshop
The nightmare of many has become a reality - a neural network has appeared, able to see if the image has been processed in Adobe Photoshop, and then recreate the original image. So far, the program defines only one (though the most popular) tool “Face-sensitive Plastic”, however, the creators of the neural network believe that in the near future no image editing will go unnoticed.
Neural networks will decide what to offer you to eat
McDonald's acquired Dynamic Yield, a company that develops neural networks for personalized advertising. So, perhaps, in the near future, they will offer you food, from the acquisition of which with a high degree of probability it will be very difficult for you to refuse.
Neural networks come up with new sports
Aren't you a fan of a particular sport? Perhaps, in the near future, neural networks will be able to come up with a new sport that you will like. Thus, AKQA , using its neural networks based on 7300 rules from 400 other sports, was able to create a new Speedgate sport . You can familiarize yourself with the basic rules of this game from the video, in which you can also see how the creators of the neural network play Speedgate.
Neural networks write music
For several years now, there have been reports that neural networks are writing music in one style or another. At the beginning of this year, Yandex introduced a neural network that could write a play for a symphony orchestra with viola. Don't like the classics? Then, perhaps, you will like the neural network from Dadabots , which live on the YouTube channel non-stop composes works in the style of death metal.
Neural networks create alcohol
Developers from Fourkind and Microsoft developed a neural network that created a new whiskey brand for the Mackmyra distillery in Sweden. In this case, more than a hundred parameters were taken into account - from the ingredients and production methods to the peculiarities of insisting the resulting drink.
What about personalization?
A significant part of a person’s life takes place on the Internet, in a variety of social networks. It is not surprising that the algorithms from Facebook, Instagram, YouTube, Google, Amazon, Twitter, etc., are known to many people almost better than themselves. And this direction will only develop. Is it bad? It’s hard to say for sure.
But it is likely that we can expect a future where each of us will write our own music, create pictures, compose stories, even offer certain foods and unique drinks. The same news for different people will be heard in a different way. One person will see dry statistics in two lines, the other - a colorful description of a process in the form of a long read, all depending on everyone’s preferences.
By the way, even movies and TV shows can also become personalized by adding the magic of technology. For example, Netflix is already experimenting with stories that depend on the decisions and actions of the viewer. And if you suddenly want to see other actors playing roles in the film? Neural networks here are already starting to come to the rescue. DeepFake technologies are getting better every year and soon the faces, bodies, clothes of any personalities in the video can be replaced in a few minutes.
For example, you can take a look at the scene from “Terminator 2: Doomsday” in which Arnold Schwarzenegger was replaced by Sylvester Stallone.
And this is not all the events associated with neural networks, only this year. Given the above news, it is not surprising that many governments are increasingly paying attention to issues related to artificial intelligence. So, on June 8 of this year, representatives of the G20 countries for the first time signed a document that contains principles for working with artificial intelligence.
It can be confidently argued that this area will develop even more rapidly, since no one wants to stay behind the train gaining momentum. For example, in Russia, at a meeting with the President on the development of technologies in the field of artificial intelligence, it was said:
... develop solutions that can ensure superiority of [artificial intelligence] over humans in special tasks. And by 2030, we must ensure human excellence in a wide range of tasks.