Machines can think for themselves and attack humans. Such scenes have always existed only in science fiction. Due to the latest developments in artificial intelligence, it is very likely that in the future, robots can be created without human input.
A Google project is trying to get two artificial intelligence algorithms against each other, and hopefully there will be such a smart machine in the future.
In the Google Brain Artificial Intelligence Lab, researchers have developed a system called "Generation Against Networks" (GAN). Traditional artificial intelligence uses input to "train" an algorithm that "trains" a particular topic by entering a large amount of information. The knowledge after algorithm training can be used for specific tasks, such as facial recognition. GAN generates new content from these learning messages and creates new images and video content based on an understanding of similar real-life images and videos.
Google's approach is to confront the two algorithms to further improve their "imagination." An artificial intelligence robot creates new content based on the real world it has learned, while another robot points to imperfections and inaccuracies in these creations. This allows the system to create more realistic images, sounds and other original works that are much more realistic than when a robot works alone.
In the future, this process may allow robots to learn new information without human involvement – ​​a process known as “unsupervised learning,†which will be a huge leap in artificial intelligence technology.
Dr. Ian Goodfellow working in Google Mind of "Wired": "If artificial intelligence robot can imagine realistic detail, learn how to imagine the reality of the image and the reality of sound, which will encourage the world of artificial intelligence to understand the structure of the real, You can think of it as an artist and an art critic, generating models that can deceive art critics and let art critics mistakenly believe that the images it produces are real."
Artificial intelligence systems rely on neural networks, which try to simulate the way the brain works to learn. These networks can be used to train to identify patterns of information, including speech, textual data or visual images, which are the basis for the development of artificial intelligence in recent years. They use input from the digital world to learn, such as Google's language translation service, Facebook's facial recognition software, and Snapchat's beautification filters.
However, the process of entering this data can be very time consuming and limited to one type of knowledge. In order to expand the limits of such machine learning, Google has already begun to design interactive artificial intelligence robots.
In February of this year, a team at Google used a game they designed to test whether the antagonistic algorithms would work together or attack each other. These experiments show that artificial intelligence is likely to work together according to the situation. The results of the experiment increase our understanding and control of complex multi-agent systems, such as the economy, transportation systems or ecological health – all of which depend on our continued cooperation.
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