The essence and principles of AI (Artificial intelligence)

The term “artificial intelligence” (AI) was first sounded in 1956 at a conference in Dartmouth, but only in the last decade it began to actively develop. Now we see only the first significant glimpses of its potential and applications. The main task of AI is to perform tasks originally intended for human cognition: pattern recognition, forecasting and making complex decisions.

Algorithms can perceive and interpret the world around us, and some believe that they will soon be able to sense emotions, compassion and create. Although the dream of AI is completely identical to the human mind, it is still very far away.

The turning point in the development of computer technology has become “deep learning” - an architecture based on the principles of the functioning of the human brain, neurons and the connections between them. Such systems can consist of thousands of layers, billions of parameters and analyze a huge amount of variable data. However, unlike the human brain, their development is based on the mathematical choice and recognition of patterns from data arrays.

To enter the initial parameters can be used any type of information system: images, sound segments or calculations by credit card. After processing, artificial intelligence provides a solution or prediction. For example, what words are spoken on the record, whether the transaction is fraudulent or further market behavior.

The breakthrough was promoted by the “data explosion” coming from the Internet and related to the activities, intentions, preferences of people. While the human mind focuses on the most obvious links between incoming information and results, machine learning algorithms, by analyzing big data, can reveal so subtle correlations that we cannot even describe them logically.

Combining hundreds or thousands of layers provides an advantage over the most experienced experts. AI algorithms are now superior to people in recognizing speech and individuals, various games, and diagnosing certain types of cancer based on MRI results.

However, for analysis, they need a lot of data for training and huge computational power to process all this. Modern AI also functions only in specific areas and is not able to generalize or use common sense. For example:

AlphaGo, who defeats world champions in the ancient Go game, does not play chess;

algorithms trained in determining underwriting loans cannot distribute assets.

Despite the existing limitations, under the influence of computer technology, artificial intelligence passed from the era of discoveries to the era of realization. At the moment, the center of gravity has already moved from research laboratories to real-world applications. Companies and governments are actively exploring this area, looking for ways to use modern AI capabilities in their operations to squeeze the maximum performance out of this innovative technology. The potential of artificial intelligence increases and the fact that it can be used in almost any field.