What is a neural network and how does it work?

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Today, neural networks are very popular and are used in many programs. Neural networks are one area in the development of artificial intelligence systems. Not the only one, but very popular because of its entertainment capabilities. In general, neural networks work according to a mathematical model that somewhat resembles the functioning of our nervous system. Neurons in our body draw information from the environment or organism, evaluate it, think about how to respond, and remember it.

In fact, the principle of operation of neural networks, which we are now talking about, is close to the human nervous system. The human brain consists of billions of neurons, which are connected in a network and are able to transmit information through low-power electric charges. Each neuron or digital processor in the neural network is a kind of neuron that has many inputs for gaining information and one for output. How multiple incoming signals are formed into an outgoing one is determined by the mathematical algorithm. And the neural network, which is a system built from many neurons, is able to perform very complex tasks of collecting information and analyzing it.

To perform these tasks neural networks consist of layers. For example, the neural network can use one algorithm for input representation processing and then transfer him to the following layer for processing by another algorithm which will give more high-level understanding and so on. In the case of the recognition of images, for example, the first layer of a neural network can analyze pixel brightness and then transfer it to the second to define the edges and lines formed by strips of similar pixels. In the case of speech recognition, the neural network cuts the heard speech into short fragments which then transfer to vowels.

Neurons of one layer of the neural network work in parallel mode. Changing the number of layers and the number of neurons in the layers allows you to flexibly or as efficiently as possible adjust the total parallel-sequential amount of calculations for the features of the computer technology used.

Among the main applications of neural networks are forecasting, decision-making, pattern recognition, optimization, and data analysis. Neural networks are also used in modern speech recognition and synthesis systems, as well as image recognition and processing. They are also used in robotics and modern navigation systems. In fact, their ability to learn makes them very smart. Neural networks can recognize deeper, sometimes unexpected patterns of data. And they can’t study until you throw in them enough data. They need large volumes of information to understand it, to pass through layers and to try to classify. Then they can compare the classifications to real answers.

Today neural networks are applied in many spheres as medicine and healthcare (for example, they are used to diagnose diseases), IT (speech recognition), economics, trading, geology and even entertainment. So, there are neural networks which play against European and world champions in cybersports. Who knows, maybe it will be possible to play online casino games such as Woo Casino login together with neural networks one day?

So, neural networks give computers the ability to understand the human world and to draw reasonable conclusions about it. And the most important thing about it is that neural networks already help people and play a big role in our lives even though we don’t know much about them. Every day we open many Internet pages with captcha recognition of information and many people use voice input mechanisms. Today neural networks are able to perform many tasks for people and surely have potential.

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