Nowadays, artificial intelligence is still not created. If we talk about something like artificial intelligence, we rather mean neural webs. Many historical figures who invented some innovative ideas in computers said that we can create any algorithm, but we can not make computers think like people (e.g., Ada Lovelace, daughter of George Bayron). So, in that text I will equate definitions of neural webs and artificial intelligence. In our time people use neural webs to solve problems with too many different variables, when humans can not create concrete algorithms. For example: we need to create a program that will tell us if the picture is with a cat or not. It is hard to find default ways to solve it. If we try to do this, firstly we may think that we need to detect cat ears. For computers that is a group of pixels without big changes in color, but not always. There can be spotty cat fur, and that algorithm will fail. So, we need to create a universal algorithm that will learn by itself where a cat is and where it is not. Neural webs choose criteria to solve the problem by themselves.

Today many industries use artificial intelligence in various ways. For example: wearable artificial intelligence biosensor networks use AI (artificial intelligence) to increase efficiency of disease diagnostics, to make biosensor networks more cost- effective and accurate point-of-care diagnosis by finding hidden patterns in biosensing data and detecting abnormalities (Zhang et al., 2022).

Artificial intelligence has unlimited potential in the future. It can already solve hard problems that humanity could not solve without this technology. In the future there are prospects in solving small business problems, conflicts between countries, researching space and quantum physics.

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