Already today, one way or another, we are immersed in the world of "weak AI" (in English it is called ANI - artificial narrow intelligence, "narrow artificial intelligence"). Artificial intelligence can refer to anything from computer programs for playing chess to speech recognition systems, such as the Amazon Alexa voice assistant, which can understand speech and answer questions.

Any of our smartphones is just a “weak AI city” with speech recognition systems and a navigation system with real-time routing, a spam filter system and a smart key typing system with word prediction. Weak AI systems book tickets for us and suggest vacation travel options. Weak AI works in warehouses, logistics and transport. In the maritime industry, artificial intelligence is able to process data from thousands of ship manifests and records filled out every day around the world in order to optimize port loading and ultimately reduce shipping times. Apps like Waze use traffic data to predict how much traffic will be on a particular road at a particular time of day. In our car, for example, an ABS system and other driving assistance systems, a fuel injection system are installed. The autopilot, which has long been a familiar thing for pilots, has finally come to the most massive industry in terms of the number of people involved in it, the road transport industry. For example, quite a long time ago, Mercedes-Benz presented a prototype of a robotic truck that can independently, without the participation of a driver, move along the highway in intercity conditions. For Germany, this is, in general, quite relevant - autopilots will significantly simplify the work of truck drivers, due to purely human errors and fatigue that most road accidents occur, since purely technical problems have long since faded into the background with operation of modern trucks. For carrier companies, this will most likely allow lobbying for an increase in the working day for drivers: now in Germany there are very strict rules on the time that a driver can actually spend behind the wheel of a car. By the way, along with the robotization of the car, in the new heavy-duty truck, Mercedes also solves a lot of related problems of the industry: for example, the eternally dangerous “dead zones” in the truck’s field of view are eliminated: with the help of stereo cameras and radars, most traffic objects are confidently detected even on distance of 70-100 m, and machine intelligence has time to adequately and quickly respond in case of danger, even from the most unusual direction. In addition, robot trucks will be able to share traffic information over Wi-Fi at a distance of up to 500 m, which will allow them to receive a lot of information not only through their own sensors, but also through cameras and radars of other road users. It is worth noting that the example is far from unique - such cars are now being developed with varying degrees of success around the world, including in Russia. AI in industry Banks use artificial intelligence systems in insurance activities (actuarial mathematics), when playing on the stock exchange and managing property. Algorithmic trading involves the use of sophisticated artificial intelligence systems to make trading decisions faster than the human body is capable of. This allows you to make millions of transactions per day without any human intervention. Automated trading systems are commonly used by large institutional investors. With their help, stocks, currencies and many other goods have long been sold and bought. Pattern recognition methods (including both more complex and specialized ones, as well as neural networks) are widely used in optical and acoustic recognition (including text and speech), medical diagnostics, spam filters, air defense systems (target identification), and also for ensuring a number of other tasks of national security. For example, artificial neural networks, such as Concept Processing technology in EMR software, are used as clinical decision systems for medical diagnostics. Another application of artificial intelligence is in human resource management and recruiting. There are three ways to use AI for human resource management and hiring. AI is used to review resumes and rank candidates according to their skill level. It is also used to predict a candidate's success in given roles through job matching platforms. Finally, AI is being used to create chatbots that can automate repetitive communication tasks. From 2016 to 2017 consumer goods company Unilever used artificial intelligence,to display all entry level employees. Unilever's AI used neuroscience-based games, recorded interviews, and analysis of facial and speech cues to predict a candidate's success in the company. Unilever partnered with Pymetrics and HireVue to create a new AI-based analytics system and increase the number of applicants considered from 15,000 to 30,000 within one year. Unilever also reduced application processing time from 4 months to 4 weeks and saved over 50,000 hours of recruiter time. AI in medicine Computer game developers use AI to varying degrees of sophistication. This forms the concept of "Game artificial intelligence". Common tasks for AI in games are finding a path in 2D or 3D space, simulating the behavior of a unit, calculating the right economic strategy, etc. In 2018, researchers at Cornell University created a pair of generative adversarial networks and trained them on the example of the DOOM shooter . During the learning process, neural networks determined the basic principles for building the levels of this game, and after that they became able to generate new levels without the help of people. Various AI tools are also widely used in security, speech and text recognition, data mining, and email spam filtering. Applications are also being developed for gesture recognition (understanding sign language by machines), individual voice recognition, global voice recognition (from many people in a noisy room), facial recognition for interpreting emotions and non-verbal cues. Other applications are robotic navigation, obstacle avoidance, and object recognition. In general, one can continue talking about today's applications of robots and systems of weak artificial intelligence for a very long time: automated ticket offices instead of cashiers and vending machines instead of sellers, cleaning robots instead of Tajik janitors and warehouse robots instead of loaders and a captain. Almost any branch of the human economy, which can be represented by a simple plot "digging from the fence to lunch", can be robotized in the near future (of course, if it is economically profitable) and equipped with weak artificial intelligence systems, which, in most cases, allow you to control robots no worse than pilots, drivers, combine operators or tractor operators. CONCLUSION As we can see, artificial intelligence already exists in our time and is successfully used in the most unexpected places for a wide variety of purposes. Yes, it is not the same as science fiction writers described it to us, but who knows what will happen next? AI in everyday life From the point of view of the authors, we should expect that the use of AI in various forms will only grow, but expecting that we will all be replaced by robots is also at least not very smart. As the history of mankind shows, basically long-term forecasts are based on the realities of the current social system and economy, and they can change beyond recognition over time. Accordingly, the increasing use of both various robots and artificial intelligence in general will noticeably change both technology and the economy - but humanity as a whole will not suffer. Rather, new professions will appear, while the old ones will either disappear or the scope of their application will decrease, but people will not be left without work. But what should be expected is certain breakthroughs in science and technology, due to the growth of both computing power and the ability to model a wide variety of structures and processes. Time will show!