The "oil" of the modern economy and the war for personnel

    All IT giants like Google or IBM have their own laboratories where scientists, engineers and analysts work on the monetization of artificial intelligence. In 2017, MTS joined the interest of Western colleagues and also opened a unit that develops and implements products based on AI technologies. What is happening in the “intelligent” laboratory and how will it change the life of subscribers?

    I talked with the head of the AI ​​development department at MTS Arkady Sandlerwho has behind him the experience of creating various projects in the field of machine learning, in particular in the field of electronic commerce. In an interview, Arkady told why AI is a key technology of our time, what awaits us in the society of a personalized product, and how to pump your startup using MTS.

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    - Arkady, how do you think the current definition of artificial intelligence sounds?

    - Artificial intelligence is a class of systems that automatically performs the functions inherent in humans. At the same time, a clear definition of the word "intelligence" cannot be given in relation to a person, therefore, only the "rationality" of actions possible for a machine is emphasized here. AI intersects with many other classes of systems, and it is still difficult to find an autonomous definition for it. Now we are already sharing systems for working with big data and systems that automate human functions. Many technologies can be used inside the systems, the question is only in their application in each specific case, moreover, each task can be implemented in different ways. For example, machine learning as a toolkit is used in various fields and is only an AI sub-industry.

    - How difficult is it to develop and “train” a neural network, what resources are needed for this?

    - Now, students of specialized specialties can engage in training neural networks, especially since universities are increasingly connected with market demands, and more and more programs for working with data and machine learning are appearing.

    In the topic of AI, the key factor in measuring the scale of work is the availability of data that is collected, labeled and can already be used to train the neural network. In an industrial format, only a team of specialists can process a large amount of data.

    - Where did the hype come from around AI?

    - I would use the metaphor that data is now the "oil" of the modern economy. Data ownership is a critical power factor in the global market. Therefore, Silicon Valley giants are investing billions in AI and opening up new units to work with data. In the coming years, large technology companies will fight for personnel who work with data and machine learning, and develop areas of work with AI, for example, from the point of view of forecasting and automation of business processes.

    “If there is enough data, can artificial intelligence learn everything?”

    - Rather, if there is a sufficiently large amount of data, you can build a system that will master this skill and be able to perform it “humanly”. What matters is the quality of the data. But in the concept of AI, there are two areas of data application - it is general AI and narrow AI, and now the latter dominates the market. General AI is not a very achievable idea of ​​a comprehensive and global AI, which will really be able to do everything and resemble the human mind.

    - This has already generated a phobia that AI will soon deprive us of work. What changes can AI really bring to the labor market?

    - Each industrial revolution, and we are now inside another of them, leads to a significant restructuring of the labor market. Naturally, the widespread introduction of AI-based systems will and will lead to this restructuring. Some professions die off, but new ones also appear. Now there is hardly a factory where cars were manually assembled. Humanity does not seem to suffer from this, but rather has more and more opportunities to consume and fulfill itself. AI-based systems free some people from routine work.

    People can engage in creativity, go into creative spheres and fulfill themselves, and not spend 8 hours a day on mechanical actions. This is initially the wrong paradigm - to drive living people capable of various actions, independence and creativity into a system of elementary tasks. Therefore, it is worth looking at the changes extremely positively.

    - In what area can you find an urgent task that AI can solve?

    - Usually, when an initiative related to AI is created, for example, a startup, we think in an abstract way. Imagine that you have at your disposal a limitless army of free labor, but each of these people is capable of performing only one cognitive function. For example, to read the text, and based on the content, press one of a number of buttons. It is worth presenting - and immediately there is a task for this army. Good target search exercise.Now, if you are a businessman and understand where you are breaching - and this is precisely the area that AI can patch - then you can open a startup.

    - Is artificial intelligence capable of self-learning?

    - This question requires about a month of scientific discussion. AI is capable of learning. The ability to self-learn in understanding a person is, to put it mildly, exaggerated. But there are areas where this is possible, if we talk about narrow AI, not general.

    - Turning to a recent experiment with the publishing house of the first book of neuro-poetry , I would like to ask - where do the ethical boundaries of using AI lie, if any?

    - If the network writes poetry no worse than Pushkin, then the ethical question arises not to the network, but to the author of the experiment. Ethics is the prerogative of man, while the system only imitates his cognitive functions. In my opinion, in the era of narrow AI, ethics and AI do not intersect in any way, and the true boundary of ethics lies next to the “culprit” of the experiment.

    - What does the AI ​​unit at MTS do?

    - We conduct applied research in the field of artificial intelligence and develop products - for example, smart bots or products in the medical and legal fields. There is also room for purely scientific cases, we are now actively cooperating with universities and are open to joint projects in the field of education. These will be the intersection points of scientific and applied interests. In addition, this is a good opportunity for students to immerse themselves in the field of urgent tasks for AI.

    - What are the specific tasks facing the AI ​​team as part of the company's requests?

    - A modern company is full of ways to use AI systems, and we are just exploring new ways. We receive tasks from the customer service department, and we help in servicing subscribers, we also developed a robot for a contact center and invent ways to simplify the processing of documents for our lawyers. In general, we optimize the work of units where we eliminate the human factor and make results more effective.

    - And how will AI change the product directly for the client?

    - Having studied the consumer, AI makes the product more personalized. In general, personalization of consumption is the future we enter into thanks to developments in AI. This frees us and allows us to be creative in everything, including consumption, which means that it takes us away from industrial goods to the side of copyright. We are waiting for a boom of independent entrepreneurship, partly this is already happening. We like bread from a small bakery rather than from a supermarket, clothes of a local designer, craft beer and coffee from an eco-plantation. Personalization will definitely defeat the bare practicality of industrial products.

    - In the framework of the AI ​​department, did you cooperate with such independent entrepreneurs? Did you share technical developments?

    - We are constantly working with startups as part of the acceleratorMTS Startup Hub , which selects the most interesting projects in our opinion to assist in development and cooperation. Together we make pilots and, of course, mutually enrich knowledge. We are particularly interested in projects related to the field of Natural language processing (NLP) - this is one of the basic families of AI technologies, and we are accumulating high expertise in this area. But overall open to any opportunity to collaborate in AI.

    - Now you are preparing for a project with the HSE Business Incubator - what awaits the participants of AI Startup Accelerator , which will start in the near future?

    - We will advise young startups in the field of AI as experts. MTS is ready to take the most interesting of them into a pilot. We are ready to take promising startups under the wing, give them the opportunity to develop, so that they, in turn, can move various industries.

    Special thanks to Marina Morozova for the opportunity to talk and help in preparing the interview.

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