Vice President for Transformation at MTS PJSC Alexander Dmitriev

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Prospects for the implementation and development of generative artificial intelligence (AI) in Russia were discussed by IT industry experts at the conference "Generative AI: presentation of the top 10 companies and cases".

is confident that in a couple iran whatsapp number database of years only the first trial results will appear: "In order for generative AI to reach a good level, we all need to have a slightly different culture in terms of implementing the project as a whole, which has a certain life cycle. Projects like generative AI are not simple. They change key business processes, transform them greatly. In this sense, we need to make sure that people, tools, and processes are ready. For everything to be perfect, we need to start these projects today or tomorrow, and in two years they will be successful. But since we are not starting in large quantities yet, only in a couple of years will we receive some specific events in specific areas, we will learn to do something. And in the next two years we will be able to talk about some successes."

Director of the Competence Center for Organization and Development of IT Production at PJSC Rostelecom Evgeny Ardyshev assessed the entry threshold for generative AI: "The entry threshold for generative AI is slightly above average. Most likely, it will decrease due to the popularization of new solutions. But when we talk about use within corporations, we want to work correctly with data, here the entry threshold increases, other solutions are needed, we cannot always use existing ones. At the moment, there is faith in the direction, but it takes time to develop."

Alexander Logachev, Director of Digital Technologies at AlfaStrakhovanie, explained why it is difficult to implement generative AI in two years: "There are factors that greatly hinder the development of generative AI. First of all, time. It is difficult to restructure a business in two years. I would compare generative networks with the advent of computers. There was a time when they did not exist. People coped well with paper documentation. But then computers appeared with unknown mice and keyboards, on which it is unclear how to work. But when people learned to use computers, productivity increased. Here, most likely, generative AI will play the same role. It will be an assistant in routine tasks. But in order for this assistant to be implemented, an ordinary person or business needs time to understand all this. And the entry threshold will be very important here. Now it is very high, because generative networks are trained, they solve many problems. But there are still problems that need to be solved. But faith in generative AI is high."

Vice President of Information Technology at the FESCO transport company Dmitry Surovets used an example to explain how generative AI can be gradually implemented: "We have infrastructure limitations at the port in Vladivostok. Historically, it has an unusual shape. We have to live with this. But at the same time, we want to increase throughput, despite the limitations. This can be done by adding people who make decisions, faster and more correct ones, or by using AI. We can add people and reward them with an assistant who makes decisions. This way, we can plan when, where and what cargo should be, thereby reducing the burden on the client in terms of cost and on us - in terms of the occupancy of the port itself."