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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Цифровая трансформация в отраслях обрабатывающей промышленности России: результаты конъюнктурных обследований

Вестник Санкт-Петербургского университета. Серия 5. Экономика. 2020. Т. 35. № 4. С. 628–657.
Lola I. S., Bakeev M.

The spread of digital technologies in the economy changes production processes and used business models. The technologies associated with the fourth industrial revolution, such as the industrial Internet of Things and additive manufacturing, have a significant impact on the production cycle in the manufacturing industry.

Based on short-term and medium-term entrepreneurial opinions and intentions, the work reflects the key aspects of the digitalization process in Russian enterprises, using the method of conjuncture observations and surveys, which supplements the methods of quantitative statistics. On this basis, taking into account the differentiation of the manufacturing industries into low-, medium- and high-tech, a set of trends in the digital technologies development, the industrial participation in digital transformation in the forms of the business processes digitalization and the digitalization of labor, as well as many other important indicators not measured or only partially measured by quantitative statistics is presented. For all the industries, factors hindering digital transformation were identified and ranked.

In general, a survey of managers showed a significant variation in entrepreneurial judgment regarding most aspects of the production digitalization. Despite the fact that the transition to Industry 4.0 is taking place in Russia on the background of rather unfavorable trends in the business climate, the resulting opinions allow us to state that progress is obvious, though the level of immersion into digitalization processes is not yet deep. Consideration of digital activity from the point of industrial separation view, as well as taking into account the classification of industries as low-, medium- and high-tech, allowed us to identify the industrial features of the digital transformation. In particular, it was shown that some technologies, such as the industrial Internet of Things, were predominantly distributed in the medium and high-tech segment, while others, such as 3D printing and RFID tags, were represented in most manufacturing industries.

The main promising areas for continuing research on digital transformation in the Russian manufacturing include expanding the conjuncture observation program by including other industries in it, the development of appropriate composite indicators, an analysis of the relationship between economic indicators and digitalization, a foresight study of the qualitative aspects of digital transformation.

Research target: Economics and Management
Priority areas: economics
Language: Russian
Full text
DOI
Keywords: обрабатывающая промышленностьmanufacturing industryцифровые технологиицифровизацияdigitalizationdigital technologiesконъюнктурные наблюденияцифровая активностьdigital activitydigital investmentdigital strategyconjuncture observationsцифровые инвестициицифровая стратегия
Publication based on the results of:
Monitoring of business climate, economic sentiment and digital activity in the Russian economy (2019)
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