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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Выступления и комментарии к докладу Р.М.Энтова

С. 275–286.
Bessonov V. A.

Two problems associated with the adequacy of traditional methods for describing the national economy as an object of study are considered. The first of them is due to the fact that technological progress leads to a decrease in the degree of representativeness of traditional macroeconomic indicators, i.e. to reduce the degree of representativeness of generally accepted methods of describing the economy. The second problem is related to the erosion of the borders of the national economy in connection with the processes of globalization, which leads to the fact that the national economy is gradually losing its representativeness as an object of study.

Language: Russian
Full text
DOI
Keywords: российская экономикатехнологический прогрессэкономическая статистикаeconomic statisticstechnological progress Russian economy
Publication based on the results of:
Intersectoral interactions, intangible assets and human capital as factors of labor productivity growth (2019)

In book

Истоки: экономика — «мрачная наука»?
Истоки: экономика — «мрачная наука»?
М.: Издательский дом НИУ ВШЭ, 2019.
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