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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Искусственный интеллект и стратегические задачи повышения международной конкурентоспособности в современных условиях

Государственное и муниципальное управление. Ученые записки.. 2022. № 4. С. 240–246.
Filosofova T. G., Матюшина Е. А.

such areas of company development as high technology have become increasingly popular. Companies are increasingly using blockchain, augmented reality, robotics, artificial intelligence, and other innovations in their activities. It is worth noting that there are already many studies aimed at studying the relationship between high technology and the growth of the company's performance. This paper investigates the impact of the use of artificial intelligence on improving the competitiveness of the company. For a more accurate understanding, the Alphabet case was taken. The work used company data before and after the introduction of artificial intelligence. In addition, data from leading companies in the high-tech market for a certain period of time were also considered to build a regression. Furthermore, we will obtain findings which show the dependence of the company's high competitiveness on the use of artificial intelligence in its activities. Since we will consider the causal factors of such dependence, our results can be useful for novice startups, as well as large market players to understand trends and benefits from the development of artificial intelligence in their enterprise.

Research target: Economics and Management
Language: Russian
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Keywords: конкурентоспособностьинновацииискусственный интеллектinnovationsвысокие технологииartificial intelligencecompetitiveness information technologies
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