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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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Кто и как производит будущее (новая философия общего дела А.А. Фёдорова)

Слово.ру: балтийский акцент. 2024. Т. 15. № 4. С. 8–24.
Tulchinskii G. L.

The article presents a reflection on Alexander Fedorov's project aimed at analysing the future and the model of production. This model facilitates the correlation of factors related to subjectivity and sociality within the process of future production. Notably, the work emphasizes Alexander Fedorov's assertion regarding the pivotal role of children and childhood and the typology of actors involved in this process. The proposed concept and model establish a fertile ground for further interdisciplinary research. From the perspective of social semiotics and pragmasemantics, shaping the future emerges as a form of meaning-making and institutionalization, unfolding through a series of interfaces that enable interaction across sociocultural practice contexts. In this framework, subjectivity is identified as a crucial interface for such interactions. Moreover, a comparative analysis of natural and artificial intelligence underscores the complex potential inherent in this research problem. While human beings possess advantages stemming from bodily experience, sexual dimorphism, and other forms of vitality over artificial intelligence, the future is largely grounded in this vitality, exemplified by the essence of childhood. Consequently, the question of management possibilities and the ethical dimensions of future production, as well as the balance between permissible and impermissible means employed, becomes particularly salient.

Research target: Social Sciences Humanities
Language: Russian
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Keywords: детствосубъективностьбудущеесмыслообразованиепрагмасемантикапроизводство будущего
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