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News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Долгосрочные тенденции развития сектора массовых коммуникаций

Форсайт. 2012. Т. 6. № 4. С. 6–18.
Kachkayeva A., Kiriya I.

The paper is part of a large foresight study carried out by the authors at the HSE Institute for Statistical Studies and Economics of Knowledge for the Russian Ministry of Telecommunication and Mass Communications. It is important that mass communication, with its virtual product is related to two other sectors: telecommunications and information and communication technology. Technological transformations affect these three industries alike; the growth of bandwidth, convergence of terminals and growth of their computational performance are transforming products and markets in all three. Long-term trends in these markets have been well defined by a range of industrial experts. The conclusion of the paper provides recommendations for the revision of public policy.

The authors note only a few new tendencies in services and products. However, wide diffusion of these trends due to cheap technologies will lead to radical changes in the sector. New markets will appear as a result of expansion and adjustment of industrial relations between agents, previously independent of each other. Key trends are the abandonment of linear-media in favor of "user-controlled" consumption, with a growing amount of content produced by the user, and the spread of social interactions. The trends are interrelated and determine the transformation of business models, the sources of income, and the value of goods produced by the media industry. The most negative trend according to experts is "deprofessionalization" of content, which poses a risk for institutionalized forms of media. With such turbulent changes regulation in mass communications will inevitably undergo transformation. Henceforth it will not be able to rely upon content filtering and setting quotas. Instead the regulation should be built upon enabling a diversity of information sources to create the news agenda at the request of the audience.

Research target: Philology and Linguistics
Priority areas: economics sociology humanitarian
Language: Russian
Full text
Keywords: журналистикамедиа-рынокинформационные технологииInformation technologiesпрогнозированиемассовые коммуникацииконтентcontentсценарииmass communicationmediamarketдолгосрочные тенденциисовременное состояние массовой коммуникациисредства массовой информации
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