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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Типологизация стратегий внедрения искусственного интеллекта в образование: Российская Федерация, Европейский союз, Китайская Народная Республика

Вып. 9 (92): Современная аналитика образования. M. : Higher School of Economics Publishing House, 2025.
Zagranichny A., Koroleva D.
Editor-in-chief: Novikova M.

The analytical report provides a comparative analysis of strategies for integrating artificial intelligence (AI) into the education systems of the Russian Federation (Russia), the European Union (EU) and the People's Republic of China (China). The study is based on an analysis of key strategic documents governing the development of AI and the digitalization of education in each of the regions. Significant differences in approaches have been identified: China is implementing a comprehensive, ecosystem model, where AI transforms both personnel training and the educational process itself; the EU focuses on ethical and legal regulation and the development of competencies for the safe use of AI; Russia considers AI primarily as a tool for data analysis, management and administrative burden reduction, with an emphasis on training personnel for the market.Based on the analysis, a typology of government strategies is proposed in three priority areas: "education for AI" (personnel training), "AI for education" (integration into educational practice) and "AI in education" (educational system management). It is concluded that a proportional combination of all three elements is the key to a balanced and effective policy for introducing AI into education.The report was prepared as a result of a joint research conducted by the HSE University and TSPU within the framework of the "Mirror Laboratories" project.

Research target: Education
Language: Russian
Full text
Text on another site
Keywords: государственная политикаобразованиеискусственный интеллектмежстрановой сравнительный анализцифровизация образованияPublic Policy comparative analysis artificial intelligence digitalization of education Education
Publication based on the results of:
AI в образовании (AIED): диффузия инновации, условия реализации и потенциал трансформации (2025)
Типологизация стратегий внедрения искусственного интеллекта в образование: Российская Федерация, Европейский союз, Китайская Народная Республика
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