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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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Сайнс-арт и китч: компьютерное искусство на основе больших языковых моделей

Коммуникации. Медиа. Дизайн. 2024. Т. 9. № 2. С. 45–64.
Milovidov S.

Today the emergence of large language models has led to the spread of popular graphic neural network generators (DALL-E, MidJourney, Stable Diffusion, Kandinsky, etc.). There was the reason of the widespread implementation and democratisation of artistic practices. The article analyses the processes of disappearance of the boundaries between art and kitsch in relation to computer art. The article considers the kitschisation of generative neural network graphics and the ways of overcoming it by means of appealing to scientific knowledge and the art direction of seins-art, as well as new artistic practices and contradictions arising in this connection.

Research target: Art History
Language: Russian
Full text
Text on another site
Keywords: искусственный интеллекттрансгуманизмtranshumanismнейросетиartificial intelligencescience artkitschкитчposthumanismПостгуманизм в искусствесайнс-артбольшие языковые моделиlarge language model (LLM)neural network
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