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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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Искусственный интеллект как симулякр смысла

Галактика медиа: журнал медиа исследований. 2025. Т. 7. № 4. С. 154–173.
Малинов С. А.

In recent years, artificial intelligence (AI) has been actively integrated into everyday human life. Its popularity continues to grow steadily, and companies increasingly employ AI to optimize and accelerate workflows. Ordinary users leverage large language models (LLMs) and multimodal AI systems to perform a wide range of tasks, including generating texts, images, and videos; planning their daily schedules; and searching for information, among others. The rapid integration of AI into diverse spheres of human activity gives rise to a number of fundamental challenges such as the simulation of meaning, the substitution of human agency, and other issues that threaten personal identity and autonomy. An increasing number of cognitive and creative functions – such as text generation, decision-making, and reflection – are being delegated by humans to AI systems. Consequently, it becomes critically important to explicitly identify and articulate the problems emerging from human–AI interaction and to develop ethically and cognitively sound frameworks for such interaction. This article examines current trends and key challenges associated with the integration of AI into everyday life. It introduces the concept of “meaning simulation” – a phenomenon whereby AI models function as simulacra of meaning, creating an illusion of understanding, thought, and meaning. The paper proposes a conceptual framework for productive human–AI collaboration and outlines a positive scenario for its implementation. This article will be of interest to researchers and professionals working in artificial intelligence, philosophy of science and technology, cognitive science, as well as to anyone concerned with contemporary technological trends and their social, ethical, and existential implications.

Research target: Philosophy, Ethics, and Religious Studies Media and Communications
Language: Russian
DOI
Text on another site
Keywords: симулякргенерация текстаТест Тьюрингаtext generationязык и речьsimulationssimulacraA. TuringTuring testА. ТьюрингИскусственный интеллектArtificial IntelligenceБольшие языковые модели (LLMs)Large Language Models (LLM)Simulacra of MeaningAI SlopperOrganiprojectionProblems of Artificial Intelligenceорганопроекциясимулякр смыслаИИ слопперпроблемы искусственного интеллекта
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