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Необходимость защиты научного приоритета советских и российских ученых при преподавании ИИ-дисциплин
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Abstract. The paper draws attention to the injustice in the distribution of scientific priority of some scientists who have ever worked in the field of artificial intelligence. The need to restore justice and protect the scientific priority of Soviet and Russian scientists through lectures and publications of scientific and pedagogical literature by scientific and pedagogical workers is pointed out.
In book
Пермь: Пермский государственный национальный исследовательский университет, 2023.
Klementiev A., Kasatkina A., Legal Issues in the Digital Age 2026 Vol. 7 No. 2 P. 40–60
The article examines specific aspects of artificial (machine) intelligence in dispute resolution in state and arbitration courts . Drawing on legal research methods and data from artificial intelligence science, the authors propose a significant obstacle to its application in the legal sphere is the so-called “hallucination problem,” i .e ., the generation of false data by machine intelligence programs ...
Added: July 14, 2026
Stoyanova O., Окусков И. С., Бизнес-информатика 2026 Т. 20 № 2 С. 81–93
The integration of artificial intelligence (AI) into information technologies is reshaping competency requirements for IT specialists. However, AI competency penetration into the early phases of the Software Development Life Cycle (SDLC) – requirements analysis and planning – remains underexplored. Existing studies either rely on static competency models lacking empirical validation or analyze the labor market ...
Added: July 5, 2026
Selskiy A., Snegirev A., Колбин Е. И. et al., В кн.: Цифровая клиентоцентричность. Как современные технологии помогают компаниям и государству сделать шаг навстречу потребителям.: М.: ИСИЭЗ ВШЭ, 2026. Гл. 2 С. 71–142.
The second chapter of the monograph analyzes the current megatrends of customer centricity, shaped by digital technologies and transforming the approaches of companies and government bodies to customer and citizen engagement. Based on semantic big data analysis (using the iFORA system) and expert interviews, the authors identify four key megatrends.
The first megatrend, proactive engagement and personalization, describes ...
Added: June 26, 2026
Капитонов И. А., Москвитин О. А., Современное профессиональное образование 2026 № 5 С. 55–57
В статье рассматривается проблема институциональной неготовности российской системы образования и науки к массовому распространению генеративного искусственного интеллекта. Авторы фиксируют парадоксальную асимметрию: студенты и аспиранты активно применяют ИИ для делегирования текстопроизводства, тогда как научно-педагогические работники в большинстве своём не используют его как исследовательский инструмент. Показано, что в основе этой асимметрии лежит не «злой умысел» участников, а ...
Added: June 23, 2026
Kosmarsky A., Напреенко И. В., Journal of Cultural Economy 2026 P. 1–4
Added: June 23, 2026
Pruzhinin B. I., Afanasov N., Буданов В. Г. et al., Вопросы философии 2026 № 5 С. 5–35
In December 2025, the Institute of Philosophy of the Russian Academy of Sciences hosted an international roundtable on the topic “Social Programming as a Methodological Tool of Network Self-Organization: Problems and Trends”.
The roundtable was organized by the journal “Voprosy Filosofii” and representatives of the research project No. 25-28-00707, “Social Programming as a Problem of Network ...
Added: June 18, 2026
Romanova T. V., Бинштейн М. М., Медиалингвистика 2026 Т. 13 № 1 С. 28–50
В данной статье противопоставляется узкое и широкое понимание содержание термина ИИ, фиксируется история его появления. Функционирование термина ИИ рассматривается в сопоставительном аспекте по данным российских и китайских медийных источников: ...
Added: June 14, 2026
Barkhatova L., Социологические исследования 2026 № 5 С. 71–83
The article conceptualizes the methodological potential of hyperlink network analysis as a tool of empirical reconstruction of social interaction through digital traces. Using the partnership network of Russia’s artificial intelligence (AI) ecosystem as a case, the paper presents an original analytical framework for translating technical hyperlink data into sociological categories. The study describes a full ...
Added: June 12, 2026
Butorova A., Bobakov V., Sergeev A. et al., European Physical Journal: Special Topics 2026 P. 1–19
This paper presents a review of artificial intelligence (AI) methods for failure prediction in data center cooling systems, with a focus on the integration of digital twins (DTs), physics-informed learning, and graph-based models. Positioned within complex network science, this review addresses a limitation of conventional graph approaches—their reliance on pairwise connectivity—whereas real-world failures often arise ...
Added: June 10, 2026
Orazmetova Dilara, Zhohov A., Vasilieva Sofia et al., , in: 2026 28th International Conference on Digital Signal Processing and its Applications (DSPA).: IEEE, 2026. P. 1–5.
The article presents a software-hardware approach for an intelligent camera trap designed for the automatic detection of stray animals in a video stream using digital image processing methods and neural network algorithms implemented on an embedded computing platform. The system architecture, video signal processing algorithms, features of adapting a neural network model to conditions of ...
Added: June 7, 2026
Seul: PMLR, 2026.
Added: June 4, 2026