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Слабый vs Сильный искусственный интеллект
Информатизация и связь. 2020. № 1. С. 81–88.
It is proposed to distinguish between the traditional, so-called, weak, artificial intelligence (AI) and strong artificial intelligence, or artificial general intelligence (AGI). The latter is not considered as the evolutionary stage of the development of AI, but something else related to the construction of an informal and non-causal phenomenological space, as a kind of opposite to AI. AGI is determined by inverse problems solving on topologies, using analogies of quantum physics and optics, connecting aspects of relativistic theory. It is noted that the AGI continual power is tens of orders of magnitude greater than the AI power, however, for its release, special integration of the both, and direct inclusion of human in the process is required. Already, elements of AGI are helping to accelerate the collective creative process many times over.
Seul: PMLR, 2026.
Added: June 4, 2026
Москвитин О. А., Лебединский В. И., В кн.: Цифровое общество: состояние, проблемы, перспективы.: [б.и.], 2026.
В статье анализируются правовые и организационные основы функционирования государственных информационных систем «Антикартель» и «ТАРИФ», созданных Федеральной антимонопольной службой России в рамках цифровой трансформации контрольно-надзорной деятельности. Исследуются возможности использования технологий искусственного интеллекта для выявления антиконкурентных соглашений и обеспечения эффективного тарифного регулирования. Выявляются отдельные возможные правовые риски и направления совершенствования использования ГИС. ...
Added: June 2, 2026
Silakov D., Системный администратор 2026 № 3 С. 28–33
В статье про платформы для разработки открытого ПО в Китае мы рассказали про GitCode – молодой проект, позиционируемый как площадка для разработчиков со всего мира. Сейчас на GitCode размещаются проекты, созданные в КНР, но некоторые из них уже известны и на международной арене. Помочь открытым проектам в становлении, развитии и расширению аудитории призван фонд OpenAtom ...
Added: June 2, 2026
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
Kazimirov D., Rybakova E., Vitalii V. Gulevskii et al., IEEE Access 2025 Vol. 13 P. 20101–20132
The Hough (discrete Radon) transform (HT/DRT) is a digital image processing tool that has become indispensable in many application areas, ranging from general image processing to neural networks and X-ray computed tomography. The utilization of the HT in applied problems demands its computational efficiency and increased accuracy. The de facto standard algorithm for the fast ...
Added: May 28, 2026
Kazimirov D., Vitalii Gulevskii, Kroshnin A. et al., Mathematics 2026 Article 1136
The Hough transform (HT) is widely used in computer vision, tomography, and neural networks. Numerous algorithms for HT computation have been proposed, making their systematic comparison essential. However, existing comparative methodologies are either non-universal and limited to certain HT formulations, or task-oriented, relying on application-specific criteria that do not fully capture algorithmic properties. This paper ...
Added: May 28, 2026
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to
implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained)
weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Jin S., Komarov M. M., Scientific Reports 2026
Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...
Added: May 21, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Федоров Н. С., Финансовый журнал 2025 Т. 17 № 6 С. 99–112
The DCF model is one of the most commonly used models in valuing companies for investment deci sions. Nevertheless, estimating the accuracy of this model remains an important research question. This article presents an assessment of the accuracy of DCF model specifications based on analyzing the variance of fair share prices of companies listed on ...
Added: May 15, 2026
Федоров Н. С., Финансы и бизнес 2025 Т. 21 № 3 С. 34–50
Currently, the role of artificial intelligence is increasingly playing a significant role in various fields, including the increasing role of machine learning in finance. On the other hand, company valuation remains an important part of research due to its difficulty in correctly predicting the accuracy of target stock prices. This study provides an analysis of ...
Added: May 15, 2026
М.: Экономический факультет МГУ им. М.В. Ломоносова, 2026.
В сборнике приводятся тексты лучших докладов участников Международной ежегодной научной конференции «Ломоносовские чтения-2025» (секция экономи ческих наук) «Настоящее и будущее социально-экономического развития: потен циал ИИ и новые вызовы», состоявшейся 9–11 апреля 2025 г. на экономическом факультете МГУ имени М. В. Ломоносова. Материалы сгруппированы по тематическим направлениям. ...
Added: May 12, 2026
Kirsanova E., Pakshin P., Право и экономика 2026 № 3 (456) С. 26–34
The article examines the legal regime of intellectual property created by artificial intelligence. Changes to the existing legal framework towards recognizing artificial intelligence as a legal entity would violate the rationale and fundamental principles of the intellectual property rights system. This article provides an overview of different views on the rationale for granting copyright to ...
Added: April 28, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026