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September 4, 2026
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.
September 4, 2026
‘Hedgehog Versus ‘Relatives: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech
Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.
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.

 

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Replacing Criterion of Creativity with Criterion of Investment for Results Created by Artificial Intelligence

Legal Issues in the Digital Age. 2026. Vol. 7. No. 1. P. 32–48.
Pakshin P.

Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the development of technologies in natural language processing and visual content generation. The development of artificial intelligence determines a revision of established doctrinal approaches in intellectual property. This study aims to provide a justification for the legal protection of results generated using artificial intelligence. The key legal risk in this area is the lack of legal grounds for granting protection to such results under de lege lata regulation. The current “silence” of the legislator regarding objects created by artificial intelligence may exacerbate the problem of legal uncertainty. At the same time, there is a significant risk that artificial intelligence itself will infringe the exclusive rights of third parties. Beyond intellectual property rights, objects created by artificial intelligence may be unreliable and misleading, as well as violate personal data laws. These challenges highlight the need to adapt legal frameworks to new digital realities. The relevance of the study stems from the dilemma facing legislators: to recognize artificial intelligence as sui generis legal personality or to modify the protection mechanism by shifting the creativity criterion within copyright law to an investment criterion within related law. The aim of the study is to resolve this dichotomy. The methodological basis of the study is based on comparative legal and formal logical methods. The scientific novelty lies in the comprehensive analysis of the hypothesis regarding the transition from the creativity criterion to the investment criterion. The article demonstrates that modifying the copyright protection mechanism by shifting the creativity criterion within copyright law to the investment criterion within related rights represents the most preferable vector of legal policy.

Language: English
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Keywords: интеллектуальная собственностьискусственный интеллектмашинное обучениенейронная сетьintellectual rightsинтеллектуальные праваintellectual propertyрезультат интеллектуальной деятельностиresult of intellectual activitymachine learningartificial intelligenceneural network
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