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August 13, 2026
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Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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August 11, 2026
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The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Assessing the Influence of Institutional Factors on the Innovation Ecosystem Model in Russian Power Sector

P. 87–89.
Burda Y.

This paper investigates the influence of institutional factors on the ecosystem model of EnergyNet within the Russian power sector. We argue that creation of ecosystem value proposition depends not only from the activities of actors, their positioning and links between them, but from the external environment as well. This environment can be described in terms of availability of resources, essential for ecosystem, possibility of partnership among actors, and state support of innovative activity. This allows to expand the ecosystem model point of view and reveal factors that determine current state of ecosystem development. Preliminary results of the research show disproportion in the assessment of importance to collaborate among big companies and SMEs. We also revealed that state support is considered to be the least important from the participants’ point of view, which seems to be contradictive to the current point of view on innovations in Russia. In addition, we can observe a considerable imbalance in the assessment of availability and importance of various institutional factors.

Language: English
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Keywords: innovation ecosystemenergynetecosystem modelRussian Power SectorEcosystem Value PropositionInstitutional Determinants

In book

ANNUAL GSOM EMERGING MARKETS CONFERENCE 2019
St. Petersburg: St. Petersburg State University Graduate School of Management, 2019.
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