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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
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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Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
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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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Вызовы пандемии для технологических стартапов в регионах России

Форсайт. 2021. Т. 15. № 4. С. 61–77.
Земцов С., Chepurenko A., Михайлов А.

Technological startups help to adapt economies to the global risks and allow one to track future trends. This paper identifies the main trends and birth factors of new high-tech companies in the Russian regions during 2013-2020. In 2020, fewer than 10,000 startups were created annually, this number has been steadily declining (by 40% since 2015), especially during the pandemic (-21%). Most of the startups are concentrated in Moscow, the Moscow region, St Petersburg, and the largest metropolitan areas. The share of the Leningrad, Belgorod, Kaliningrad, Lipetsk, Ulyanovsk, and Kaluga regions is growing due to the proactive policies of local authorities. Most startups are associated with knowledge-intensive services for business (B2B) and digital technologies. In 2020, their number increased in pharmaceuticals (about 100%) and in the production of medical devices (by about 30%). Based on the results of econometric analysis, start-up activity in Russia, analogous to countries with an established market economy, depends upon human capital concentration, market access, and a favorable business climate. Universities, through attracting students, especially those in STEM specialties, stimulate startup creation; although the share of university startups does not exceed one third of a percent. Budgetary and university expenditures on R&D are ineffective in terms of creating new companies. The influence of development institutions on start-up activity was not found, while clusters and technology parks have a weak effect. The growth of startups is lower in regions with a predominance of large organizations, as well as in resource centers. The latter may be one of the manifestations of the “resource curse”. Startup activity is stable over time and depends on the situation in neighboring regions, which limits the chances to change the situation by means of entrepreneurship support policy. During the pandemic, start-up activity decreased minimally in regions with large metropolitan areas and a high level of education. Recommendations include tools for establishing a more balanced cross-regional situation by implementing the model of an entrepreneurial university, an expansion of start-ups’ access to capital and markets, and the regionalization of entrepreneurship policies.

Research target: Economics and Management Sociology (including Demography and Anthropology
Language: Russian
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Text on another site
Keywords: предпринимательствоРоссияинституты развитияentrepreneurshipRussiaкластерыclustersdevelopment institutionsвысокотехнологичные отраслиentrepreneurial universitiesпредпринимательские университетыпандемияpandemicCOVID-19high-tech sectorregional entrepreneurial ecosystemрегиональная предпринимательская экосистемаCOVID-19
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