Moscow State University has reportedly completed the creation of a closed artificial intelligence hub that brings together several major AI education and research resources. The project is centered around Katerina Tikhonova, who heads the university’s Institute of Artificial Intelligence and is widely reported to be the daughter of Russian President Vladimir Putin. The Moscow Times reported the development on April 28, 2026, citing the independent outlet T Invariant.
The reported hub brings together the Institute of Artificial Intelligence, a newly established Faculty of Artificial Intelligence, a research center and the MGU 270 supercomputer at the university’s Vorobyovy Gory campus in Moscow. Consequently, the project represents a significant concentration of AI education and computing resources within one university ecosystem.
Katerina Tikhonova and the AI Project
Tikhonova is the director of Moscow State University’s Institute of Artificial Intelligence. International reporting has widely identified her as Putin’s daughter, although the Kremlin has not publicly confirmed the relationship. The reported role in the AI hub places her at the center of an initiative that combines academic research, advanced computing and specialist education.
Meanwhile, Moscow State University officially announced the launch of its Faculty of Artificial Intelligence on April 21, 2026. Ivan Oseledets, a professor and head of the AI research institute AIRI, was appointed to lead the faculty. The university said the faculty would admit undergraduate and postgraduate students, with both state funded and tuition based places available.
MGU 270 Supercomputer Draws Attention
One of the most significant components of the reported hub is the MGU 270 supercomputer. According to T Invariant reporting cited by The Moscow Times, the system uses Nvidia graphics processors acquired through indirect channels involving Chinese companies.
The report also says access to the computer is tightly restricted. Sources cited by T Invariant claimed that even some specialists within Moscow State University’s Research Computing Center had been unable to access the system. These claims could not be independently verified by The Moscow Times.
Nevertheless, the reported restrictions highlight the strategic importance of high performance computing infrastructure for modern AI research. Advanced computing capacity is essential for training sophisticated models, running large simulations and developing increasingly demanding machine learning applications.
Russia’s Push for Domestic AI Capabilities
The development comes as Russia seeks to strengthen its domestic AI capabilities while facing Western sanctions and restrictions on advanced semiconductor technology. These restrictions have complicated access to some high performance computing components.
Therefore, building domestic research capacity has become an important part of Russia’s broader technology strategy. AI trends and insights increasingly show that computing infrastructure, specialized talent and access to advanced processors are closely connected.
For Russia, universities can play an important role in this effort because they combine research, education and technical expertise. The Moscow State University project illustrates how academic institutions can become important centers for national technology development.
New Faculty Focuses on AI Education
The creation of a dedicated AI faculty also reflects the growing demand for specialists in artificial intelligence. According to The Moscow Times, the faculty planned to admit 36 undergraduate students and 36 master’s students, with 20 state funded places available at each level. Annual tuition was reported at approximately 500,000 rubles.
As AI adoption expands globally, universities are increasingly adapting their programs to prepare students for emerging technology roles. Machine learning advancements, generative AI developments and new computing architectures are creating demand for professionals who understand both theoretical concepts and practical applications.
Consequently, specialized education could become an important component of Russia’s effort to develop domestic AI expertise.
Questions About the New Academic Structure
The creation of a separate AI faculty has also generated discussion within the academic community. The Moscow Times reported that one Russian Academy of Sciences member questioned why AI needed a separate faculty rather than being incorporated into existing university departments.
Such discussions reflect a broader question facing universities worldwide. As artificial intelligence becomes relevant to mathematics, engineering, medicine, economics and social sciences, institutions must decide whether AI should remain a specialized discipline or become integrated across existing academic programs.
The answer may influence how universities organize research funding, teaching resources and interdisciplinary collaboration.
China Cooperation and Future Research
The reported project is also expected to involve deeper cooperation with Chinese institutions. The Moscow Times reported that discussions were underway regarding joint laboratories involving Shenzhen MGU BIT University. The university had previously announced plans for laboratories focused on nanostructured materials and AI algorithms.
In addition, Moscow State University plans to establish a robotics park within the new AI faculty building. The facility is expected to support research into AI based control systems.
These developments connect the project with broader Automation and future tech trends. Robotics, advanced algorithms and high performance computing are increasingly converging as researchers develop systems capable of operating in complex environments.
AI Development Under Technology Restrictions
The reported use of indirectly sourced Nvidia processors highlights another important issue in global AI development. Access to advanced computing hardware has become an important factor in technological competition.
AI industry updates increasingly focus not only on software models but also on semiconductor supply chains, computing infrastructure and access to specialized hardware. Countries seeking greater technological independence therefore face the challenge of developing both AI expertise and the infrastructure required to support it.
For researchers, this environment can affect which models they can train, how quickly experiments can be completed and what types of projects can be pursued.
What the Moscow AI Hub Could Mean
The reported development illustrates how artificial intelligence is becoming closely connected with national technology strategies. Universities are no longer simply places for academic research. They can also serve as important centers for developing specialized talent, computing infrastructure and applied technology.
Future of AI research will likely depend on cooperation among universities, technology companies, governments and research institutions. At the same time, questions surrounding transparency, access to computing resources and international technology restrictions are likely to remain important.
For technology professionals and businesses, developments such as this provide another example of how AI competition is expanding beyond individual companies and into education, infrastructure and national research systems.
Actionable Insights for Technology Leaders
Organizations following global AI development should look beyond new AI models and examine the infrastructure supporting them. University research programs, semiconductor access, specialist education and international partnerships can all influence the pace of technological progress.
The Moscow State University project also demonstrates why AI industry updates should be considered alongside machine learning advancements and Future of AI research. Together, these developments provide a broader view of how artificial intelligence capabilities are being built and deployed around the world.
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Source – themoscowtimes
