AI Is for Active Involvement... of Russian Students in Artificial Intelligence ResearchDecember 20, 2019
Russia will design and put in place world-class educational programs to train highly skilled artificial intelligence (AI) professionals and executives, as envisaged by the National Strategy for the Development of Artificial Intelligence through 2030 which President Vladimir Putin signed last October. The document defines AI as technological solutions capable of mimicking human cognition and performing intellectual tasks similarly to, or better than, humans.
Artificial neuron networks are an integral part of speech recognition, web browsing and other everyday applications, and banking and finance have already emerged as AI-heavy industries, says Mikhail Burtsev, leader of the iPavlov conversational AI project and head of the Neural Networks and Deep Learning Lab at the Moscow Institute of Physics and Technology (MIPT), a Project 5-100 university.
As many as 90% of businesses worldwide have made some investment in AI, according to a survey of over 2,500 CEOs across 27 industries conducted for the MIT Sloan Management Review (SMR) and Boston Consulting Group (BCG) Global Executive Study and Research Report that was published last October.
In Russia, 69% of business leaders lament a shortage of skilled AI specialists, as revealed by a Russian Public Opinion Research Center (VCIOM) survey released on December 12.
What can Russian universities do to fill this gap?
Mikhail Burtsev believes that, to begin with, forward-looking educational programs must be designed to anticipate industry trends. They should equip graduates with skills that meet both current and projected market needs.
Experts see practice-oriented education and collaboration between academy and high-tech business as key to producing the kind of AI professional that industry is clamoring for.
Alexander Boukhanovsky, who heads the National Center for Cognitive Technologies at ITMO University, another Project 5-100 institution, says that any program training experts for such a fast-changing field as AI must be constantly updated, with business partners cooperating both by providing individual specialists to act as instructors and by setting up full-blown corporate educational programs. As product lead times in the sector are growing shorter, students should engage in authentic AI-related R&D long before they write their theses.
Accordingly, ITMO University runs its master's programs in Artificial Intelligence using a project approach that allows for personalizing educational pathways. Students are encouraged to get involved in real-life projects commissioned by the university's corporate partners and choose which subjects to study with reference to their project activities. This enables them to develop a specialization and gain experience working at top-tier companies, including Gazpromneft (an oil & gas major), Mail.Ru (an OSP), MTS (a telecoms operator) and Sberbank (a banking & finance giant).
At MIPT, AI trainees also acquire practical skills through participation in real-life R&D projects, as the university collaborates with Russia's leading research, infrastructure and high-tech companies and institutions: ABBYY (a software designer), Innopolis University, National Research University Higher School of Economics, Russian Railways, Rosseti (a power grid operator), Rostelecom, Sberbank, the Skolkovo Institute of Science and Technology, and the Federal Biomedical Agency.
Once trained, professionals have to be retained, a challenge that Russian companies should be able to deal with, say experts. In Russia, there is strong demand for highly skilled AI workforce from both big corporations, domestic (Mail.Ru, Sberbank, Yandex) as well as international (Huawei, Samsung), and high-tech startups. Indeed, as Mikhail Burtsev points out, specialists are not flocking out of the country; rather, their outflow is close to a 'natural' rate of migration.
Alexander Boukhanovsky sees the progress of AI as largely driven by industry needs, since, in his opinion, AI research has no market value unless applied to solving industry-related tasks. Its future therefore appears to lie with the development of industrially oriented solutions and decision-making systems aimed at reinforcing human intelligence in an environment that brings together machinery and both natural and artificial intelligence.