Russia & Artificial Intelligence: Closing The Gap
During the 20th century, the Soviet Union had the second largest economy in the world behind the US. After the Cold War, however, Russia’s economy took a hard hit.
Since Vladimir Putin came to power in 2000, the Russian economy grew at 7.825% annually until 2008. In the past decade, however, Russia’s annual GDP growth has declined to around 1.5%. Traditional drivers for production, such as the heavy industry and the petroleum industry, no longer provide long-term sustainable economic growth.
Russia has instead been devoting considerable resources into AI industry development in the hopes that its great potential will boost the economy to new heights.
On October 11, 2019, Russian President Vladimir Putin approved the National Strategy for the Development of Artificial Intelligence (AI) until 2030. This document argues that it is critical for Russia to become one of the leading countries in AI and new emerging technology, as these sectors will play an irreplaceable role in the development of the economy.
Assessing Moscow’s current policies in this domain, there are three main areas where the development of AI (and related technologies) could attain the country’s strategic objectives.
The first objective pertains to domestic-civilian purposes, premised on expectations that the integration of AI technologies in various spheres of public life will result in much-needed socio-economic transformations.
As noted earlier this year by Russia’s Minister for Economic Development, Maksim Oreshkin, the integration of AI could result in a significant increase in labor productivity by 2030.
At the same time, German Gref, the CEO and chair of the executive board of Sberbank, commented that the integration of new economic or financial solutions on the basis of AI could potentially have a huge transformative effect “on the whole country.”
Yandex, a multinational, Russian corporation specializing in Internet-related products and services, utilizes artificial intelligence and machine learning algorithms to make each search result more precise. Machine learning is a blanket term encompassing wide range algorithms that learn from datasets to provide recommendations, decisions and predictions.
Search engines use ML to process data across the internet and, in the case of Yandex, some offline sources providing better search results and experiences for users.
In 2016, Yandex introduced the Palekh algorithm, which uses deep neural networks to better understand the meaning behind a search query. The algorithm is able to see the connections between a query and a document, even if they don’t contain common words.
In 2018, Yandex introduced the successor to the Matrixnet machine learning algorithm: CatBoost, a software supporting non-numerical, categorical variables that is capable of making more accurate predictions and greater diversification of results. The algorithm utilizes a machine learning technique known as gradient boosting for regression and classification problems manifesting as decision trees.
More specifically, CatBoost is applied where gradient boosting with reduced risk of overfitting in decision trees is required, ie. for combatting bot-powered credential stuffing, and is currently used by organizations such as Cloudflare and CERN.
Yandex’s machine learning algorithms are only a small subset of the updates that the search engine has made over the years to tackle link spam and poor quality content, which is similar to how Google approached the problems.
The second objective of AI research in Moscow is directly related to military objectives. Russia must create more effective, less expensive means to confront looming challenges to lessen the gap between Russia and the US, as mentioned in last year’s article in Voyenno-Promyshlennyy Kuryer.
In Syria, Russian forces tested and employed a broad range of unmanned ground vehicles to perform a variety of tasks including demining, intelligence, surveillance and reconnaissance (ISR), logistics and combat missions.
After having faced treacherous conditions in the mines, improvised explosive devices, and unexploded ordnance that endangered its personnel and allied forces, the Defense Ministry successfully tested and utilized Scarab and Sphera in small, unmanned vehicles for ISR, as well as the larger remote-controlled mine-clearing Uran-6 unmanned vehicles.
These ground robots were reportedly put into service in 2018, and the Defense Ministry is now incorporating the lessons learned from their use into the official concept of operations. Concurrently, the Russian defense sector was working on an unmanned ground vehicle designed specifically to withstand tough urban combat conditions.
The third objective addresses involving artificial intelligence technology with research and technology development. Many leading educational institutions in Russia have already built partnerships with the Chinese technology company Huawei after Huawei ended its partnerships with America.
When Chinese President Xi Jinping visited Russia last June, the two governments announced a joint investment fund for high-tech projects. The fund launched in September with an initial budget of $1 billion and a focus on financing AI research. Several Chinese tech companies have since entered Russia, hunting for AI opportunities.
China's Dahua Technology and Russia's NtechLab joined forces in May to release a camera with facial recognition capabilities ‒ a product that could be helpful to law enforcement in both countries.
In December, the Chinese software developer Vinci Group agreed to work on AI products with the Russian IT startup Jovi in Technologies. However, no Chinese company has done more than Huawei to establish itself as a major AI player in Russia.
In the 21st century, in partnership with China, Russia is becoming a major force in AI development.
Written by Zhehao Zhang
Edited by:
Gihyen Eom
James Rhinelander
Bryan Xiao
Alexandar Ristic
Jason Kauppila
Alexander Fleiss