Kolin Konstantin

DrS (Tech. Sci.), Professor, Chief Researcher of the Federal Research Center "Computer Science and Control”, Russian Academy of Sciences (Moscow, Russia)

Khoroshilov Alexander

DrS (Tech. Sci.), Professor of the Moscow Aviation Institute (National Research University), Leading Researcher of the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Senior Researcher of the 27 Central Research Institute of the Ministry of Defense of the Russian Federation (Moscow, Russia)

Nikitin Yuri

Researcher of the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Development Team Leader of the Scientific and Industrial Company “High Technologies and Strategic Systems”(Moscow, Russia)

Pshenichny Sergey

PhD (Econ. Sci.), Program Director of the Scientific and Industrial Company “High Technologies and Strategic Systems” (Moscow, Russia)

Khoroshilov Alexei

Ph.D (Engineering Sci.), Senior Researcher of the 27 Central Research Institute of the Ministry of Defense of the Russian Federation (Moscow, Russia)

Artificial intelligence in machine translation

The potential of machine translation is closely related to advances in modeling of understanding and generating texts in natural languages, which traditionally belongs to Artificial intelligence sphere. The article attempts to analyze the main approaches to developing machine translation technologies. It is concluded that these approaches so far ignore the generation and use of dynamic models of the world, but are moving mainly in the direction of a grammatically consistent translation of word sequences.

Keywords: machine translation; natural language; Artificial Intelligence; machine translation technologies.

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For citation: Artificial intelligence in machine translation / Kolin K.K., Khoroshilov Al-dr A., Nikitin Yu.V., Pshenichny S.I., Khoroshilov Al-ei A. / English transl. by Nikulichev M.Y. // Social Novelties and Social Sciences. – Moscow : INION. RAN, 2021. – N 2. – P. 52–65.
DOI: 10.31249/snsn/2021.02.05, 10.31249/snss/2021.02.05

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