.png)
UDC 81`2:004.8
Novikova Marina L.,
Doctor of Philology,
Professor of the Russian Language and Cultural Studies Department
Peoples’ Friendship University of Russia named after Patrice Lumumba
e-mail: novikova-ml@rudn.ru
Novikov Phillip N.,
Candidate of Philology,
Associate Professor of the Foreign Languages Department
Peoples’ Friendship University of Russia named after Patrice Lumumba
e-mail: philippnovikov@gmail.com
In the timeframe from 2022 to 2023, the progress in the development of large language models, based on machine learning and neural network technologies, also referred to as “artificial intelligence”, reached an unprecedented level. This facilitated making a significant leap for the application of natural language processing algorithms to both science and everyday life. The article examines the potential and current challenges of using these technologies with respect to the languages of the peoples of the Russian Federation and the CIS in the modern digital environment. The study touches upon such areas as translation, linguistic analysis, language popularization, and development of original language online services.
Keywords: artificial intelligence, machine learning, languages of the peoples of Russia, large language models.
References
1. Avramenko A.P., Tishina M.A. Didakticheskii potentsial lingvisticheskikh korpusov na baze tekhnologii iskusstvennogo intellekta dlia adaptatsii uchebnykh materialov // Vestnik Moskovskogo gosudarstvennogo oblastnogo universiteta. Seriia: Pedagogika. 2023. No. 1. S. 29–38.
2. Bakhtikireeva U.M. “Mladopis’mennye iazyki”: o relevantnosti termina po otnosheniiu k tiurkskim iazykam // Sokhranenie i razvitie iazykov i kul’tur korennykh narodov Sibiri. Abakan, 2022. S. 7–12.
3. Bakhtikireeva U.M. Razmyshleniia o bilingvizme i trans”iazychii // Lingvistika v dialoge s drugimi oblastiami znanii: iurislingvistika i diskursivnaia lingvistika, kommunikativnaia lingvistika i lingvokul'turologiia. Vitebsk: VGU im. P.M. Masherova, 2022. S. 6–12.
4. Burnashev R.F., Alamova A.S. Kvantitativnaia lingvistika i iskusstvennyi intellekt // Science and Education. 2022. No. 3 (11). S. 1390–1402.
5. Athaluri S.A., Manthena S.V., Kesapragada V.K.M. Exploring the boundaries of reality: investigating the phenomenon of artificial intelligence hallucination in scientific writing through ChatGPT references. DOI 10.7759/cureus.37432 // Cureus. 2023. No. 15 (4).
6. Is it possible to preserve a language using only data? / J. Bensemann, J. Brown, M. Witbrock, V. Yogarajan. DOI 10.1111/cogs.13300 // Cognitive Science. 2023. No. 47 (6).
7. Biswas S. Role of Chat GPT in computer programming: Chat GPT in computer programming. DOI 10.58496/MJCSC/2023/002 // Mesopotamian Journal of Computer Science. 2023. March. P. 8–16.
8. How good are gpt models at machine translation? A comprehensive evaluation / A. Hendy, M. Abdelrehim, A. Shara et al. DOI 10.48550/arXiv.2302.09210 // arXivLabs. 2023. arXiv:2302.09210.
9. Hutchin W.J. Machine translation: History of research and applications // Routledge encyclopedia of translation technology. 2023. P. 128–144.
10. Low D.S., Mcneill I., Day M.J. Endangered languages: A sociocognitive approach to language death, identity loss, and preservation in the age of artificial intelligence. DOI 10.2478/sm-2022-0011 // Sustainable Multilingualism. 2022. Vol. 21. P. 1–25.
11. Probing GPT-3’s linguistic knowledge on semantic tasks / L. Zhang, M. Wang, L. Chen, W. Zhang // Proceedings of the Fifth Blackbox NLP Workshop on Analyzing and Interpreting Neural Networks for NLP. 2022. P. 297–304.