COGNITIVE AND SEMANTIC APPROACHES OF ARTIFICIAL INTELLIGENCE IN THE PROCESS OF TERMINOLOGICAL TRANSLATION - E.T.Tursunnazarova; G.V.Petruk (ARAB TILI GLOBALLASHUV DAVRIDA: INNOVATSION YONDASHUVLAR VA O‘QITISH METODIKASI MAVZUSIDAGI XALQARO ILMIY-AMALIY ANJUMAN, 2025)
The article examines the cognitive and semantic approaches of Artificial Intelligence (AI) in the process of terminological translation. It discusses how AI-based systems, such as neural machine translation (NMT) and large language models (LLMs), process, interpret, and reproduce specialized terminologies across different languages. The study highlights the integration of cognitive linguistics principles, including conceptual mapping and frame semantics, into computational translation models. It is argued that the success of terminological translation depends not only on lexical equivalence but also on the AI’s ability to understand semantic relations and cognitive structures underlying technical vocabulary. The research draws on comparative examples from English, Russian, and Uzbek terminological data.