Historical Development of The Formation of Artificial Intelligence Vocabulary

Abstract

This article examines the formation and historical development of Artificial Intelligence (AI) vocabulary from technological and linguistic perspectives. The study discusses the early theoretical foundations of artificial intelligence, Alan Turing’s ideas concerning machine intelligence, the Turing Test, the Dartmouth Conference of 1956, and subsequent stages in the development of AI. Particular attention is paid to the emergence and semantic development of such terms as artificial intelligence, machine learning, deep learning, neural networks, natural language processing, computer vision, large language models, and generative AI. The rapid development of big data, neural networks, generative models, and digital technologies in the twenty-first century has significantly contributed to the expansion and diversification of AI-related vocabulary. The article also considers the penetration of AI terminology into such fields as graphic design, photography, education, medicine, economics, and other professional domains, resulting in the emergence of new terminological units. The findings demonstrate that AI vocabulary is developing as a dynamic, interdisciplinary, and continuously expanding terminological system. Purpose of the Study. The purpose of this study is to develop and validate approaches to the application of machine learning methods to improve the accuracy and reliability of financial flow forecasting in logistics systems based on an analysis of their structure, influencing factors, and operational characteristics.