THE EVOLUTION OF TEXT TRANSLATIONS TOOLS THROUGH ARTIFICIAL INTELLIGENCE

analysis of evolution, functioning, and technological impacts

Abstract

This study analyzes the evolution of artificial intelligence (AI) translation tools, with a focus on innovations in real-time translation and their growing relevance across various sectors. The research aimed to understand AIs applied to translation by investigating their evolution, creation, training, and differences compared to traditional tools. The methodology combined a literature review and case studies, evaluating tools such as Google Translate and ChatGPT. The results indicate that AIs, using neural networks and deep learning, provide greater accuracy and fluency in translations, especially in technical and complex texts, surpassing the limitations of traditional approaches based on rigid grammatical rules. The practical application of these tools stands out in e-commerce, the legal sector, education, and healthcare, facilitating global communication. The conclusions highlight that AIs offer more consistent terminology and efficiency, continuously improving with new data. However, they still face challenges in specific cultural contexts and with less documented languages. Future research should focus on minimizing bias in training data and exploring hybrid translation approaches to improve the accuracy and quality of automatic translations.