Artificial Intelligence Translation Adaptability from the Perspective of Eco-Translatology: Challenges and Countermeasures

Abstract

With the rapid development of artificial intelligence (AI) technology, AI translation has made significant progress in terms of language adaptability, yet it still faces numerous challenges. This paper explores the language adaptability of AI translation systems from the perspective of Eco-Translatology, focusing on issues such as differences in grammatical structures, cultural context understanding, contextual adaptation, and data bias. This paper identifies key directions for improving the language adaptability of AI translation through an evaluation of current AI translation technologies, including technological innovation, the application of Eco-Translatology, interdisciplinary collaboration, and the integration of hybrid translation models. Finally, the paper anticipates the future development of AI translation and emphasizes the importance of cross-cultural communication and global cooperation.