AI-Powered Language Translation: Bridging Global Communication Gaps

Abstract

Language barriers continue to challenge global communication in business, education, and diplomacy. This paper examines how artificial intelligence (AI)-powered translation models, such as neural machine translation (NMT) and large language models (LLMs), are improving cross-lingual understanding. The study explores the strengths and limitations of AI-driven translation tools in handling complex linguistic nuances, cultural context, and low-resource languages. A comparative analysis of AI translation technologies in China, the U.S., and Europe highlights advancements and areas for improvement. Ethical considerations, including bias in translation algorithms and data privacy, are also discussed. The findings suggest that AI-powered translation has the potential to create a more interconnected world.