Google Translate has made significant advancements in recent years, but it still faces challenges in achieving human-level translation accuracy, particularly for complex or colloquial language. While the introduction of the Transformer model in 2018 has significantly improved the accuracy of Google Translate, it still struggles with certain language-specific nuances and contextual understanding.
One of the key limitations of Google Translate is its reliance on statistical machine translation, which can struggle with complex grammatical structures and idiomatic expressions. This is especially true for language pairs that have significant structural differences, such as the differences between the imperfect and preterite past tenses in Romance languages. In comparison, professional human translators can draw on their deep understanding of language and culture to produce more accurate and natural-sounding translations. However, Google Translate has continued to improve, and recent studies have shown that it can perform remarkably well on certain types of content, such as business-related text and literary works, with accuracy rates approaching 95%. As the technology continues to evolve, it's possible that Google Translate could one day rival or even surpass the capabilities of human translators for certain tasks, but the need for professional translation services is likely to remain, especially for high-stakes or sensitive communications.