Machine translation, such as Google Translate, is a tool that uses artificial intelligence to automatically translate text and speech from one language to another. While it can be a helpful tool for translators, it is not always reliable and can produce inaccurate translations, especially for languages that are less commonly translated.
Professional translators may use machine translation to increase translation speed, as it can deliver a first draft almost instantly, reducing the overall workload and allowing for faster turnaround times. However, relying solely on machine translation can result in inaccurate translations, as it chooses the best translation based on statistics and probabilities, rather than the most interesting or poetic one.
To ensure accurate translations, translators may use machine translation as a starting point and then edit and refine the translation to ensure it meets the desired level of quality. This approach can be particularly useful for translating content that requires a more nuanced understanding of language and culture, such as marketing materials, legal documents, and literary works.
Recent advances in machine learning have driven improvements to automated translation, including the introduction of neural translation models like Google's GNMT. These models have enabled significant improvements to the quality of translation for over 100 languages. However, state-of-the-art systems still lag significantly behind human translation, and the accuracy of machine translation can vary depending on language pair and content type.
Overall, while machine translation can be a useful tool for translators, it is important to approach it with a critical eye and not rely solely on its output. By combining machine translation with human editing and refinement, translators can ensure accurate and high-quality translations that meet the needs of their clients.