What are the main challenges faced by machine translation systems when translating idiomatic expressions between languages?
How does context influence the accuracy of language translation, and what methods can be used to ensure contextual appropriateness?
In what ways can computer-assisted translation tools aid human translators in improving the quality and speed of their work?
How has neural machine translation (NMT) technology improved upon previous statistical methods in terms of translation accuracy and fluency?
What ethical considerations should be taken into account when developing and deploying translation technologies, especially in culturally sensitive or politically charged contexts?
How do machine translation systems, like Google Translate, handle idiomatic expressions and cultural nuances, and what are the limitations?
What are the main differences between human translation and machine translation, and in what scenarios might one be preferred over the other?
How has the development of neural networks and artificial intelligence impacted the accuracy and efficiency of language translation?
What are the challenges in developing translation systems for low-resource languages, and what efforts are being made to address these challenges?
How do translation memory and computer-assisted translation (CAT) tools aid professional human translators in their work?