The evolution of translation has been greatly influenced by the development of machine translation technologies. While human translation is still widely used and valued for its ability to capture nuance and context, machine translation has become an increasingly important tool in the translation industry.

The first attempts at machine translation date back to the 1940s, when scientists began exploring the use of electronic computers to translate text. These early efforts were based on rule-based systems that used linguistic rules to generate translations. While these systems were able to produce some basic translations, they often struggled with more complex language structures and idiomatic expressions. More recently, neural machine translation (NMT) has emerged as the state-of-the-art approach to machine translation.NMT uses deep learning algorithms to train translation models, allowing for more accurate and fluent translations. NMT systems are able to capture the nuances of language and produce translations that are often indistinguishable from those produced by human translators.

Overall, the evolution of translation has been marked by the ongoing development of new technologies and approaches, both human and machine-based, that aim to improve the accuracy and efficiency of translation.