The field of language translation is experiencing an exciting period of growth and advancement. Thanks to the development of artificial intelligence, machine learning, and natural language processing, translation management systems now have the ability to generate accurate, real-time translations. In this article, Adriano Raiano explores the evolution of translation technology, from its origins to its current state, and discusses the future advancements we can expect to see.

The article begins by highlighting the challenges of multilingual content development and the importance of using the right translation tools. It then traces the history of translation technology, starting with Al-Kindi’s Manuscript on Deciphering Cryptographic Messages and the arrival of computers in the mid-twentieth century. Significant milestones such as the Georgetown-IBM experiment in the 1950s and the rise of statistical machine translation in the late 1980s and early 1990s are discussed.The article also covers the emergence of commercial computer-assisted translation tools in the early 1990s and IBM’s rule-based statistical translation engine in the late 1990s. The introduction of cloud-based translation management systems in the early 2000s and the launch of Google Translate in 2006 are highlighted as major developments in the field.The article then delves into the different types of translation technology, including computer-assisted translation (CAT), machine translation (MT), and translation management systems (TMS). It explores the benefits and drawbacks of both human and machine translation approaches and emphasizes the importance of finding the right balance between them.The article also discusses the future of translation technology, particularly the competition between Google and OpenAI in the AI-powered translation landscape. It suggests that collaboration between human translators and AI-powered machines is the key to achieving accurate translations. The role of translation management systems in facilitating this collaboration is also highlighted.Finally, the article concludes by acknowledging that while Google Translate and DeepL currently lead in terms of translation quality and specialization, the competitive landscape is constantly evolving. OpenAI’s focus on language generation and natural language processing research may lead to improvements in machine translation capabilities, and new platforms or models could disrupt the current dynamics.Overall, the article presents a comprehensive overview of the evolution of translation technology and highlights the exciting possibilities for the future of the field.