1954 - Georgetown researchers perform the first-ever public demonstration of an early MT system.

1962 - The Association for Machine Translation and Computational Linguistics is formed in the U.S.

1964 - National Academy of Sciences forms a committee (ALPAC) to study MT.

1970 - The French Textile Institute begins to translate abstracts using an MT system.

1978 - Systran begins to translate technical manuals.

1989 - Trados is the first to develop and market translation memory technology.

1991 - The first commercial MT system between Russian, English, and German-Ukrainian is developed at Kharkov State University.

1996 - Systran and Babelfish offer free translation of small texts on the web.

2002 - Lionbridge executes its first commercial MT project using its rule-based MT engine.

Mid 2000s - Statistical MT systems launch to the public. Google Translate launches in 2006 and Microsoft Live Translator launches in 2007.

2012 - Google announces that Google Translate translates enough text to fill 1 million books every day.

2016 – Both Google and Microsoft enable Neural Machine Translation (NMT), slashing word order mistakes and significantly improving lexicon and grammar.

2020 - As of October, Google Neural Machine Translation (GNMT) supports 109 languages.

2022 - Lionbridge experts share findings that MT engine output performance is stagnating, and all tracked engines perform similarly. These developments indicate that the Neural MT paradigm may be reaching a plateau and suggest that a new paradigm shift could be approaching.

2022 - OpenAI launches its generative AI engine, ChatGPT, to the public in November, highlighting an evolving and expanding translation technology landscape.

2023 - GenAI proliferates with more model launches, a steady stream of new iterations, and solutions catering to various industries and use cases.

2024 – MT’s relevance shifts, complementing LLMs as generative AI flourishes.