Editing SYSTRAN (section)

==History==
With its origin in the [[Georgetown–IBM experiment|Georgetown]] machine translation effort, SYSTRAN was one of the few machine translation systems to survive the major decrease of funding after the [[ALPAC|ALPAC Report]] of the mid-1960s. The company was established in [[La Jolla]] in California to work on translation of Russian to English text for the [[United States Air Force]] during the [[Cold War]].<ref name=USSR.cold>{{cite news |newspaper=[[The New York Times]]
   |url=https://archive.nytimes.com/www.nytimes.com/library/tech/98/03/cyber/eurobytes/10euro.html
   |title=Free Translation of Language Proves More Divertimento Than a Keg of Monkeys
   |author=Bruno Giussani  |date=March 10, 1998}}</ref> Large numbers of Russian scientific and technical documents were translated using SYSTRAN under the auspices of the USAF [[Foreign Technology Division]] (later the [[National Air and Space Intelligence Center]]) at [[Wright-Patterson Air Force Base]], Ohio. The quality of the translations, although only approximate, was usually adequate for understanding content.

The company headquarters is in Paris, while its U.S. headquarters is in San Diego, CA.

During the [[dot-com bubble|dot-com boom]], the international [[language industry]] started a new era, and SYSTRAN entered into agreements with a number of translation integrators, the most successful of these being WorldLingo.<ref>{{cite web|url=http://translations.com/services/language-services/machine-translation.html?gclid=EAIaIQobChMIqI23ycHO2QIVBw5pCh1nDAxVEAAYASAAEgJZgvD_BwE#WorldLingo|title=Machine Translation|date=2016-12-01|website=translations.com|access-date=2018-03-02}}</ref><ref>{{cite news  |newspaper=[[The Wall Street Journal]] (WSJ)
   |url=https://www.wsj.com/articles/SB119811828316841433
   |title=With Online Services, Foreign Texts Can Get Lost in Translation
   |date=December 20, 2007}}</ref>

In 2016, the [https://nlp.seas.harvard.edu/ Harvard NLP group] and SYSTRAN founded [https://opennmt.net/ OpenNMT], an open source ecosystem for neural machine translation and neural sequence learning. This has enabled machine translation software with learning capabilities, dramatically increasing MT translation quality. The project has since been used in several research and industry applications, and its open source ecosystem is currently maintained by SYSTRAN and [https://www.ubiqus.com/ Ubiqus].