Article by Jourik Ciesielski.
The year is 2023. Six years after the big neural MT push of 2017, it seems appropriate to say that machine translation (MT) has finally found its way in the localization industry. Most MT providers are producing reasonably acceptable baseline quality and MT solutions have never been more accessible. As a result, MT is becoming a reality in many organizations. What’s more, MT technology has reached a certain level of maturity in terms of customization and training. The barrier to working with legacy data and using it to train custom models and deploy proprietary MT programs — both large and small — is no longer as insurmountable as it once was. The purpose of this article is to provide an update of the state of the current MT technology market and a summary of everything you need to know to deploy trained MT models in your localization processes.
Although Google Translate (public) and SYSTRAN (corporate) once dictated the law of the land of the MT market, things have changed. The technology market has exploded and has enabled every organization to find the right MT solutions partner, even if the quest might be a long and intense one. There are now three primary technology tracks to choose from: cloud services, SaaS providers, and open-source frameworks.
The MT tool landscape. Source: Nimdzi Language Technology Atlas
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