XTM Insights

When translation memory meets AI: Going global at scale with the most advanced linguistic technology and GPT
When translation memory meets AI: Going global at scale with the most advanced linguistic technology and GPT illustration
Melissa Favre-Lorraine
AuthorMelissa Favre-Lorraine

Translation memory (TM) is a key aspect of localization, as it’s a tool that enables linguists to leverage previously translated assets. Without it, they would have to translate all content from scratch every time, even content that had already been localized, resulting in huge losses in efficiency and increased costs. If you’re not using a Translation Management System (TMS) with a robust translation memory feature to localize your content, chances are you are wasting your time and money translating content that already exists.

Any TMS will include translation memory technology, but you’ll probably want to get more from your existing assets and localization technology than just the bare minimum. However, there is no industry standard set for leveraging in TMS systems or TM leveraging comparison data that shows which approaches are better. How do you really know if your leveraging is good enough? How can you really tell if one system is better than another without having to test them all? Well, beyond testing all of them yourself, we have a suggestion. Look for tech providers that continuously improve their leveraging mechanisms; they are often the ones with the highest-quality solutions.

At XTM, we recognize that the leveraging mechanism is a key aspect of delivering higher-quality translations, consistency, and speed while decreasing costs. For this reason, we are always looking at ways in which we can make our leveraging mechanism better. In this article, we’ll explore how we’re leveraging AI so you can make the most of your translation memories, which will cut your costs even further and enable you to produce higher-quality content at speed.

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