What's going on in the world of language technology? Nimdzi has organized a series of panel discussions to cover some of our favorite topics in the space.
New challenges brought about by doing business in our digital world demand new solutions. Some constants still remain, however, without which a text and the quality of its translation would be less than satisfactory. One good example of such a constant is terminology and terminology management. Terminology management includes a number of different aspects, but […]
We recently introduced you to the two- (or five-) second rule, which is essentially the reaction or decision-making time a linguist should spend judging whether to post-edit a segment of machine translation (MT) output or to retranslate it. This rule of thumb aims to help increase the linguist’s productivity when working with MT.
If you’re a driver, you’ve probably heard of the two-second rule. Staying at least two seconds behind any vehicle is considered a rule of thumb for drivers wanting to maintain a safe following distance at any speed. The two seconds don’t represent safe stopping distance but rather safe reaction time.
On June 10, 2020, we published our Nimdzi Language Technology Atlas, the comprehensive resource that maps hundreds of language technology solutions from all around the world. Two months later, after receiving and reviewing feedback from more than three dozen companies who submitted requests to add new tools or change their categorization, we released an update to the infographic on August 27.
(Non-Traditional) Revenue Growth Through Customer-Centric Project Management Although it is not "traditional," project managers can generate more revenue than even the best salespeople … with the right tools and training. In this discussion, Tucker Johnson (Managing Director, Nimdzi Insights) and Vera Richards (VP, Akorbi Translation and Localization) will share their experience turning traditional operations teams […]
Webinar: New(ish) applications of AI in content creation and localization When people think of AI use cases in content localization, the first thing that comes to mind is MT for structured content. But there are many other use cases for AI in and around translation that are rapidly gaining traction. In order to stay ahead […]
Instructional videos are a big deal. When was the last time that you went to YouTube to watch a video on how that smartphone or that car or that fancy vacuum cleaner worked before deciding on buying it? Or comparing different brands to see which one spoke to you the most? We bet it wasn’t that long ago!
We all know that human input is still invaluable when reviewing localized content. But with ever-improving localization technologies, where does a manual approach to auditing matter most?
Do you remember the last time when people were NOT talking about machine translation (MT)? We don't. Wherever you go, there’s someone talking about MT. With few exceptions, it seems like the only major disruptors in our industry over the past few decades have been breakthroughs in language technology.