Our Analysts' Insights

Language services today stand on the cusp of a disruptive transformation that will redefine how professional linguists work. This shift will come from the availability of ubiquitous artificial intelligence (AI) that extends their reach and capability and makes them far more efficient than they could otherwise be.

Recent advances in neural machine translation (NMT) represent a significant step forward in machine translation capabilities. Although most media coverage has significantly oversold the technology, one of Google’s announcements may actually be the most important one in the long run – the first successful deployment of zero-shot translation (ZST).

Increasingly, B2B and B2C companies alike provide an app-like experience for their brand websites. Today, more than 50% of searches, globally, take place on mobile devices. Sure, people that carry handhelds still download apps for handling frequently repeated tasks, like checking the weather, but otherwise expect to perform app functions via their mobile web browser. How did we get to this point?

By now, most language professionals have seen that claims that neural machine translation (NMT) is delivering results as good – or almost as good – as human translation. If these claims – which have been repeated in the mainstream tech press without much examination – are accurate, it is only a matter of time before human translators will be out of work.

The "yes" vote on Brexit and the election of Donald Trump surprised many media outlets, pollsters, analysts, and political experts. Those that predicted a different result emerged as the biggest losers of public confidence in their forecasting ability. Meanwhile, the U.S. election added the memes of fake news, fauxtos, and foreign interference to the discourse. Commentators across the political spectrum now debate a "post-fact" or "post-truth" world that would be fa...

Users of interpreting services don’t like gambling with unproven talent. It’s a lot easier – and a lot less risky – to rely on resources that you already trust rather than try out new ones. This aversion to risk makes it really hard for recent graduates of interpreting programs to break into the profession. Recognizing its own challenges with newbies, one language service provider is trying a new approach with it “Cadence Cares Fellowship.”

To address even half the online opportunity, it already takes four languages. To capture 98% of the online audience – and 99% of the entire world online wallet – requires 64 languages. However, in 2017, building multilingual websites to serve those markets will take a company only so far. Why? Visitors and customers expect more than a simple website. What they want is what they’re getting from the most innovative brands in the world – immersive experiences and ongoing interactions both with ...

While linguists may not be as popular as doctors or lawyers on the big screen, they make a regular appearance in a supporting role. Occasionally, they even land the lead role with big-name stars like Amy Adams in the recently-released “The Arrival” or Nicole Kidman in “The Interpreter.”

Are you wasting sales and marketing resources going after the wrong leads? Many language service providers (LSPs) aren’t sure which prospects to pursue, so they market to a broad spectrum of buyers, with little in common, and which cross company sizes, industries, geographies, and countless other attributes. The more LSPs struggle to grow in a predictable fashion, the more they talk about hiring additional salespeople, redesigning incentive plans, and going after any prospect – good or bad.

SYSTRAN announced the beta test of its Pure Neural Machine Translation (PNMT) software with 30 language pairs (18 with English, 12 with French), a dozen corporate clients in diverse industries, and online public access to its software. This beta program caps a year of industry and media attention to deep learning, artificial intelligence, and more recently neural MT (NMT). SYSTRAN announced its PNMT product in August with this October beta. Google revealed its single-pair NMT solution in late Se...