Google, Microsoft, Baidu, Yandex and Yahoo! are either getting paid or getting ready to be paid for translation through advertising revenue. Giving access to multilingual information increases their user base and raises cash. Lots of it. They are setting an example that many others would like to emulate.

Anyone who fails to see the fundamental shift in the demand for translation from the traditional buyer to the billions of citizens, patients, tax payers and consumers, is just scratching the surface of the vast potential for the global language industries.

The European Commission tell us that each EU citizen is paying on average €2 per year to fund the one Billion Euro translation budget of the Directorate General of Translation, by far the largest in the world.

We can rightfully say that translation is already being paid for in different ways than the word-price model.

Data-driven machine translation is still in its infancy and the language industry is only just starting to work with this technology on a material scale. We are only at the beginning of an innovation journey that will include game changing shifts for both buyers and providers of translation as they seek to adapt their models to the 21st century.

By 2020 English will already have lost its status as a lingua franca. And no new lingua franca will replace English as a language of commerce. Linguistic diversity is the new reality and machine translation technology will help us to communicate despite all its shortcomings and the inevitable partial understanding.

We can expect that by 2020 automated translation tools will be embedded into every device, application and website. Imagine a web of hundreds of thousands of automatic translators trained not only for a few languages and industry sectors but tuned to a myriad of language pairs, many sub-domains and customized for every company and offering. Such large-scale, if basic translation can only be paid for in ways that don’t exist now.

We can expect a whole new technical infrastructure and service base for our industry. A layer to provide access to language data: the fuel for machine translation. Another layer that organizes and prepares the data for use. The ‘pipes’ that channel data to and from tools and devices. A sea of people needed to keep such an infrastructure running.

In this context TAUS Data is just a first generation incarnation of such an industry utility. In a meeting taking place later this week, on March 1, in San Jose (CA, USA) forty bright minds from the TAUS community and beyond are meeting to brainstorm ‘TAUS Data Vision 2020’ More.

See: TAUS