Перевод "Breakthroughs from Research #3"

Luigi Muzii, “Breakthroughs from Research #3”, public translation into Russian from English More about this translation.

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Breakthroughs from Research #3

In the last few years, Internet and data have been the engine for change, affecting global communications in every area, including the translation industry.

Big data and the IoT

A few weeks ago, at the International Consumer Electronics Show in Las Vegas, 2015 has been designated as the year of connected devices. From toothbrushes that can schedule check-ups with dentists to yoga mats that can analyze āsana in real-time, over collar-powered trackers helping owners locate their runaway pets.

It is the Internet of Things (IoT), everyday objects with integrated network connectivity, which Gartner predicts in over 25 billion by 2020.

These devices will be producing exabytes of data every day. Real-time processing, analysis, and leveraging are becoming a capability requirement.

Right now, big data is central to many areas because of the unparalleled amount of data produced every day. Most research projects require a massive data-crunching and machine-learning approach.

Recently, the American Association for the Advancement of Science identified a poor fit in traditional university career paths for experts to build the tools to analyze vast amounts of data now abundant in every field. Big data experts are already sought-after by industry and needed in academia, i.e. to process gene sequences or cosmological data.

Achievements in statistical machine translation are also due to a change in paradigm made possible by the availability of an unmatched amount of language data.

Kenneth Cukier, co-author of Big Data: A Revolution That Will Transform How We Live, Work, and Think, explained this brilliantly in a TED talk last June.

Computer scientists changed the nature of the problem from trying to explain to the machine how to translate to instructing it to figure out what a translation is from a huge amount of data around it. They call it machine learning.

With the emergence of IoT, data is changing status, from static to dynamic, and is been leveraged for uses never imagined when collected, with translation becoming ubiquitous and more and more a big data issue.

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