Tuesday, March 31, 2020

Is machine learning breaking down language barriers?

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Is machine learning breaking down language barriers?


Machine-learning breaking down language Barriers
Machine learning is transforming our world faster than many beliefs; in particular, it is transforming trade. According to Richard Baldwin of the WEF portal, this represents a radical change in the way computers "think". Before machine learning, we taught computers to work with computer programs step by step and with computer programs that explain what computers do. This limited computers to imitate human thinking only where we understand step by step how humans think.
For example, it is conscious of thinking because we understand how to do arithmetic and algebra. On the contrary, we have no idea how we recognize a face or maintain balance when running on an open field since this is unconscious thought. Before machine learning, computers could only do conscious thinking because we knew how to program them. Tasks that are accidental are beyond the computer because they are not programmed.
Machine learning changed this by omitting step-by-step programming. With this technique, the computer (the "machine" part) uses a large amount of data to determine the best way to guess the solution to a particular problem (the "learning" part). Thanks to exponential advances in computing, power, and access to absurd amounts of data, machine learning-trained computers routinely achieve human-level performance on unconscious thinking tasks, such as recognizing writing, speaking, or bone breaks in imagery. X-rays. An application that changes the game of machine learning is a machine translation.
What is automatic translation?
Machine translation, machine learning applied to the language, has become surprisingly good in recent years. And it's free, it works instantly and every day it improves. This unique development will change the way the modern world works, as language barriers have been a major obstacle to international trade since time immemorial.
Machine translation is not an exotic future technology in its beta testing phase. It's already on your smartphone, laptop, and tablet. Free apps like Google Translate and iTranslate Voice now work quite well across major languages. Take Google, for example, it does a billion translations a day for online users.
YouTube has instant machine translation for many videos in foreign languages: just go to settings "gear", click "subtitles" and choose "auto-translate". The instant, free and spoken translation is also possible on Skype: the Skype Translator plugin will allow you to understand the foreign language speakers you are flying with. It is not perfect, but being able to speak freely with someone who speaks a different language is wonderful.
Impact of language on trade
In empirical studies, economists find that the language barrier slows trade dramatically, while estimates suggest that sharing a common language increases trade between nations by about 50%. This may sound high to many, but it probably sounds true to most international business leaders who encounter an almost unimaginable range of problems on a daily basis that arise when the buyer and seller cannot speak directly. As machine learning breaks down the language barrier between the major ones, global trade flows should increase, a lot.
In 2015, Google Translate scored 3.6, far worse than the average human translator who scored around 5.1. After a massive update that came in 2016, Google Translate now hits numbers like 5. Machine translation capabilities are advancing by leaps and bounds.
In 2015, Google Translate scored 3.6, far worse than the average human translator who scored around 5.1.
After a massive update that came in 2016, Google Translate now hits numbers like 5. Machine translation capabilities are advancing by leaps and bounds.
In 2016, the UN released a dataset online with nearly 800,000 documents that had been manually translated into the six official languages ​​of the United Nations: Arabic, English, Spanish, French, All this information was used to train machine translation algorithms. One of the biggest barriers to human cooperation is falling at an explosive rate. As usual, the changes will create pain and profit. It is time for all of us to start taking action to seize opportunities and address challenges.

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Is machine learning breaking down language barriers?
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