This new app from Google is designed to preserve the words of fading languages

For many reasons, including globalization and cultural assimilation, a handful of languages, such as English, Spanish, and Mandarin, are dominating the world’s linguistic landscape—and that often comes at the expense of older and less popular dialects, which slowly fade out. It’s estimated that a language goes extinct every 14 days; almost half of the world’s 6,000 to 7,000 languages are endangered. UNESCO has a scale for threatened languages, called the Atlas of the World’s Languages in Danger, where tongues range from vulnerable to critically endangered (the rung on the scale right before “extinct”).

This modern-day reality creates a distressing sense of loss for many people who understandably want to preserve their cultural heritage and keep their family traditions from fading into obsolescence. That’s why Google Arts & Culture is deploying its machine-learning tech to allow anyone in the world to easily find words for common objects in 10 of these endangered languages. Through image detection technology, and partnerships with language preservation groups around the world, the project is curating an ever-expanding glossary of words, to be a source of hope for those with attachments to a historic culture, or of fun for those who simply want to learn about a new language.

The free app is part of Google Arts & Culture’s mission to “democratize access to the world’s arts and culture,” says Chance Coughenour, the Google division’s head of preservation, which it does with the help of 2,500 partners in 80 countries. The division first started by digitizing pieces of museum art for public online access, and it’s now branched into using its tech to help preserve “intangible heritage,” or “the ephemeral part of heritage that is at risk of being lost or endangered,” Coughenour says.

Users can pull up the app, called Woolaroo, on their mobile browsers and take a photo of any object, or a scene containing several objects. Google’s Cloud Vision API, its image recognition system that’s used for such programs as Google Lens, analyzes the photo based on its machine learning data from having processed millions of images, explains Ian Pattison, head of retail engineering at Google Cloud U.K. The app will generate suggestions for each object in a photo—along with the translation for that word in the chosen language, plus an audio pronunciation of that word.

Read more: Fast Company

Has Google made the first step toward general AI?

Artificial Intelligence (AI) has long been a theme of Sci-fi blockbusters, but as technology develops in 2017, the stuff of fiction is fast becoming a reality. As technology has made leaps and bounds in our lives, the presence of AI is something we are adapting to and incorporating in our everyday existence. A brief history of the different types of AI helps us to understand how we got where we are today, and more importantly, where we are headed.

A Brief History of AI

Narrow AI – Since the 1950’s, specific technologies have been used to carry out rule-based tasks as well as, or better than, people. A good example of this is the Manchester Electronic Computer for playing chess or the automated voice you speak with when you call your bank.

Machine Learning – Algorithms which use large amounts of data to ‘train’ machines to properly identify and separate appropriate data into subsets that can be used to make predictions has been in use since the 1990s. The large amounts of data are basically allowing programming machines to learn rather than follow defined rules. Apple’s digital assistant, Siri, is one example of this. Machine translations for processes like web page translation is aso a common tool

Read more: The London Economic

This Is How Google Wants To Make The Internet Speak Everyone’s Language

JAKARTA, Indonesia — When Nurhaida Sirait-Go curses, she curses in her mother tongue.

The 60-year-old grandmother does everything emphatically, and Bahasa, the official language of Indonesia, just doesn’t allow for the same fury of swearing as Batak, the language that Sirait-Go grew up speaking on the Indonesian island of Sumatra.

“On Facebook, on Whatsapp, they speak only Bahasa. So I can’t speak the way I want,” said Sirait-Go, who giggles uncontrollably and covers her mouth with both hands when asked to repeat one of her favorite curse words in Bakat. “I can’t, I can’t! People don’t use these words anymore. … They aren’t on the internet so they don’t exist.”

Batak is one of over 700 languages spoken in Indonesia. But only one language, Bahasa, is currently taught by public schools and widely-used online. For language preservationists, it’s just one more example of how the internet’s growing global influence is leaving some languages in the dust. Linguists warn that 90% of the world’s approximately 7,000 languages will become extinct in the next 100 years. Or, as one prominent group of linguists ominously put it, every 14 days another language goes extinct.

Read more: BuzzFeed News

Google Translate AI invents its own language to translate with

Google Translate is getting brainier. The online translation tool recently started using a neural network to translate between some of its most popular languages – and the system is now so clever it can do this for language pairs on which it has not been explicitly trained. To do this, it seems to have created its own artificial language.

Traditional machine-translation systems break sentences into words and phrases, and translate each individually. In September, Google Translate unveiled a new system that uses a neural network to work on entire sentences at once, giving it more context to figure out the best translation. This system is now in action for eight of the most common language pairs on which Google Translate works.

Although neural machine-translation systems are fast becoming popular, most only work on a single pair of languages, so different systems are needed to translate between others. With a little tinkering, however, Google has extended its system so that it can handle multiple pairs – and it can translate between two languages when it hasn’t been directly trained to do so.

For example, if the neural network has been taught to translate between English and Japanese, and English and Korean, it can also translate between Japanese and Korean without first going through English. This capability may enable Google to quickly scale the system to translate between a large number of languages.

“This is a big advance,” says Kyunghyun Cho at New York University. His team and another group at Karlsruhe Institute of Technology in Germany have independently published similar studies working towards neural translation systems that can handle multiple language combinations.

Read more: New Scientist

Why Google is investing in global translation

The term “language barrier” may soon be outdated as new, powerful translation tools, from apps to widgets to websites, hit the market.

On Wednesday, Google announced its latest translation innovation in a blog post. Google Translate has introduced 13 new languages to its portfolio. The translation system can now translate 103 languages and covers 99 percent of the online population, according to the tech giant’s own estimates.

The news of Google’s language expansion came a little over a month after Skype, owned by rival tech company Microsoft, rolled out real-time text translation over video chat and text conversations with Skype Translator.

With the race to be the preeminent translation tool growing more competitive, what’s at stake and why are tech companies so interested?

Read more: Christian Science Monitor