Last fall, Google introduced a new system for machine-assisted language translations, Google Neural Machine Translation system (GNMT), which takes advantage of deep neural networks to translate entire sentences – not just phrases – for greatly improved translations. The company put the system to work in Google Translate for eight language pairs in November, and is today expanding support to three more: Russian, Hindi and Vietnamese. Neural Machine Translation went into action late last year with support for translating to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish. These represent the native languages of around one-third of the world's population, covering more than 35% of all Google Translate queries, the company said at the time. Today's news is also fairly significant in terms of scale, as in the U.S. alone, 1,292,448 people speak Vietnamese; another 836,171 speak Russian; and 586,173 speak Hindi, Google says, citing U.S. census data. And more languages will be added in weeks ahead, including Thai, which didn't quite make today's release.

Last fall, Google introduced a new system for machine-assisted language translations, Google Neural Machine Translation system (GNMT), which takes advantage of deep neural networks to translate entire sentences – not just phrases – for greatly improved translations. The company put the system to work in Google Translate for eight language pairs in November, and is today expanding support to three more: Russian, Hindi and Vietnamese. Neural Machine Translation went into action late last year with support for translating to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish. These represent the native languages of around one-third of the world's population, covering more than 35% of all Google Translate queries, the company said at the time. Today's news is also fairly significant in terms of scale, as in the U.S. alone, 1,292,448 people speak Vietnamese; another 836,171 speak Russian; and 586,173 speak Hindi, Google says, citing U.S. census data. And more languages will be added in weeks ahead, including Thai, which didn't quite make today's release.

This tutorial introduces a new and powerful set of techniques variously called "neural machine translation" or "neural sequence-to-sequence models". These techniques have been used in a number of tasks regarding the handling of human language, and can be a powerful tool in the toolbox of anyone who wants to model sequential data of some sort. The tutorial assumes that the reader knows the basics of math and programming, but does not assume any particular experience with neural networks or natural language processing. It attempts to explain the intuition behind the various methods covered, then delves into them with enough mathematical detail to understand them concretely, and culiminates with a suggestion for an implementation exercise, where readers can test that they understood the content in practice.

Naver and LINE Corp. unveiled their artificial intelligence (AI)-based assistant platform Clova at the Mobile World Congress (MWC) 2017 in Barcelona, the companies reported Thursday. According to Naver and its mobile service subsidiary, Clova, which stands for "cloud virtual assistant," aims at an AI platform that works based on the five human senses. "Clova is a platform that incorporates various AI technologies including vocal, visual and conversational engines," LINE Corp. CEO Idezawa Takeshi said in his keynote at the MWC 2017, Wednesday. The two companies are jointly developing Clova by improving Naver Labs' voice-recognizing assistant service AMICA. They said it will expand the system to have more cognitive capabilities to make it more humanlike.

If trying to order dinner or find your hotel abroad fills you with fear due to your abysmal grasp of foreign languages, don't panic. A new in-ear gadget claims to be able to translate speech like the Babel Fish in The Hitchhiker's Guide to the Galaxy, or the Universal Translator gadget in Star Trek. The system, dubbed the Pilot, will cost $249 and go on sale later this year. It uses two earpieces, one worn by each person in the conversation. The Pilot system comprises two earpieces (shown in three colours above) to be worn by two people who don't speak the same language The Pilot works as a normal set of wireless earphones.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. A woman uses a translation app on her smartphone in Paris on Nov. 4, 2014. If you have ever traveled through a foreign country armed with little more than Google Translate to communicate, you know how awkward it can be to use the app to ask a friendly local for directions to the zoo only to unwittingly end up insulting his sister.

Editor's note: This is the first chapter of a book I'm working on called Demystifying Artificial Intelligence. The goal of the book is to demystify what modern AI is and does for a general audience. So something to smooth the transition between AI fiction and highly mathematical descriptions of deep learning. I'm developing the book over time - so if you buy the book on Leanpub know that there is only one chaper in there so far, but I'll be adding more over the next few weeks and you get free updates. The cover of the book was inspired by this amazing tweet by Twitter user @notajf. Feedback is welcome and encouraged!

Back in September 2016, Google launched its Neural Machine Translation (GNMT) system, which uses deep learning to deliver more natural translations between languages. Google Translate originally supported only a handful of languages when it launched 10 years ago; today that number has risen to 103. Creating a computer system to translate multiple languages is complex. The people at Google who built it wanted to find out just how clever their system was. So they came up with a challenge.

In The Hitchhiker's Guide to the Galaxy, writer Douglas Adams describes a "small, yellow, leech-like creature" called the Babel fish which "feeds on brain-wave energy, absorbing all unconscious frequencies and then excreting telepathically a matrix formed from the conscious frequencies and nerve signals picked up from the speech centres of the brain, the practical upshot of which is that if you stick one in your ear, you can instantly understand anything said to you in any form of language". Botanists have not discovered anything like the Babel fish, but the science fiction of universal translation is rapidly becoming reality thanks to technological advances. Most exciting for Hitchhiker fans is the Pilot earbud, backed by $3.5 million in crowdfunding raised by a startup called Waverly Labs. The company's chief executive Andrew Ochoa says: "We were really inspired with wearable technology and began working on the idea of a smart earpiece that could solve a global challenge. We were a small team back then, but we all came from different backgrounds and spoke different languages, and that's how we came up with the idea."

In his book Outliers, Malcolm Gladwell repeatedly mentions what has become known as the "10,000-hour rule", which states that to become world-class in any field you must devote 10,000 hours of "deliberate practice". Whether or not you believe the 10,000-hour figure, many would acknowledge that to become an accomplished legal professional requires considerable legal, communicative and, particularly in in-house environments, interpersonal skills that are often acquired after a tremendous amount of effort exerted over many years. There has been much hoopla about AI-based legal systems that, some might have you believe, may soon replace lawyers (no doubt causing a degree of anxiety among some legal professionals). There is some misunderstanding among many lawyers, and much of the public, about what AI systems are presently capable of. Can a legal AI, based on current technology, actually "think" like a lawyer?