Mr. HUANG talked about the challenges facing the industry in the era of AI and how it could translate those challenges into opportunities. He pointed out that the emergence of neural machine translation, the application of speech interactive technology and the rapid development of the Internet Era had a huge impact on traditional human translation. Though the industry has begun to realize the importance of AI and other technologies, the mechanism and platform to promote their application is still lacking. Mr. HUANG believed that governments, language colleges, language and AI service providers, experts and freelance translators should join hands in exploring this topic and advise the industry on development in the new era. In addition to the guidance of government and industrial organizations, an effective cooperative mechanism shall be established to ensure the maximum synergy between colleges, research institutes and language service providers.

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!

The potential usefulness of automatic computerized translation was recognized by the very first AI researchers in the 1950s. But it wasn't until new algorithms emerged in the 1980s and 1990s that the field made significant progress. Now, translation tools of great sophistication are playing a growing role in both everyday office use and for specialized fields, as the economy becomes increasingly globalized and companies sell products and services in multiple markets. The poster child for computer translation is Google Translate, the easy-to-use, general purpose Web-based translation engine that can handle nearly 60 languages. Google's Translate has the same 800-pound gorilla status in its world that the company's namesake product does in search.

A renewed international effort is gearing up to design computers and software that smash language barriers and create a borderless global marketplace. A woman sits at a desk in Manhattan, talking to herself in French. The phrases she balances on each breath are musical to American ears. She has postcards of Montreal tacked up on the walls of her cubicle – pastel-painted houses in the snow – so as she sculpts the contours of each syllable, she can remind herself of the place where the sounds she's making are heard every day in the street. Her name is Guylaine Laperrière, and she came to New York City more than a decade ago to study musical theater. One day, a friend asked her if she wanted to make a little cash dubbing a French voice-over for a promotional short about insurance. She took the job, and was surprised how much she enjoyed bringing ideas from one language home into another. This article has been reproduced in a new format and may be missing content or contain faulty links.

Compiled by Carl Zimmer (zimmer@panix.com) Natural Language Laboratory, School of Computing Science, Simon Fraser University Burnaby, British Columbia Researchers are devising "relaxed grammars" to extract the sense of transcribed speech through a method known as "partial parsing," which deciphers chunks of language rather than breaking down the structure of entire sentences. Their work is being integrated into closed-captioning technology for real-time TV translations. This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue.

This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. The outcome is a halt in federal funding for machine translation R&D. Darpa launches its Spoken Language Systems (SLS) program to develop apps for voice-activated human-machine interaction. Researchers focus on portable systems for face-to-face English-language business negotiations in German and Japanese.

Running software that took four years and millions of dollars to develop, Carbonell's machine – or rather, the server farm it's connected to a few miles away – is attempting a task that has bedeviled computer scien tists for half a century. The message isn't encrypted or scrambled or hidden among thousands of documents. I brought along the text, taken from a Spanish newspaper transcript of a 2004 al Qaeda video claiming responsibility for the Madrid train bombings, to test Meaningful Machines' automated translation software. The brainchild of a quirky former used-car salesman named Eli Abir, the company has been designing the system in secret since just after 9/11. Now the application is ready for public scrutiny, on the heels of a research paper that Carbonell – who is also a professor of computer science at Carnegie Mellon University and head of the school's Language Technologies Institute – presented at a conference this summer. In it, he asserts that the company's software represents not only the most accurate Spanish-to-English translation system ever created but also a major advance in the field of machine translation. This article has been reproduced in a new format and may be missing content or contain faulty links.

Imagine it's the 1950s and you're in charge of one of the world's first electronic computers. A company approaches you and says: "We have 10 million words of French text that we'd like to translate into English. We could hire translators, but is there some way your computer could do the translation automatically?" Original story reprinted with permission from Quanta Magazine, an editorially independent division of SimonsFoundation.org whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. At this time, computers are still a novelty, and no one has ever done automated translation. But you decide to attempt it.

The guide was written in German, which Casey cannot read, so she typed bits of it into an Internet translation tool. "It occurs nobody endlschleudern, however, intercatapults" is one result she got. Stumped, she pressed some buttons and eventually managed to wash her clothes, in an elongated wash cycle that kept her pinned down for three hours. Libby's quandary will come as no surprise to anyone who has tried to use a computer to translate things. For decades, machine translation was mostly useful if you were trying to be funny.

Captain Kirk had the universal translator, Arthur Dent had the Babel fish -- and the rest of us have smartphones. Neither the universal translator nor the Babel fish chew up your 4G data allowance, potentially costing you an arm and a leg on your overseas vacation. Software developers are creating more mobile translation tools that you can use offline. Software developers are creating more mobile translation tools that you can use offline. Luckily for you, though, the translator gap is narrowing as more developers create apps with helpful offline modes that let you do your translating at your leisure, without worrying about the bill.