Google says its Translate app now spits back more natural translations. Google said Tuesday that it has vastly improved its Google Translate app, available on phones and the web. The search giant said it's now incorporating "neural machine translation" into the software, which translates whole sentences at a time, instead of breaking the text down to smaller chunks and translating those pieces. That means translations come out more natural, with better syntax and grammar. "It has improved more in one single leap than in 10 years combined," said Barak Turovsky, the product lead for Google Translate, during a press event at Google's San Francisco office. The new translation system is coming to eight of the 103 languages supported by the app.

WIPO Director General Francis Gurry speaks about WIPO's ground-breaking new "artificial intelligence"-based translation tool for patent documents, a new service that hands innovators around the world the highest-quality service yet available for accessing information on new technologies. WIPO Translate now incorporates cutting-edge neural machine translation technology to render highly technical patent documents into a second language in a style and syntax that more closely mirror common usage, out-performing other translation tools built on previous technologies.

Reusability: One of the reasons why AI progress is accelerating is the community is creating more and more reusable components that can be plugged into different domains, frequently attaining performance equivalent to or better than hand-designed algorithms. The 2015 ImageNet challenge was won by a Microsoft system built out of Residual Networks, then in 2016 Microsoft made a speech processing breakthrough via a system that also relied on Residual Networks. Similarly, DeepMind's WaveNet system has been slightly tweaked and re-applied to the domain of neural machine translation (PDF). This kind of re-use is a good thing as it suggests we are beginning to create the right sorts of low-level primitives that general intelligences can be built out of.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

Artificial intelligence is difficult to develop because real intelligence is mysterious. This mystery manifests in language, or "the dress of thought" as the writer Samuel Johnson put it, and language remains a major challenge to the development of artificial intelligence. "There's no way you can have an AI system that's humanlike that doesn't have language at the heart of it," Josh Tenenbaum, a professor of cognitive science and computation at MIT told Technology Review in August. In September, Google announced that its Neural Machine Translation (GNMT) system can now "in some cases" produce translations that are "nearly indistinguishable" from those of humans. "Machine translation is by no means solved. GNMT can still make significant errors that a human translator would never make, like dropping words and mistranslating proper names or rare terms, and translating sentences in isolation rather than considering the context of the paragraph or page."

Have you ever been in a situation where knowing another language would have come in handy? I remember standing on the platform at Tokyo Station watching my train to Nagano -- the last train of the day -- pulling away without me on it. What ensued was a frustrating hour of gestures, confused smiles, and head-shaking as I wandered the station looking for someone who spoke English (my Japanese is unfortunately nonexistent). It would have been really helpful to have a bilingual pal along with me to translate. Bilingual pals can be hard to find, but Google's new translation software may be an equally useful alternative.

Code to train Neural Machine Translation systems as described in our EMNLP paper Effective Approaches to Attention-based Neural Machine Translation. Here, we convert train/valid/test files in text format into integer format that can be handled efficiently in Matlab. This trains a very basic model with all the default settings. We set'isResume' to 0 so that it will train a new model each time you run the command instead of loading existing models. Decode with beamSize 2, collect maximum 10 translations, batchSize 1.

The World Intellectual Property Organization has developed a ground-breaking new "artificial intelligence"-based translation tool for patent documents, handing innovators around the world the highest-quality service yet available for accessing information on new technologies. WIPO Translate now incorporates cutting-edge neural machine translation technology to render highly technical patent documents into a second language in a style and syntax that more closely mirrors common usage, out-performing other translation tools built on previous technologies. WIPO has initially "trained" the new technology to translate Chinese, Japanese and Korean patent documents into English. Patent applications in those languages accounted for some 55% of worldwide filings in 20141. Users can already try out the Chinese-English translation facility on the public beta test platform.

Microsoft hopes to release a mobile app before the end of year to translate multi-lingual conversations involving groups of speakers in real time. Microsoft's new speech-recognition record means professional transcribers could be among the first to lose their jobs to artificial intelligence. Whereas the Microsoft Translator mobile apps that are available today can translate conversations involving two speakers, Microsoft says by the end of the year the new app will support multiple speakers using nine languages. The firm demoed a prototype of a mobile app powered by Microsoft Translator that showed three people engaged in a conversation, each speaking a different language, French, English and German. Each speaker had a phone app, which displayed written text, showing the real-time translation of the other person's speech, as shown below.

The dream of thinking machines goes back centuries, at least to Gottfried Wilhelm Leibniz, in the 17th century. Leibniz (right) helped invent mechanical calculators, independently of Isaac Newton developed the integral calculus, and had a lifelong fascination with reducing thinking to calculation. His Mathesis Universalis was a vision of universal science made possible by a mathematical language more precise than natural languages, like English. The Limits of Modern AI: A Story In the 18th Century the Enlightenment philosopher and proto-psychologist Étienne Bonnot de Condillac imagined a statue outwardly appearing like a man and also with what he called "the inward organization." In an example of supreme armchair speculation, Condillac imagined pouring facts--bits of knowledge--into its head, wondering when intelligence would emerge. Condillac's musings drew inspiration from the early mechanical philosophy of Thomas Hobbes, who had famously declared that thinking was nothing but ...