China’s biggest online commerce company is making big strides in the field of artificial intelligence. The Alibaba Group has developed a machine-learning model which scored higher than human users on the Stanford Question Answering Dataset.
The dream of in-ear real-time translation goes back at least as far as Douglas Adams’s Babel Fish, a little alien that fits in a human ear, feeds on brain waves and, miraculously, excretes translations into the ear canal.
A team of engineers at the University of Antwerp in Belgium has developed a 3D-printed robotic arm that can act as a sign language translator for deaf people.
There have been some drastic changes in the way that people are able to lead their lives over the past decade. The internet has connected people across the globe in ways that we never previously thought possible.
RAY KURZWEIL HAS invented a few things in his time. In his teens, he built a computer that composed classical music, which won him an audience with President Lyndon B. Johnson.
A buried line in a new Facebook report about chatbots’ conversations with one another offers a remarkable glimpse at the future of language.
Human translators will face off against artificially intelligent (AI) machine translators next week in Seoul, South Korea. The competition, sponsored by Sejong Cyber University and the International Interpretation and Translation Association (IITA) will pit human translators against Google Translate and Naver Papago.
I’M SORRY, Dave. I’m afraid I can’t do that.” With chilling calm, HAL 9000, the on-board computer in “2001: A Space Odyssey”, refuses to open the doors to Dave Bowman, an astronaut who had ventured outside the ship. HAL’s decision to turn on his human companion reflected a wave of fear about intelligent computers.
The gap between human and machine translators could be narrowing as researchers find a new way to improve the learning capabilities of Google Translate’s neural network.
On the same day that Google announced its translation services were now operating with its Neural Machine Translation (NMT) system, a team of researchers released a paper on arXiv showing how its NMT could be pushed one step further.
Of the vast wealth of information unlocked by the Internet, most is plain text. The data necessary to answer myriad questions – about, say, the correlations between the industrial use of certain chemicals and incidents of disease, or between patterns of news coverage and voter-poll results – may all be online. But extracting it from plain text and organizing it for quantitative analysis may be prohibitively time consuming.
Google has just created possibly the world’s best computer program designed to understand the English language but this cutting-edge technology may just be the tip of the iceberg.
A new theory could be about to unlock the secrets of how natural human language really works, putting an end to a question that has troubled linguists for more than half a century.