The company recently switched its Translate feature to the deep-learning Google Neural Machine Translation (GNMT) system. That's an "end-to-end learning framework that learns from millions of examples," the company says, and has drastically improved translation quality. The problem is, Google Translate works with 103 languages, meaning there are 5,253 language "pairs" to be translated. If you multiply that by the millions of examples needed for training, it's insanely CPU intensive. After training the system with several language pairs like English-to-Japanese and English-to-Korean, researchers wondered if they could translate a pair that the system hadn't learned yet.

Google's artificial intelligence (AI) has created its first own language through the use of machine learning, allowing it to improve how it translates languages. The search giant fired up its Google Neural Machine Translation (GNMT) back in September to aid the development of the Google Translate service. Google found that be training the system to learn to say translate English to French and French to Italian it could create a means for the system to translate English to Italian even if it has not studied the language before. The system works by analysing whole sentences of language rather than individual words then inferring similarities between them and other sentences in different languages to seek out common patterns in the languages. By doing this the system can translate a language into another even if it has not seen a translation between the languages before.

Google's AI is not just better at grasping languages like Mandarin, but can now translate between two languages it hasn't even trained on. In a research paper, Google reveals how it uses its own "interlingua" to internally represent phrases, regardless of the language. The resulting "zero-shot" deep learning lets it translate a language pair with "reasonable" accuracy, as long as it has translated them both into another common language. The company recently switched its Translate feature to the deep-learning Google Neural Machine Translation (GNMT) system. That's an "end-to-end learning framework that learns from millions of examples," the company says, and has drastically improved translation quality.

Google's AI is not just better at grasping languages like Mandarin, but can now translate between two languages it hasn't even trained on. In a research paper, Google reveals how it uses its own "interlingua" to internally represent phrases, regardless of the language. The resulting "zero-shot" deep learning lets it translate a language pair with "reasonable" accuracy, as long as it has translated them both into another common language. The company recently switched its Translate feature to the deep-learning Google Neural Machine Translation (GNMT) system. That's an "end-to-end learning framework that learns from millions of examples," the company says, and has drastically improved translation quality.

Google has previously taught its artificial intelligence to play games, and it's even capable of creating its own encryption. Now, its language translation tool has used machine learning to create a'language' all of its own. In September, the search giant turned on its Google Neural Machine Translation (GNMT) system to help it automatically improve how it translates languages. The machine learning system analyses and makes sense of languages by looking at entire sentences – rather than individual phrases or words. Following several months of testing, the researchers behind the AI have seen it be able to blindly translate languages even if it's never studied one of the languages involved in the translation.

What does the Chinese Room problem attempt to demonstrate?

All right, don't panic, but computers have created their own secret language and are probably talking about us right now. Well, that's kind of an oversimplification, and the last part is just plain untrue. But there is a fascinating and existentially challenging development that Google's AI researchers recently happened across. You may remember that back in September, Google announced that its Neural Machine Translation system had gone live. It uses deep learning to produce better, more natural translations between languages. Following on this success, GNMT's creators were curious about something.

Google just made a major upgrade to its Translate app. The company is now using a new technology called neural machine translation -- which aims to make computer-generated translations more similar to those done by humans -- to power its translations in seven new languages. Google says the update should make translations in those languages much more accurate and easier to understand. The company previously rolled out this technology for Chinese to English translations in September. Now, Google is using the same technology to power translations to and from English in French, German, Spanish, Portuguese, Japanese, Korean and Turkish.

All right, don't panic, but computers have created their own secret language and are probably talking about us right now. Well, that's kind of an oversimplification, and the last part is just plain untrue. But there is a fascinating and existentially challenging development that Google's AI researchers recently happened across. You may remember that back in September, Google announced that its Neural Machine Translation system had gone live. It uses deep learning to produce better, more natural translations between languages. Following on this success, GNMT's creators were curious about something.

The Google Cloud, Google's eponymous artificial intelligence platform, is quite the capable little set of services. Its algorithms can handle everything from language translation to the identification of objects and landmarks. On Tuesday, Google Cloud chief Diane Greene announced the formation of a new team, the Google Cloud Machine Learning group, that will manage the Mountain View, California-based company's cloud intelligence efforts going forward. The group will be helmed by Jia Li, former head of research at Snapchat and pioneer behind the feature that lets you attach emojis to real-world objects, and Fe-Fei Li, former director of AI at Stanford. They will oversee a slew of upgrades to Google's cloud services in the coming months, much of which will involve Google Cloud's hardware infrastructure.