Google announces artificial intelligence group for Google Cloud

When Google Translate launched a decade ago, its phrase-based algorithms simply looked up individual words, replaced them with the equivalent word in another language, and pieced them together.

The company also noted that the progress it has made in translation accuracy with the new Neural Machine Translation system is bigger than what it achieved in the past ten years combined with the old phase-based system. That results in much more natural translations. Over time, Google also plans to bring Neural Machine Translation to all 103 languages which Translate now supports. It then arranges and adjusts the translation to package it with proper grammar as to sound more human-like. The technology enables a higher degree of accuracy in translation as well as making them easier to understand. It lets you make music using machine learning, wherein you just need to play a new notes to see how it would respond. They may just be a few languages but they already represent one-third of the world’s population.

Mr Barak Turovsky, the product lead for Google Translate, was cited on CNET as saying that the new method cuts down on errors by 55 to 85 per cent.

However, as the company pointed out, this only the beginning of a process that can potentially revolutionize the way we interact with translation engines. While limited to eight languages now only, the new system will be available for all 103 languages that Google Translate supports eventually.

That is not the end of the latest update. “Today also marks an exciting next step in Google Cloud’s product commitment to make machine learning more accessible for all businesses”. In my case, Google’s neural network easily racked up 4-out-of-6 of my disgusting drawings, which I think is considerable.

Part of the reason for the competition is that there are only so many A.I. workers available and that “the universities aren’t graduating PhD level” candidates as fast as Google would like, Craft said.

But when a single attention mechanism is used for multiple languages, the system can be coaxed into learning to translate between pairs of languages it hasn’t encountered before – something the researchers call “zero-shot translation”.