Google Opens Machine-Learning Center in Zurich

Overall, the teams working under Zurich will focus on improving the infrastructure of the now trending artificial intelligence, broadly facilitating research for the community and enabling it to be put to practical use. It was also the first time voice searches grew faster than text-based searches, with voice making up roughly 20pc of all mobile searches, according to Behshad Behzadi, director of conversational search at Google.

Google’s machine learning powers many of its tools including Translate, Photo Search, SmartReply for Inbox and many more.

Google Zurich, the company’s largest engineering office outside the USA, is behind the engine that powers Knowledge Graph and the conversation engine that powers the Google Assistant in the recently announced Allo messaging platform.

Google is extended its research facility with new European research centre, dedicating its resources to the advancement of this technology. Think image recognition, understanding natural language and creating neural networks that can learn tasks and improve over time.

Based in Zurich, Switzerland, the new unit called Google Research, Europe is one of largest Google’s engineering office outside US.

It uses new and classical learning algorithms to find these relationships and infer what the algorithms can interpret about the relationships. “The only limiting factor will be talent”, he told journalists gathered in Zurich to hear more about Google’s AI plans.

Following Google’s recently launched Assistant, the company’s European research team on artificial intelligence would be under the expertise of Emmanuel Mogenet plus up to a few hundred colleagues.

NLP involves words in context, viewing words as parts of speech and checking their semantic values.

The significance to understand words and word usage via NLP affect searches, user interfaces, and cross-culture and cross-language communications. Those are Machine perception, Machine intelligence and natural language processing. The study will include tackling an artificial intelligence software’s ability to understand the underlying symbols in a sound, picture, video or music.

As with NLP (word perception), machine perception converts perceived data to a stable state of understanding for processing.