Google is diving deeper into artificial intelligence, with the company opening a dedicated machine learning research center in its Zurich office, the search company announced on Thursday, June 16.
The Google Research Europe center will focus on three areas: Machine intelligence, natural language processing and understanding, and machine perception. The research center aims to deliver machine learning that can be put into practical use, to improve the machine learning infrastructure, and to assist the research community overall.
"Google's ongoing research in machine intelligence is what powers many of the products being used by hundreds of millions of people a day -- from Translate to Photo Search to Smart Reply for Inbox," Emmanuel Mogenet, head of Google Research Europe, wrote in the blog post announcing the center.
Mogenet noted machine learning software engineers and researchers will be able to develop products and conduct research at the Zurich center, which also holds the largest Google engineering office outside of the US.
The Zurich office has already developed such things as the engine that powers Google's Knowledge Graph and also the Google Assistant engine for Allo.
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Google Research Europe will collaborate with the company's other research groups around the world. One of the high-profile artificial intelligence research groups at Google is its DeepMind group in London. The six-year-old company acquired by Google in 2014 became widely known when its AlphaGo AI machine beat the top-ranking world Go player Lee Sedol in a five-game match earlier this year.
DeepMind will continue to collaborate with other Google teams, as Google Research Europe focuses on its image recognition and natural language understanding.
Google CEO Sudar Pichai recently told Forbes that embedding artificial intelligence into all of Google’s products is a "big focus" for him. In distinguishing between Google's artificial intelligence experiments like DeepMind's AlphaGo and more practical AI uses, he added, "There are things you can do now, some in two to three years and some that are deeper and will take more time to do. With Deep Mind and even some of our internal teams, we are focused on long-term AI."