AI News, Baidu Expands U.S. Research Space With New Silicon Valley Site

Baidu Expands U.S. Research Space With New Silicon Valley Site

plans to double its footprint in Silicon Valley with a second research and development facility, seeking to gain an edge in artificial intelligence technology.

The company has about 1,300 engineers working on the technology across sites in China and the U.S. Baidu suffered a blow earlier this week when Andrew Ng, a leading AI researcher, said he would be stepping down from his role as chief scientist and head of the Sunnyvale office.

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It lives instead in Baidu’s data centers, where servers run complex algorithms on huge volumes of data and gradually make its applications smarter, including not just Web search but also Baidu’s tools for music, news, pictures, video, and speech recognition.

Despite lacking the visibility (in the U.S., at least) of Google and Microsoft, in recent years Baidu has done a lot of work on deep learning, one of the most promising areas of artificial intelligence (AI) research in recent years.

This work involves training systems called artificial neural networks on lots of information derived from audio, images, and other inputs, and then presenting the systems with new information and receiving inferences about it in response.

Ng, whose move to Baidu follows Hugo Barra’s jump from Google to Chinese company Xiaomi last year, is one of the world’s handful of deep-learning rock stars.

Google’s search engine is far more popular than Baidu’s around the globe, although Baidu has already beaten out Yahoo and Microsoft’s Bing in global popularity, according to comScore figures.

And Baidu co-founder and chief executive Robin Li, a frequent speaker on Stanford’s campus, has said he wants Baidu to become a brand name in more than half of all the world’s countries.

Now that Ng leads Baidu’s research arm as the company’s chief scientist out of the company’s U.S. RD Center here, it’s not hard to imagine that Baidu’s tools in English, if and when they become available, will be quite brainy —

Unlike Silicon Valley’s tech giants, which measure activity in terms of monthly active users, Chinese Internet companies prefer to track usage by the day, Ng said.

Now the Silicon Valley researchers are using the GPU cluster and also looking to add to it and thereby create still bigger artificial neural networks.

“We deepened our investment in advanced technologies like deep learning, which is already yielding near term enhancements in user experience and customer ROI and is expected to drive transformational change over the longer term,”

Baidu’s neural networks can work behind the scenes for a wide variety of applications, including those that handle text, spoken words, images, and videos.

Google has the brain trust on image analysis, and Microsoft has the brain trust on speech, said Naveen Rao, co-founder and chief executive of deep-learning startup Nervana.

Google has built up a hefty reputation for applying deep learning to images from YouTube videos, data center energy use, and other areas, partly thanks to Ng’s contributions.

And recently Microsoft made headlines for deep-learning advancements with its Project Adam work, although Li Deng of Microsoft Research has been working with neural networks for more than 20 years.

Key figures in the past few years include Yoshua Bengio at the University of Montreal, Geoff Hinton of the University of Toronto (Google grabbed him last year through its DNNresearch acquisition), Yann LeCun from New York University (Facebook pulled him aboard late last year), and Ng.

Whereas Bengio made strides in training neural networks, LeCun developed convolutional neural networks, and Hinton popularized restricted Boltzmann machines, Ng takes the best, implements it, and makes improvements.