The avid reception helps explain why Baidu has made Ng, 38, the linchpin of an effort to transform itself into a global force. The company hired him in May to head its research organization, which includes a new artificial-intelligence lab in Silicon Valley and two labs in Beijing, one focused on deep learning and the other on large-scale data analysis. Often called China’s Google, the company plans to invest $300 million in the new lab and a development office on the same floor over the next five years. Ng (it is pronounced “Eng”) aims to hire 70 artificial-intelligence researchers and computer systems engineers to work in the new lab by the end of 2015. “It will really target fundamental technology,” says Kai Yu, the director of Baidu’s Beijing deep-learning lab, a friend of Ng’s who urged him to join the company.
Baidu, which hopes to get half its revenue from outside China by 2020, is just one of several large Chinese Internet companies now looking abroad for talent and customers, seeking to make the most populous nation on earth more than just the world’s factory. With 632 million citizens online, China claims four of the planet’s 10 most-visited Internet properties, up from just one a year ago. The top 20 Chinese Internet companies listed on public exchanges outside mainland China have a combined market value of about $340 billion. The social-networking giant Tencent, whose WeChat mobile messaging service has 100 million registered users from outside China, accounts for almost half of that. And in September, the e-commerce group Alibaba was expected to complete what could be the world’s largest initial stock offering ever. Its debut on the New York Stock Exchange could value it at $150 billion.
Andrew Ng hopes to lure AI talent to Baidu’s new Silicon Valley research lab.
As they look beyond China, Baidu and other Chinese companies find themselves on a collision course with the established U.S. Internet leaders. It’s unlikely that companies such as Google, Facebook, and Amazon will be in danger in Western markets anytime soon. But the field is wide open in much of the rest of the world, where billions of people aren’t yet online. Here, companies like Baidu believe they have an advantage because of their experience with customers who are relatively new to the Internet, says Jixun Foo, a managing partner at the venture capital firm GGV Capital and an early investor in Baidu at a previous firm. “Chinese companies are starting to dream,” he says.
Cool Things
The first thing you notice about Andrew Ng is his voice. Extraordinarily gentle, it is almost a whisper, and his speech carries traces of his birth in London and childhood in Hong Kong and Singapore. As he patiently explains the nuances of deep learning, he sounds as if he’s reading a bedtime story to a child. At times, he’s scarcely audible above the clack of billiard balls as engineers on a break play pool in Baidu’s still largely empty Silicon Valley lab, a 15,000-square-foot office space in Sunnyvale, a few minutes southeast of Google’s headquarters. But when Ng turns to his mission at Baidu, his voice rises above the background noise.
Maybe that’s because the mission is a grand one: to change the world with artificial intelligence. Ng says he will focus on projects that could “significantly influence” the lives of at least 100 million people. That, he adds pointedly, means more than creating “shiny” apps that rise and fall on the whims of teenage fashion. “Who knows who’s going to be the next—boy, I’m even losing track—Snapchat?” he says in a rare flash of snark. “When you build some of the hard technologies that companies like Baidu try to, it gives you a more lasting base to build on.”
Ng’s work on artificial intelligence has shaken up a major search company before. He is best known for a project referred to as the Google Brain, which he helped set up inside the secretive Google X research lab in 2011. The project was designed to test the potential of deep learning, which involves feeding data through networks of simulated brain cells to mimic the electrical activity of real neurons in the neocortex, the seat of thought and perception. Such software can learn to identify patterns in images, sounds, and other sensory data. In one now-famous experiment, the researchers built a “brain” with one billion connections among its virtual neurons; it ran on 1,000 computers with 16 processors apiece. By processing 10 million images taken from YouTube videos, it learned to recognize cats, human faces, and other objects without any human help. The result validated deep learning as a practical way to make software that was smarter than anything possible with established approaches to machine learning. It led Google to invest heavily in the technology—quickly moving the Google Brain software into some of its products, hiring experts in the technique, and acquiring startups (see “: Deep Learning,” May/June 2013).
Baidu is one of many Chinese Web companies on a collision course with Internet leaders such as Google, Facebook, and Amazon as they look abroad for new customers.
Ng, who calls deep learning a “superpower,” will build a new generation of such systems at Baidu. Services that may result remain in the brainstorming stage, but he will hint at what they may be. He dreams of a truly intelligent personal digital assistant that puts Apple’s Siri to shame, for example. Looking further ahead, the technology could transform robotics, a pet subject for Ng—his engagement photos were taken in a robotics lab—and make autonomous cars and unmanned aerial vehicles much more capable. “We’re going to do some cool things here,” he says with a grin.
They’ll have to if they are to compete: Google, Facebook, Microsoft, and others have been hiring lots of deep-learning experts for their labs, sometimes even from each other. And Baidu still has a lot to prove. Fairly or not, it has the reputation many Chinese companies do for copying the products and business models of U.S. Internet leaders. It’s a process cynics dub C2C—“copy to China.” Baidu has seemingly tried to emulate Google in countless ways over the years, from its spare search homepage to a head-mounted computer, Baidu Eye, that looks a lot like Google Glass. Baidu has even begun working on self-driving cars. With its new star hire, it appears to be following Google’s lead once again.
Ng insists that the C2C stereotype is no longer accurate, particularly for his new employer. “I used to work for the USA’s Baidu,” he jokes. Then he picks up his phone and says in English, “Please call a taxi for me.” A moment later, Baidu’s translation app utters the same phrase in Mandarin Chinese and shows the equivalent ideograms on the screen. It’s slick—but is it better than Google’s translation app, which appears to do the same thing? That’s not clear. It’s Ng’s job to develop cutting-edge technologies that will leave no doubt who is ahead.
Out into the World
Baidu’s Silicon Valley lab is led by Adam Coates, a 32-year-old who stumbled into artificial intelligence quite by accident. As a Stanford computer science student in 2002, he got talking with Ng, who mentioned that he was working on a project involving remote-controlled helicopters. Coates had built and flown them while at high school in California’s Napa Valley resort town of Calistoga. Ever since, the two have done research together, writing papers on using machine learning for unmanned helicopters, household robots, and image recognition. When Ng left Stanford for Baidu, Coates, then a postdoctoral researcher in Ng’s lab, followed. By then, he had begun to see that machine learning would be crucial to just about everything. “It doesn’t matter whether you’re really excited about language or helicopters,” he says. “You can use it to solve any problem.”
Ng and Coates have one key quest for their new lab: creating software that can, in a real sense, learn on its own. Until recently, most improvements in areas like speech and image recognition came by training software with data that had been laboriously labeled. For example, teaching software to spot cats would require a database of thousands of images, with any cats identified by humans. You don’t have to be an artificial-intelligence expert to see the main drawback of that approach, known as supervised learning. No human child needs to see 50,000 labeled images to recognize a kitty. “We wander around the world and see how things work,” Coates says. “The hope is that we can find algorithms that learn the same way.” Deep-learning systems might still need to see a lot of cats to spot one on their own, but they can be much more useful because they need minimal human help.
Software intelligent enough to understand the images, text, and sound in our lives could make decisions for us and take on jobs such as answering simple e-mails.
Software smart enough to understand the images, text, and sound in our lives could use that information to make decisions on our behalf—and transform our relationship with technology, says Coates. For instance, it might analyze your vacation photos and recognize the people shown in each one, identifying what they’re doing and recognizing landmarks. Then you could find an old shot later by asking for, say, “photos of Mom on the beach.” Or you could snap a photo of a shirt with your phone and ask it to find others like that, trusting that instead of just seeing an arrangement of colored pixels, it would apply an understanding of clothing styles, fabric, and your personal taste. Ng envisions our cell phones being able to recognize speech as well as humans can, so you could at last reliably dictate text messages even in a noisy car. He hopes to see e-mail apps that can learn from your interactions with friends and colleagues and then start answering some simple messages on your behalf. Looking further ahead, Ng and Coates may also get a chance to continue their research on robotics, says Yu. “We’re not only interested in cyberspace but physical space,” he says.
First, however, the Baidu lab in Silicon Valley will try to make it easier to test out deep-learning software, which requires enormous computing power. Training a new speech recognition model can take a week or more, a period Ng would like to cut in half. Last year Coates led a Stanford team to a breakthrough that makes that goal realistic. They built a neural network that roughly matched the Google Brain system for a 50th of the cost—only $20,000—using off-the-shelf graphics chips from Nvidia. That approach could help Baidu get powerful deep-learning infrastructure running at relatively low cost. And it fits well with the company’s existing work in Beijing, where simpler clusters of graphics chips have already been used to train deep-learning systems for image and speech recognition.
Air of Mystery
Walking around Baidu’s headquarters along the technology corridor in Beijing’s Haidian district, you might be excused for thinking you had somehow teleported to the fabled Googleplex in Mountain View, California. Free cafeteria? Check. On-site gym? Check. Sleeping pods? Check. Jeans and shorts, T-shirts, flip-flops? Check, check, check. About the only thing breaking the illusion is a giant Baidu bear-paw logo sculpted into the lobby ceiling. It all seems to reinforce the C2C stereotype Ng and others try so hard to quash. And Kai Yu happily boasts that the similarities to U.S. Internet companies are more than skin deep. Like them, Baidu favors flat management, small teams, fast product cycles—and, he adds, his whole face brightening, cool technologies. “Baidu is not so different from a Silicon Valley Internet company,” says Yu, who ought to know: he spent six years working at NEC Labs America in Cupertino, two miles from Apple headquarters.
Dig into the history of Baidu, however, and you’ll find it has Valley roots of its own. CEO Robin Li cofounded the company in 2000 with biotech salesman Eric Xu, after a stint as an engineer at the Sunnyvale-based search engine Infoseek. Li was armed with a patent for a way to rank sites in search listings by the number of incoming links—filed in 1997, a year before Google cofounders Sergey Brin and Larry Page patented their similar PageRank algorithm. As China’s Internet population grew, so did Baidu, enough to attract a $5 million investment in 2004 from Google itself—which later tried to buy Baidu for $1.6 billion in an attempt to head off the Chinese company’s IPO, according to Bloomberg Businessweek. Instead, Baidu went public in August 2005, and shares rocketed 354 percent the first day. Much as Google had done in the United States, Baidu quickly solidified its hold on China’s search market and used the profits to expand into a range of other online services.
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