C&B Notes

The Artificial Intelligence Race in China

Microsoft veteran Qi Lu left the company last year after a bicycling accident. Since recovering, he has become the COO at Baidu. This recent interview touches on a number of interesting things in technology and China. We were particularly interested in his comments on the coming impact of artificial intelligence and Baidu’s strategy for it.

That’s why earlier this year, after leaving Microsoft the previous fall, legendary engineer Qi Lu headed to Beijing to become Baidu’s chief operating officer.   At his former job, he was, among other things, CEO Satya Nadella’s top deputy in helping to lead the company’s AI strategy.  Clearly, he saw more opportunity across the Pacific: In China, 731 million people — nearly twice the entire population of the United States —are online.  Says Lu: “China has the structural advantage.”

How do you describe your AI strategy?

We believe the best way to commercialize AI technology is to build ecosystems.  Essentially, to enable our partners to better accelerate their pace of innovation, using healthy, stable economic models to build strong, long-term win-wins for our developers and partners.  The baseline is Baidu Brain [the term Baidu uses for all of its AI assets].  It’s broader and more extensive than what Microsoft and Google offer today in the United States, because it’s a platform.  We have 60 different types of AI services in our suite we call Baidu Brain.  And we’re the first major company to clearly separate the perceptual and the cognitive layer.  Perceptive capability and the cognitive are related, but they are quite different.  ost of the [other] AI platforms bundle them together…

How does the US market for voice technology compare to the Chinese market?

The home environment is very different.  Because we’re talking about voice interactions. The acoustic environment, the pattern of noises, will be very different.  Alexa, Echo, and Cortana are optimized for American homes.  In my view, this only works in North America and maybe a portion of Europe.  Essentially, the assumption is that you have spacious homes; you have several rooms.  In China, that’s not the case at all. For our target, even for the young generation with high incomes, typically they have 60 square meters [645 square feet], sometimes 90 square meters [970 square feet].  We have better opportunities to globalize DuerOS, because guess what?  A home in Japan, a home in India, or a home in Brazil, is a lot closer to a home in China than a home in North America…

But don’t you think that Amazon’s handicap is on its back end, in that it can’t keep up on the technology side with Google and Microsoft?

I worked on Cortana four and a half years ago.  At the time we all were like, “Amazon, yeah, that technology is so far behind.”  But one thing I learned is that in this race to AI, it’s actually more about having the right application scenarios and the right ecosystems.  Google and Microsoft, technologically, were ahead of Amazon by a wide margin.  But look at the AI race today.  The Amazon Alexa ecosystem is far ahead of anybody else in the United States. It’s because they got the scenario right.  They got the device right.  Essentially, Alexa is an AI-first device.  Microsoft and Google made the same mistake.  We focused on Cortana on the phone and PC, particularly the phone.  The phone, in my view, is going to be, for the foreseeable future, a finger-first, mobilefirst device.  You need an AI-first device to solidify an emerging base of ecosystems.

It’s become so much clearer, living in China, what AI-first really means.  It means you interact with the technology differently from the start.  It has to be voice or image recognition, facial recognition, in the first interactions.  You can use a screen or touch, but that’s secondary.  At Baidu [headquarters], it’s all face recognition-based.  At the vending machine at Baidu, you can buy stuff with voice and a face.  And we’re also working on a cafeteria project.  Our goal is, when you go to a cafeteria, you walk away with food…

You were instrumental in developing Apollo, right?

I am the COO of the company, but I run that business directly.  For the last three plus months, I probably spent about about 40 percent of my time on the autonomous driving technology product — talking to customers; talking to partners.  Essentially, from where things are today, toward the future of being able to be fully autonomous, the fundamental technological path for the self-driving technology is the speed of iterations.

What does that speed depend on? 

Essentially, how much data you can get.  Because to be able to drive on the road, you have to drive different kinds of roads in different kinds of conditions — lighting, weather, whether it’s wet, how much physical pressure is on your tires.  And with Apollo, we will be able to pull together all the resources, particularly the data resources, in a way that enables everybody to be better off.

We wrote a manifesto of Apollo.  Essentially, there are four principles.  Each is important. One is open capability. At Baidu, we open up our capability — in code, in services, in data — to all partners.  This works particularly well in China, because China is highly, highly fragmented. There’s more than 250 car OEMs [original equipment manufacturers], unlike the United States, which is a heavily concentrated industry. None of the OEMs will have the full capabilities to build out deep R&Ds.  With our code base that we released on July 5, [we will make it possible for] one person to assemble a vehicle in three days that can do autonomous driving in limited forms and start on R&Ds.

The second is shared resources.  Essentially, with the Apollo design, there are two tiers.  You are able to use the Apollo code and capability, and some data sets, with no strings attached.  The second tier is enables you to use all the data that Baidu provides — HD maps, the training data — but we ask you to contribute your data.  However, there’s a key principle.  The more you contribute, the more you should be able to get back.

The third principle is the accelerating pace of innovation.  Essentially, because we’re able to put together more data, we are able to achieve more capability in our simulation engines.  We enable everybody, collectively, to innovate at a much faster pace.

And the fourth principle is sustained win-win.  Baidu is the biggest model.  It’s going to focus on delivering high-end services, high-value services, HD maps, [and] security services.  We’re competing against nobody.  We enable each OEM, whether it’s Bosch, Continental, or Nvidia, to be able to do more.

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