#47 - Baidu's COO, Qi Lu Discusses AI with Daniel Gross

**Craig Cannon** (0:00)
Hey, this is Craig Cannon, and you're listening to Y Combinator's podcast. Today's episode is with Qi Lu and Daniel Gross. Qi is the COO of Baidu, and Daniel's a partner here at YC. So just before we get going, if you haven't yet subscribed or reviewed the podcast, it'd be awesome if you did.
All right, here we go. All right, hello. My name is Daniel, I'm a partner at Y Combinator, and I'm here today with Qi Lu, who's the COO of Baidu, and is in particular focused on a lot of their AI strategy.
So Qi, thank you so much for coming today.

**Qi Lu** (0:32)
You bet, thanks for having me.

**Craig Cannon** (0:34)
Cool, so I guess first question that is on my mind is, and I think many others, is help us understand why you left, you're previous to Baidu, you were very senior at Microsoft, and a lot of us are wondering why you decided to leave to Baidu.

**Qi Lu** (0:52)
So, two things, one is I left Microsoft purely for personal reasons, because I had an injury.
I broke my left hip, so I needed a second surgery and need to take some time off, because my job at Microsoft was very critical to the company, I thought it's for the best interest of the company for me to move on. A great thing was that I had a good successor who was extremely capable, I'm super happy that he is taking over and leading the company's productivity business moving forward. And in particular, also I was able to have a very good relationship with Microsoft. I continue to serve as the personal advisor to the CEO Satya Nadara and also to Bill Gates. So when I go back to Seattle, I often go see them.

**Craig Cannon** (1:51)
And then how did you decide to go to Baidu as opposed to any other place?

**Qi Lu** (1:55)
Yeah, so that's for a simple reason, which is AI plus China, because we all know, I guess most people in our field will agree, AI is the next big wave. I think AI plus China is particularly meaningful because in my views, China has a structural advantage in terms of AI technological development and commercializations.
In that context, Baidu offers a very unique opportunity for me. First of all, Baidu, in many ways, is the Google of China. Its heritage was so changing, and as a result, from an engineering capability perspective and a cultural perspective, is uniquely positioned to seize the AI opportunity. And also, I happen to be a friend, knows Robin Li, the founder and CEO, for almost 20 years. So there's a lot of long-term relationship and trust, so that was just a good opportunity for me to take on.

**Craig Cannon** (3:08)
So in what ways is China's approach to AI different from America's?

**Qi Lu** (3:14)
I think, first of all, I think it's environmentally different. And approach-wise, I'll come back to the approach aspects from my advantage point.
From environmental perspective, I think China has unique structural advantage for AI technological development and commercialization of AI technologies, for a simple reason.
If I may just explain my thinking on why this is so. Because in this wave of technology development, there's one aspect that is fundamentally different from previous generation of big technology wave, which is data plays an essential role. Because I often use this as a simple example.
You can have 10,000 engineers, great engineers, or you can have many great engineers. You will not be able to build a system that understands human conversations. You will not be able to build a system that will recognize objects or scenes of images because you need to have data.
A simple analogy is very much like human. When you and I grow up, it's not like our parents or god is writing coding to our brains.
Our built-in neural engines has the ability to learn through our sensory systems, essentially our perceptive systems, whether it's visual systems or whether it's auditory systems, that we are able to observe the world and our observation, those sensors, these are data because these data carries knowledge and we are able to learn from our interaction with the world. So as we grow up, we acquire knowledge. And the same thing happens for AI technology. It's not about writing code this time. It's about writing code that implements AI algorithms with both software and hardware. They are able to learn and learn knowledge from the data. So if you take that perspective, data, data in my view is for the AI era, what becomes a primary means of production, which is by definition means of production is a form of capital. Because you look at historically in our human history, let's say in the agriculture era, land is the primary means of production, so that you can see everything is organized around the land. All the walls are competing for land. In the industrial eras, the means of production is primarily labor and equipment, different types of equipment, and certainly financial capitals, human talent. But in the AI era, my view is data will become the primary means of production. So harnessing data becomes key. And then comes back to China, because China has a different social, economical policy environment that makes for certain segments, not on everything, for certain segments, it's much easier to acquire and harness data. And with that, it creates an environment for developing AI technologies, and then commercialize those technologies towards market-oriented applications or social applications. So in that context, China has a structured advantage. And in terms of approach, there will be cultural differences, even in entrepreneurial world, or the startups in China environment, they tend to work in their ways. That, I would say, Silicon Valley and China, there's commonalities, there's some different approaches, but that's not the bigger factor. In my view, it's the environment that's the more determinant factors making China to be relatively compared to other marketplaces or other regions a better place for AI development because of data.