- Chi Lu, COO of Baidu, left Microsoft due to personal reasons and joined Baidu because of the AI potential in China.
- China has a structural advantage in AI development and commercialization due to its ability to acquire and harness data.
- The Chinese government is more willing to invest in AI infrastructure and talent, seeing it as an opportunity for innovation and growth.
- Baidu operates independently but collaborates with the government when there are mutually beneficial opportunities.
- China may beat the United States in mass adoption of self-driving cars within the next 3 to 5 years.

- The speaker believes that China has the opportunity to surpass the United States in autonomous driving technology within the next 3 to 5 years.
- The Chinese government sees autonomous driving as a way for the country's auto industry to advance and become a global leader.
- Baidu, a Chinese tech company, is partnering with municipal governments to develop initiatives such as autonomous vehicle certification programs and new infrastructure designs.
- The speaker believes that China will see larger-scale deployment of autonomous driving technology in the next few years.
- The speaker discusses cultural differences in engineering and product development between China and the United States, noting that Chinese product people are more philosophical and reflective.

- The speaker believes that product people in Chinese companies, particularly Baidu, are better than those in US companies.
- There is a belief that Silicon Valley is more creative and allows for more free thought, while China is seen as structured and good at implementation.
- Baidu and Tencent are exceptions to the top-down nature of Chinese companies, as they empower teams and leaders to innovate.
- The speaker believes that while China is closing the gap in AI research with top universities in the US, the overall environment and culture is not yet conducive to truly groundbreaking research.
- The speaker hopes that in the next 5 to 10 years, China will have research organizations equivalent to OpenAI and DeepMind.
- Baidu and other companies are investing in corporate research labs, while national labs and universities are also increasing their research efforts.
- The speaker does not provide a clear view on China's approach to cryptocurrency, but mentions that Baidu sees blockchain as a fundamental technology for its financial services business.

- Baidu offers financial services and is developing core infrastructures to modernize traditional financial institutions.
- Baidu is using blockchain-based technologies to build data platforms and anticipates the increasing importance of data ownership and value attribution.
- Baidu aims to attract top-tier talent to its research lab in Silicon Valley and collaborate with universities.
- Baidu believes that China has the opportunity to become a top-tier talent importer and wants to be one of the top choices for graduates from prestigious universities.
- Baidu is building products for the Chinese market with the goal of globalizing them, focusing on smart home products.
- The company emphasizes the importance of strong engineering foundations, understanding product context, and embracing business models.
- Baidu values a learning and iterative experimentation culture and looks for people who understand future mainstream users' needs and can see through the noise to identify underlying trends.

- The speaker believes that understanding human needs and anticipating future usage patterns will be highly valuable in the future job market
- They emphasize the importance of product sensitivity in all lines of work, as it helps individuals perform their jobs better
- The speaker suggests reading articles and comments on hackernews.github and getting hands-on experience with coding to figure out what one loves to do in the AI or software engineering field
- The speaker initially wanted to be a philosopher but ended up in computer science due to pragmatic constraints and fell in love with the field
- They no longer code but continue to read code and understand core algorithms and system architecture
- The speaker acknowledges the challenge of balancing involvement in algorithms without micromanaging and emphasizes the role of challenging and debating with team members while allowing them to make decisions
- They mention Bill Gates' similar approach of staying mentally sharp by understanding code and surrounding oneself with talented individuals

- The speaker suggests picking a few key technologies to have a deep understanding of, in order to calibrate other systems and prevent people from bullshitting.
- They emphasize the importance of being able to do the job two levels down in management to ensure honesty and hard work from employees.
- The speaker mentions their own practice of studying core algorithms and systems to set the tone for honest discussions.
- They discuss the concept of giving more autonomy to leaders in organizations, while still orchestrating efforts towards a common mission.
- Motivation and structure are identified as key factors in designing organizations that unleash innovation.
- The speaker mentions their personal principles of learning every day and maintaining integrity.

- Integrity has three subsets: always speaking truthfully, keeping one's word, and acknowledging mistakes or weaknesses.
- Being frugal and saving financial resources is important.
- There are five important things: integrity, learning every day, work ethics, work-life balance, and one more thing (not remembered).
- These beliefs guide the speaker's actions and are shared with their teams at Microsoft.

- Chi Lu, COO of Baidu, left Microsoft and joined Baidu due to the potential of AI in China.
- China has advantages in AI development and commercialization due to data acquisition and government investment.
- Baidu collaborates with the government and is partnering with municipal governments for autonomous driving initiatives.
- China may surpass the US in self-driving cars within 3 to 5 years.
- Baidu aims to attract top talent and globalize its products, focusing on smart home products.
- Baidu values strong engineering foundations, understanding product context, and embracing business models.
- The speaker emphasizes the importance of understanding human needs and anticipating future usage patterns in the job market.
- They suggest reading articles, getting hands-on coding experience, and understanding core algorithms.
- The speaker emphasizes the importance of integrity, learning every day, work ethics, work-life balance, and one more thing.

Qi Lu is the COO of Baidu - https://twitter.com/qilu

Daniel Gross is a Partner at YC - https://twitter.com/danielgross

And I'm here today with Chi Lu, who's the COO of Baidu and is in particular focused on a lot of their AI strategy.

So, Chi, thank you so much for coming today.

So, I guess first question that is on my mind is, and I think many others, is help us understand why you left your previous to Baidu.

You were very senior at Microsoft And a lot of us are wondering why you decided to leave to Baidu.

1 is I left Microsoft purely for personal reasons.

So I needed a second surgery and need to take some time off because my job at the 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.

And then how did you decide to go to Baidu as opposed to any other place?

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 commercialization.

In that context, Baidu offers a very unique opportunity for me.

First of all, Baidu in many ways is the Google of China.

And as a result, from an engineering capability perspective and a cultural perspective, it's uniquely positioned to seize the AI opportunity.

And also I happen to be a friend, knows Robin Lee, the founder and CEO for almost 20 years.

So there's a lot of long-term relationship and trust.

So that was a just a good opportunity for me to take on.

So in what ways is China's approach to AI different from America's?

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 1 aspect that's fundamentally different from previous generations 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 a million 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 grew 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.

Our observation, those sensor, these are data, because these data carries knowledge and we are able to learn from our interaction with the world.

And same thing happens for AI technology.

It's about writing code that implements AI algorithms with both soft and hardware.

They are able to learn and learn knowledge from the data.

So if you take that perspective, 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.

In the industrial era, the means of production is primarily labor and equipment, different type of equipment, and certainly financial capitals, human talent.

But in the AI era, my view is data will become the primary means of production.

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 structural advantage.

And then in terms of approach, there will be cultural differences, even in entrepreneurial world, 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.

And I guess 1 question I'm wondering in particular is in the US there's this belief that 1 of the ways China's somehow doing better when it comes to technology is that the government is much more integrated with companies and their initiatives.

Is that something that you see it by do, as you guys focus on your different AI initiatives, are you able to work very closely with the government?

In general, the Chinese government at this stage has a lot more willingness to invest in infrastructures, in talent, And they in particular see AI as an opportunity for China to, in many ways, to ride that big wave, to elevate its innovation capacity.

So there was a, about somewhere between 1 month, 2 months ago, there was a white paper that's published by the Chinese government.

It actually spells out pretty much a certain level of details about, by 2030, how the Chinese government plan to systematically invest in infrastructures, talent, and technologies to enable China to lead in AI technologies in many different dimensions.

So in general, the government indeed has a lot more willingness and commitment to invest.

And with regard to private company, particularly a company like Baidu, which is more viewed as culture practice-wise closer to American companies, listed in NASDAQ, Internal working culture is very entrepreneurial, closer to Silicon Valley style.

So we do, in many ways, operate independently.

We view, essentially, market opportunities as the primary objectives to pursue those opportunities.

And when there are wing-wing alignment with the government initiative, we welcome that.

For example, Baidu is the host of a national deep learning labs, And Baidu is also working with various different government entities when they have expressed willingness to support in certain areas of AI technology.

For example, let's say for self-driving cars.

So we will work with those government entities to discuss opportunities that are mutually beneficial.

But as a company, our primary means is market success.

We don't have sort of any other agendas because we are an independent company.

We want to build products that serve our users.

When there is synergistic opportunity with government support, we will collaborate with government when they are truly mutually benefit, mutually win-win.

Do you think that China will beat the United States to having mass adoption of self-driving cars?

So my belief is the opportunity to commercialize and deploy autonomous driving technologies in various forms, China will have opportunities to get ahead of the United States over the next 3 to 5 years.

1 is different regions, whether it's municipality or provincial government or central government, they see this as an opportunity for China's auto industry to get out of where right now the China auto industry does no real strong technology, heavy fragmentation with over 250 OEMs.

The Chinese government very much would like to take the autonomous driving dimension of innovations to enable the Chinese auto industry to leapfrog, to be the world's best and leading the world.

For example, there's 5 municipal governments right now, members or partners of Baidu's open autonomous driving ecosystem, open platform called Apollo.

So they work with us on a variety of initiatives.

For example, new kind of driving schools that will certify autonomous vehicles for different levels of maneuverability.

Just like a driving school today, they will certify human drivers, you know, you pass through a certain test.

And we're working with a new city that is being kind of built up, ground up by the Chinese government plan, will be bigger than Shenzhen, will be bigger than Dubai in 5 to 10 years.

It's a massive new city that's being built up from pretty much 0.

So working with them on designing new infrastructures, new segment of the cities, that makes it much easier for autonomous vehicles to be deployed.

Just as an example, let's say, today's cities, you have streetlights.

And the streetlights in many ways is a sensor device.

It enables the sensors of a vehicle to be able to better see the road.

It just happened to be the 1 area that does the sensing on human, and human use the eyeballs.

When it's dark, you won't be able to see the road, see the separation of the roads, and you have steer lights.

But imagine in the future when the sensor is not done by the human eyeballs, but different sensor, whether it's LiDAR, radar, or cameras, whatever the sensor technology you use, the future city infrastructures, those streetlights, will be intended for non-human sensor capabilities to see the road, to be able to navigate the road.

So we are actively designing those new type of infrastructures and having ongoing discussion with these municipal government to lay out plans to build those infrastructures with the intent to have commercial deployment of autonomous driving in various forms.

So if you combine all those efforts together, I very much believe in the next 3 to 5 years, we'll see autonomous driving in China gets deployed in more variety in larger scales than other markets.

Going back a little bit to kind of more broadly, China and the United States, you were managing very large software engineering teams here in the United States, and now you're doing the equivalent in China.

What are some cultural differences you've noticed in terms of how people work, how you have to manage in between those 2 countries?

Yeah, first of all, Baidu's engineering culture, product culture, is very similar to Microsoft, very similar to what I know of Google, even though I haven't worked at Google, but I have enough interaction with friends who work at Google.

Essentially, very heavy in technology, Very heavy in algorithms, very heavy in large-scale computing, very weak in product design, very weak in understanding user needs, human needs.

As a result, the technology is good, the product generally isn't great.

Just I'm not critiquing or criticizing my former colleagues, but Microsoft as a company in many ways lagged behind companies such as Apple and Facebook in building truly mobile, particularly mobile consumer product that struts the emotional connections with users and whether it's application or services or devices, the fit and the finish, the experience design is very much more than appeal to young demographic, young generations.

Microsoft as a company struggled on that, and I see similar things from what I can see.

Google as a company, their product that I use, and the Baidu is exactly the same way.

I always try to change the engineering culture at Microsoft.

Actually, that was the reason why I broke my leg, but it's a different story.

Because you need to earn, learn, learning new way of doing things.

just tell us about the bicycle that you rode, which is I think how you got that injury?

Yeah, because it was a, there's something called a backward brain bike.

If you search on YouTube how to ride a bicycle, there's plenty of videos.

Essentially, the bike goes the other way.

If you turn the handle this way, the wheel actually goes the other way.

The reason, there's some profoundly important reasons, because first of all, we humans learn, There's 3 primary ways we learn.

And the bicycle riding is often said as the best example because you cannot learn how to ride a bicycle by watching other people riding bicycle, by reading about it, by people telling about it.

You have to ride a bicycle yourself, and often, bumping, bruising, hurting.

It's in the muscle memory, you don't think about it.

And that's the problem for a large organization for cultures, because the reason those big companies, they couldn't survive when you would come, That's based on Professor Rebecca Hedgeson's study at the Harvard Business School.

It's that those material relations, their muscle memory, the way they talk to customer, the day we do research, the day we design experiences was built like 30 years ago.

And they try to think, but their muscle memory don't think.

So if you're asking me why Microsoft couldn't get mobile at all, isn't that we're not working hard, we're working super hard.

We tried everything, we buy Nokia, we build a Katana, You name it, we tried everything.

Rebecca Henderson was the 1 who convinced me this is the real problem.

So, Microsoft colleague of mine, his name is Bill Buxton, he's 1 of a kind of people.

He said, hey, Chi, you should try this bicycle thing.

So we built the bike, Bill Buxton and another 1, the 3 of us, we tried to practice it because this bike, for a normal adult who knows how to bike, takes you about 8 months training every day.

And Once you learn how to ride that bike, you won't be able to ride the normal bike anymore.

And I think for larger organization, culture change is that difficult, because it's your muscle memory, the way you do things.

It just becomes a habit you don't even think about.

Even though the CEO say, we're going to die, you guys have to figure out mobile.

They try, try, try, the mobile product is like a PC product, smaller form, right?

So coming back on culture, I see Baidu has very similar traits of Microsoft that I work with.

So what I'm working on today with Baidu is really to change that engineering culture to be a lot more product-centric, to be a lot more understanding user needs, particularly for mobile product, for AI product.

And then I will briefly answer the engineering culture between companies that are in China versus companies that are in the United States.

There are various different aspects of it.

The biggest thing, and I need to perhaps think more about summarizing in my head what I observed so far, some of the key differences in terms of product engineering culture.

The 1 thing I would say is, start off for me, I learned a lot in my 8 months plus living, working in China, is the product people in China are a lot more philosophical.

They think a lot deeper than what you would typically observe from a product people when they describe their product.

And also the Chinese, the R&D product leaders emphasize a lot more self-reflection.

They use the word cognition but it means a person's ability to understand, to make judgment, make decisions.

Essentially, they emphasize a lot more self-improvement for product people in particular, how you elevate your cognitive capacity.

So if you ask me, the 1 thing stood out for me is I used to believe the product people in the United States companies is better than, now I kind of held the other way around.

I see better product people more often in Baidu, in other Chinese companies than in Rataways, than perhaps I would say on average, the percentage.

Huh, well so on that point, there's another belief, I think, in the West that, you know, California and Silicon Valley are very creative environments, and they really allow ideas to come up and bubble up from any person in an organization, versus China where the image, I guess, that we think to ourselves is a very structured society that is very good at implementing something, but maybe not as good at creative, free thought.

Would you agree with this sentiment at all?

And if so, how do you think that plays out for, say, doing core research that involves a lot of creativity?

So I would say there are different degree of truth towards the top-down nature for Chinese company.

Baidu, even though among the Chinese tech company, Baidu is the kind of the closest in terms of culture to Silicon Valley.

A lot of people, their pedigrees are Google, worked at Google, worked at Microsoft, meaning English is also kind of a common working language.

You won't have any problem if you just speak English or write an email in English.

But Even that, the top-down phenomenon happens.

And my hypothesis was, this is perhaps due to 2,000 plus years of Confucianism.

You know, the Confucius is essentially harmony through hierarchy, right?

So that's the central idea of Confucianism.

So having said that, the company that I work with, including Baidu, all realize driver Innovations is a lot more about empowering teams, empowering capable leaders to experiment, to try new ideas at a fast velocity.

Baidu does a lot of those, and in The startups that I interacted with, they emphasize that aspect a lot.

There's no difference in terms of the belief and the practices than Silicon Valley startups that I see.

The large company, 1 company I'll probably point to, I believe overall does a good job, is Tencent.

Tencent, they have this challenging culture.

Any ideas, they encourage the challenge, the more authoritative senior peoples.

And also, for Any major initiatives or any areas of new innovation, they tend to have 2 teams, 3 teams working on the same thing.

There's a lot more internal competitive dynamics that are going on.

And 1 last thing, in Baidu, we have this quarterly meeting.

We have all our company's directors we have about 200 directors once a quarter we will invite speakers and the past few speakers they all emphasize the aspects of building a learning organization so that a truly thriving organization, each cell, each team, they are able to be nimble, adapt, quickly learn.

So even though there are this couple thousand years of Confucianism, I think it's still somewhat there, reflects to different degree in different companies.

But by and large, driving innovation, empowering teams, empowering leaders are the common understanding.

And everyone in the nation is striving to do more and to better in that regard.

So there's no fundamental difference than Silicon Valley, I would say.

And do you think that Baidu and Tencent then are kind of the exception to the rule?

Do you guys feel somewhat alien compared to other Chinese companies which may be more structured?

So I would say among the internet or technology, IT technology related companies, even though I haven't talked to a whole lot of them yet, based on what I have seen so far, are largely in the mode that I just described.

But when you go out of that range, you go to much more traditional companies, let's say steel industries or traditional retails, then you will see more of the Confucian hierarchical styles in management.

That again, I haven't done studies, it's just my perception.

So today it feels like, in particular when it comes to AI research, most of the great research is still being done here in the United States.

Do you think that will change over time, will we start to see 20, 30% of the papers suddenly be published from China?

Or will America kind of always be the hub of AI innovation?

Yeah, so this is 1 topic I had a somewhat ongoing discussion with many of my colleagues in China.

Our current view is the very top end of research that's fundamentally paving new ground.

I would say the example in AI would be, let's say, deep-minded, open AI.

I think that won't happen in the next few years.

Unlikely, I wouldn't say won't, say unlikely to happen.

The odds of that type of research happening in China perhaps will take quite a few years.

Right now, we see the research community, particularly the upper echelon, the gap is closing.

The leading Chinese universities, the way the gap is being closed is a lot of those researchers, they are pedigree, they study in top tier universities in the United States, whether it's Stanford, Princeton, and they go back.

So the gap is closing, but the overall environment, the culture context, isn't quite there yet, meaning that it's completely driven by your imagination.

The social economic surrounding is still not quite the same as United States, whereby you have truly world-class people driven by pure, the desire to seek knowledge, the desire to unleash imagination.

Often these researchers, then in the context of personal fames, economic payback, Once you have those, you constrain yourself.

You don't see very far, you don't go pursue the bigger dreams.

But Our collective belief among, at least myself, my bunch of colleagues, friends, we all believe given enough time, let's say in the next 5 to 10 years, you will see top echelon research work happen in Chinese institutions.

And it is certainly my hope that in the next, in somewhere between 5 years to 10 years windows, we will have equivalent of research organizations, let's say, OpenAI, DeepMind type, that would be truly do groundbreaking research towards AGI or different type of initiatives that would be at the very forefrontiers of extending the scope of humanist.

It's take time, we believe it takes time, not in the short future yet, but it will happen.

Are you going to try to create a Baidu research lab that is somehow has a different culture around it than what traditional Chinese academia has?

Baidu is doing quite a bit, and our peers, whether it's Alibaba or Tencent, they are also investing quite heavily in corporate research labs.

At the same time, the national labs, the top tier universities, they are doing more and more.

And there's also, in the private sectors, there's always ongoing discussion.

A new type of research entities can be envisioned and can be created.

So there's an ongoing set of ideas being explored.

I think it likely will be a combination of corporate research lab, university, and somewhat new generation, let's say open air type research organizations will be established over time that will be capable of carrying top tier research work that's based in China.

Shifting gears to a completely different topic.

Another thing that is a hotly debated topic out here in Silicon Valley is cryptocurrency.

No 1 really knows how to understand China's approach to cryptocurrency.

So I will speak from Baidu's perspective, not necessarily my personal view, because I haven't spent enough time on this particular subject to develop views that I thought would be educated views.

I would say it's more from Baidu's company perspective.

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