Baidu's CFO on How It Became a Full-Stack AI Player

24:57I think the policy supporting to getting the moment we have today is already proven. We have a proven path to leading not only the technology renovation and innovation, but also the way monitor that into the stage we already have today. So that's my first point. My second point is I think today the technology is growing very fast and the checks on the performance and on the data transparency and the rules regarding the data regulation, even without the AI model, even on the cloud age in the past kind of 20 years or five years, has been getting more robust. Because if you think about that, in a cloud environment, you have almost similar issues, right?

25:39Who own the data? Who use the data? Who can access that? But today, it's a new tool to actually cover all the things we are doing So I think it is not a new concept for the policymakers to think about. It is a new model. It is a new thing. It is really a new and better tools to utilize and access resources we're already building. And existing resources will have been building on existing platforms, which has been 100 % compliant. But also, we have a lot of support from the policymakers, industry practitioners, academics. They're actually all contributing to that. So overall, my feeling is it's a very transparent and open environment, not only China, but also globally.

26:18And academia and industry practitioners actually contributing quite a lot of the good conversations to this environment. And my feeling is the policymakers through different channels has been very open also listening to the new frontier issues and questions.

26:32Tracy Alloway:I know this is a business conference and we want to keep things very professional here and not engage in gossip, et cetera. But I have like one sort of, I'm just curious about something, which is if the American AI CEOs, the most hawkish on the sort of like chip exports on China stuff is Dario, who used to be a Baidu employee. Do you ever hear things in the office? Do people ever say like, oh, I remember that guy. He was, you know, is there any little Dario gossip that people talk about in the office from his stint at Baidu? So that's why I want to put the ball back to your porch. I want to share another gossip, which you probably want to hear.

27:15So probably in the past kind of 100 days, right, has Open Cloud become very popular, right? And educate the market about how AI is really getting to the real task and the real world. Obviously, in China, you know, there are different ways. You have a new way of calling, you know, not only the cloud, but other Niki names, right? So one day I saw Peter, who is the founder of the community, which drives Open Cloud to be prevailed, put, I think, Instagram saying, you know, he actually want to work with Baidu because, you know, open cloud is a tool, but the tool is it's kind of eating up all the capacity, i.e.

27:52the skills, right? So everyone is contributing to the skills, and the cloud is actually grab all the skills and do the work, right? So I think one day we are pretty happy, you know, when Peter dropped us a note in a very positive way because he kind of On one side, I noticed that the search is an important capability of the skills, i.e. the skills in the OpenClaw environment. So actually, he asked Baidu to work with him to beef up the search skills in order for OpenClaw to do a better work to accessing the real-time information. Because today, the foundation model, one kind of carve out is every few months, you train a new model.

28:31And the model itself, in his mindset, doesn't have the real-time information. For example, the foundation model yesterday doesn't capture, you know, Joe and Tracy were talking about today. You need to have a new skill to accessing the Ocelots, what is happening in real time.

28:45Tracy Alloway:That's right. So I think, you know, Google globally and Baidu for China, they are the powerhouse for searching the real time information. So it has to be linking to the open cloud. So I think that's actually one of the things we're pretty much happy to do about. So, you know, next day we ask our engineers to link up with Peter and we're actually part of this skill marketplace doing pretty OK. And right now, I just want to share our foundation model called Earning 5.1. Right now, it's ranked as globally number one in a text format of the global LIM arena and globally number five in the search skill capabilities globally in the LIM arena as well.

29:18So I think that's, I want to give you another gossip. But for the previous one, I probably can talk with you after this open session.

29:25Tracy Alloway:Yeah, I know you didn't give us any Dario gossip, But implicitly, because I know that the OpenClaw guy, you know, was originally called OpenClawed, and then Anthropik sued him. And also, he's got kind of annoyed because they didn't let the API users get full access. So I think that fellow who created OpenClaw is not the biggest fan of Dario's approach. So by giving us that answer, you at least gave us a little drama there. Thank you. You mentioned search a number of times already, and data is obviously very important to AI. We spoke with Grace Hsiao earlier in the week. She writes about AI on her sub stack.

30:05And I asked her if China has an edge when it comes to data collection. And she said she thought not really, because a lot of the data that's been collected was unstructured. And so it was hard to harness for AI model training and inference purposes. Can you talk a little bit more about how you did that at Baidu? Because you've got a lot of data, you're using it for Ernie. How is that transition process actually carried out? Yeah, sure. I probably will talk about something the market has not noticed enough. And I will talk about what's a real challenge, right? So it's always two sides of the story.

30:41I think I'm very happy to talk about Google versus what we think about Baidu in some certain formats. A few things. I think the markets, not only the capital markets, but also the industry, has kind of undervalue a little bit regarding the same components we actually matching with the same structure Google is monetizing and have this integrated capacity. So first of all, Google has its own TPU, which power the cloud. So the GCP growth, the Google Cloud is growing faster, which is part of the reason it's a TPU. And for Baidu, we have our own chip department. And based on the public information, we recently did the public filing, wanted to spin off these assets, right?

31:23So the chip, we have the same with Google. For the foundation model, we have our earnings, as I just mentioned. However, in the physical AI called applications or called work model, so we have our robot taxi called Apollo Go. Just want to share one number. I think in the market, sometimes I tell even my friends, it's kind of surprised that each week, including San Francisco and including all the cities, Austin, Texas, and U.S., Waymo from Google delivered about 500 ,000 trips per week. And in the last quarter, Baidu's Apollo goal, in a globally 27 cities, delivered about 350 ,000 trips, which is only about 25 % fewer than Google.

32:02The part of that is not only about robotaxi, it's about how we're using the data, empower our own foundations, models, trainings, and also do inference, but also have a lot of know-how regarding the multimodal contents and all the different things. And more importantly, if you look at the traditional search, right now on this quarter, also in the market, didn't notice that, you know, still even my friends telling me, oh, Henry, congratulations for your earnings, but your search is probably still 80 % or 90 % of the revenue, but the truth is for this quarter is declined to about 48%. So it's already below 50%.

32:34So the new growing area, for example, the digital humans and also our AI application software is becoming a powerhouse and growing very fast. So my point on that is if you look at key components or the blocks from the chip cloud, robot taxable AI, physical AI applications and the software. And also one more thing I want to mention is Google linking with YouTube for the multi-model contents. And we actually have our controlled subsidy called iQIQ in China, which is actually over 50 % of market share in China for certain long-form contents in China as well. So we also have our a closed loop of the data flag well as well.

33:11Probably at a different scale, but I think it's still in the same format and the same model. So my view is, yes, I think on one side, it is right that certain data and elements are in their own kind of pockets. But however, for Baidu, we still have access to those pockets. Probably better than other peers. But I want to also very honest admit, right, given Joe is my girlfriend, I still owe him a little kind of gossip after this session. I just want to share my own challenge. Obviously, in China, you have different camps, right? Different camps, they kind of don't open up enough to share the data, which is reality known to the market for everyone.

33:49But my point is, right now, this, you know, the agents and the foundation model become super smart. And it has a great push to move everything to a public cloud. It's actually helped resolving that issue to be accessing more information. Last note I want to share is, before AI came, the public cloud penetration in China is about 20-30 % versus the US is kind of 90%. So that's why your comments I can totally understand because without AI, the gap is like this. But right now, it's actually getting closer, but still there's a gap. But my confidence coming from this gap will further narrow because everything will be on cloud environments, everyone access real-time information, but also for Baidu, we have a full stack, and each component given the Google Pass has been proven to be right and more efficient.

34:38We just want to follow the same pattern and access and the benefits from the different layer of the data itself.

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37:44Tracy Alloway:So I am very glad that you brought up the RoboTaxis because first of all, I just love robo-taxis, period. They're very fun to ride in. You took me on my first Waymo ride. I remember. And I was a big, I was like, Tracy, you got to ride in a Waymo. You got to ride in a Waymo. And I think you were convinced. They're pretty cool. Now we have to ride in an Apollo Go, right? But here's another, besides, I'm also excited about them as a business story for a very specific reason, which is that when I think of like Baidu, people call it the Google of China, et cetera, but you know, separate markets, right?

38:14Tracy Alloway:Google isn't in China. People in the U.S. don't, by and large, use Baidu, as far as I know. But there's going to be cities now where there's going to be direct competition between Waymo and Apollo, including London, I think, is going to be the first city where there's going to be head-to-head bow. And so this is exciting because I feel like, OK, the tech internet, the consumer facing internet giants of the U.S. and the consumer facing internet giants of China are for the first time going to really be competing in certain identical consumer markets. And so what I'm curious about is like not who you think is going to win.

38:51Tracy Alloway:I presume you think you're going to win. But like, what is the dimension upon which the winner will emerge? Will it be the quality of the application? will it be who can produce and secure automobiles in volume what is the most important dimension that will determine the winner either globally or in a specific city so before getting there just you know also the car is one of my hobby too just you know joe probably know i'm actually a race car driver so i got my race my license as well so every time i actually uh drive a little bit so uh it's quite nice enjoyable because i think that probably the remaining car you can to use gasoline and drive yourself.

39:32Probably 20 years from now. So before getting there, I think the key word is change the car ownership.

39:39Tracy Alloway:Okay. My view is, in my own calculation, in US, as an example, right now, each mile, including insurance, gas price, parkings, on average is about 60 to 80 cents per mile is the tipping points between rent a car versus own a car. Okay. So if it's cheaper than that, people will buy a car. but more expensive people will rent a car right so right now for global player i don't want to name name but the average robot taxi cost today because the scale is still very small it's about you know one two or two point five dollar per mile okay there's a wrench about one to two dollars so my point is this curve just like agents getting more prevailing is coming down very fast so assuming at one some point you know five years six years whatever ten years if globally the Robotex can deliver average price per mile coming down to let's say 60 to 80 cents US per mile, then many people were thinking buying a car because today it's very simple.

40:37You know, Joe and Tracy, you're probably in Hong Kong, you know, the parking is so expensive, even more expensive than the gas. And the gas in Hong Kong also very expensive. So first of all, the car right now is all EV drive car. Number two, you don't have to buy parking because you and me can drive and the car can go out. And number three, why are we having this 40 minutes? My car actually can go out pick up passengers and they can make some money for me. So it's a new agent. That's why I'm saying it's a physical AI agent on the road to making money for myself. So my view is RoboTaxi will change the human behavior getting out in terms of behavior pattern of transportation.

41:10That's one thing, right? So we and Waymo and all other players globally are going to that direction. So that's my vision for the market going forward. However, as you mentioned about the market as a player in the near term competition. My view is right now that the market is due very early and the time is very high. So in the last quarter we shipped our car in London and as you know you know both Waymo and us are starting to open the market in London. Hopefully next year you will see a car and you know we have a good partner with both Uber and Lyft and also with Grab in Southeast countries. So next time you probably call a car from Uber or Lyft apps you will get a Baidu's car.

41:51So I think it's actually helping increasing the services because one interesting note is the human driver probably don't work in the midnight, right, in certain cities. But right now the car actually can work 24 hours. So it's expanding a new market. And right now it's still a very low percentage of penetration. So it's still going to have a lot of room to go. On the other hand, to your question about the success factor, I think the two things. One is the technology needs to be cutting edge and improving. And number two is operation efficiency, right? So it's actually have a lot of work need to be operational driven.

42:23For example, how many locations you pick up passengers to be more efficient, right? The charging stations and all the different network designs is actually very important. But given we are working on this business for kind of 13 years so far, and I can tell you one interesting fact that globally, there are only two cities right now have over, you know, thousand cars in that scale, which is San Francisco and a win city in China, which is Google operating in San Francisco and Apollo from Baidu operating one city in China. But I think our kind of partnership with both Lyft and Uber globally with different cities, I think has been very collegial because the demand is much higher than the supply.

43:05Yeah. Joe, I'm going to admit something slightly embarrassing. Actually, you already know this, but I never learned to drive partly because I grew up in Tokyo and then I moved to a bunch of other big cities. And so I never needed to. And now I always joke that I'm basically, I'm never going to learn. I'm just going to hold out for the self-driving cars. So, you know, fingers crossed.

43:26Tracy Alloway:It's coming. I hope so. I wanted to ask something about, you know, you've mentioned agents a number of times, and this seems to be becoming the hot new thing in AI. And I know your CEO has talked about how one of the key metrics for Baidu is daily active agents. And my question is, how does that actually turn into revenue or return from a CFO's perspective? Because I understand with search, you know, you type something in, you see the ads, advertisers are paying you for that, but I'm very unclear how it works if the agent is actually going out and doing something. Yeah. So in the mobile internet where, you know, everyone look at, for example, the DAO, the daily active users, because that either fulfill information query demand and individual are the primary users for many of the mobile applications in app stores.

44:17So the DAU was the primary matrix to measure that. However, in the recent conference, our chairman and founder of Baidu, Robin, mentioned, I think based on his leadership, that DAA, which is the daily active agents, are the new kind of matrix to defining the success of agents. So I kind of very much agree on that. The reason is, if you look at tasks, it's actually spread out into different verticals, right? So right now, it's very difficult to find a new way to identify how much people using, especially how much value coming out from using AI. So the agents today is basically can deliver a final task, not only using as a tool for human beings.

45:02The agent is smart enough to think about planning the task and completing the task. And obviously, in the way of interacting with human beings, it actually becomes more smarter and in a way that working with more efficient planning of that. So, Tristan, to your question, overall, my thinking is the DAA will measure not only how many people using that, but also how difficult it is. To your question, the result-driven payment is coming up in a near trend. So I just want to share a few things. For example, right now we have three or four different key products. One of them in China called FAMO. It's really solving complicated issues for enterprises.

45:43It's very similar to AlphaGo, which actually in the previous years has to do the planning. But right now it's actually coming to the real world. So we install this agent to one of the biggest port in China and help them deploy and planning for the shipments and the logistics. It is saving the cost of the idle time and improving the revenue of their parts. So the parts actually waiting to share a certain profit generation with us. So the key things I'm observing is in the previous meetings, even I'm in the CFO, but actually I'm attending a lot of the meetings to meet with clients. In the previous meeting without AI, most of the meetings we are talking with is the CTO and the CIO of that company, because it was a tool.

46:26It was a cost center. so they need to find a budget internally. Joe, you know, it's not easy, right? So they have their CFO and their CEO. But right now, most of the meeting we are having today is with the CEO himself because AI right now is not only about Baidu, it's really about helping our clients. So the client has to be a top-down level of the initiatives to really drive AI internally. So I think our sales process becomes relatively more efficient in the way that we're getting to the number one decision makers. He has a budget and he knows that driving the pot efficiency is important for his task.

46:59So he's willing to share certain economics with us. I think the customization is also diminished because right now the agents can be used different paths. You can repeating that success, lower the unit basis of the cost and the agents become more real and the clients see the value and the profits. So they have a higher willingness to pay and high ability to achieve that payment. So I think these four cycles actually in the AI world is very different with the traditional IT.

47:25Tracy Alloway:This is actually an interesting question because I've seen debate on this within AI about what does revenue look like or what is, you know, a sales price look like. Because another thing people talk about is, for example, using an AI agent to say, resolve an insurance claim or something like that. And then the AI provider gets paid on, say, like, you know, the number of successful claims resolved, etc. Are you bullish on that basic model where the payment is, as you said, okay, maybe they'll share revenue with you because they can measure that savings. Is that the model that you see across a range of AI applications where it's like a sort of per task or sort of very clearly linked to the efficiency gain?

48:13Yeah, we have another kind of line of business. We call the digital employees, which, you know, Joe, probably you have the similar experience that if you have one season of the podcast, you're probably very energetic. Right. If you do that like 10, 20 times in two weeks, it's very exhausting. Right. Because you need to think about.

48:31Tracy Alloway:Wait, you're saying we're going to be replaced? You share my views, right? Wait, wait, is that what you're insinuating? We're going to get replaced because we get exhausted, but the AI agent won't get exhausted? So my point is, the humans, their motivation and the knowledge base have their own kind of territory, to be frank. But if you look at the conversation, look at the quality of the know-how, if you really tap in a good manner, of course, the digital human actually can deliver efficiency and a better execution quality. So one example I just want to share is e-commerce is a big industry in China.

49:07and a lot of live performance is really selling the products. It looks fun. But you know, the come out is the KOL cannot work like 24 hours, right? And people cannot buy stuff like 24 hours. But if you think about it, you have a great quality of the human employee can help the merchant owners to sell into different time zones and also can speak Chinese, speak English and for the different parts of audience to have the little jokes from their own countries. it actually can help the e-commerce revenue. So that's why we have their own kind of product called Digital Employees. We actually help our merchant and the e-commerce store owners to really push on that and selling all the goods.

49:50And it actually can perform pretty well because on the Q &A sessions, on the questions, it's actually reacting to the random users asking a wide range of questions. That knowledge actually is very fluent in a way that for the foundation model, It is the way it works, right? So I think that actually have different user case. And we actually monetize by charging, for example, the result improvement and all the different things. I've tried to buy things for 24 hours straight before. I think when I first used Taobao, I think I had Taobao psychosis or something. And that's how my husband and I ended up with three couches in our apartment that was about 500 square feet large.

50:26So my little suggestion, you need to have another agent help you to select the right products. So that's another way you probably can monetize on that. Are you going to spin out the chips business? We're at Bloomberg Invest. It's our first live recording of Odd Lots. Let's break some news. All right. So it's coming to the money part. So I was not, to be frank, I was not even trained by finance. I become a salesman by accident. So actually my both bachelor and master training was a chip designer myself. So I think after joining Baidu, I definitely realize that Baidu's chip product has been really, really high quality and really good for the inference for all the things we talk about, helping our DAA to grow as well.

51:09So based on the public information, we already filed the confidential filing for spinoff of our chip assets in Hong Kong. And we are doing that and processing that process on track. And that is one part of the assets we try to unlock at this moment. But however, as I mentioned, the cloud foundation model, they are all very important. So after spinoff, we hopefully can enhance that ecosystem. And as you know, chip is not only the hardware. I deeply understand it is about ecosystems. We need to work pretty well with our customers and the suppliers and the software developers all at one goal. And I think to be a separatistic public company, it will help to achieve that goal not only as hardware but also the entire ecosystem as well and our customer will view our chip products more neutral and independent products that can actually do more testing and

52:02Tracy Alloway:more usage on their own cases yeah i seem to recall reading that you've figured out a way that uh developers can easily port over their uh cuda stack over to your stack without much trouble uh henry thank you so much for uh coming on oblox our first live recording anywhere in asia Really appreciate it. Again, thanks for having me. Thank you, Joe. Thank you, Tracy. Thank you.

52:38That was our conversation with Henry He, the CFO of Baidu, recorded live at Bloomberg Asia Invest. I'm Tracy Allaway. You can follow me at Tracy Allaway.

52:48Tracy Alloway:And I'm Joe Weisenthal. You can follow me at The Stalwart. Follow our producers, Carmen Rodriguez at Carmen Armand, Dashiell Bennett at Dashbot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And for more OddLots content, go to Bloomberg.com slash OddLots where we have a daily newsletter and all of our episodes. And you can chat about all of these topics 24-7 in our Discord, discord.gg slash OddLots. And if you enjoy OddLots, if you like it when we talk to Chinese tech executives, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free.

53:24All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.

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