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

In the China tech space, Baidu is now a full-stack player in the AI industry. The company makes its own chips, has its own AI models (Ernie), its own cloud system, and it's integrating AI into its self-driving car business, Apollo Go. But before all this, Baidu was known for being China's leader in search. Things, obviously, have changed a lot since the company was founded in the late 1990s. In today's episode, we speak with Baidu CFO Henry He about the company's AI ambitions. He talks to us about maximizing token spend, how Chinese tech firms are thinking about safety and alignment, the global robotaxi competition, and how the core search business fits into the company now. Read more: Chinese AI Stocks Rally on Demand Optimism and Policy Support https://www.bloomberg.com/news/articles/2026-06-22/chinese-ai-stocks-rally-on-demand-optimism-and-policy-support?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article US Seeks AI Partnership With EU on Regulation, Supply Chains https://www.bloomberg.com/news/articles/2026-06-25/us-seeks-ai-partnership-with-eu-on-regulation-supply-chains?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article Only http://Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox each week, plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots https://www.bloomberg.com/subscriptions/oddlots?in_source=oddlotspodcast Subscribe to the Odd Lots Newsletter http://bloomberg.com/subscriptions/oddlots Join the conversation: discord.gg/oddlots https://discord.gg/oddlots See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Tracy Alloway?

  There are some market stories where you want every detail. Joe and I have made quite a few podcasts on that basis. But sometimes you've only got 10 minutes and just want to know what's moving markets fast. That's the Barclays Brief Podcast. Every week, experts from Barclays Markets and Research get you up to speed on what's happening and what to watch next. Concise, focused, and brief. Search Barclays Brief wherever you get your podcasts.

• 0:26Speaker 01

  This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Business Week's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw, innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting

• 1:08Speaker 01

  and hiring practices, but according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company, and Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, "must be willing to work extended hours and weekends as needed." One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at chatgpt.com.

• 1:52Speaker 01

  Bloomberg Audio Studios. Podcasts, radio, news.

• 2:07Joe Weisenthal?

  Hello and welcome to another episode of the Odd Lots Podcast. I'm Joe Weisenthal.

• 2:11Tracy Alloway?

  And I'm Tracy Alloway.

• 2:12Joe Weisenthal?

  So we were in Hong Kong recently. That was a lot of fun.

• 2:15Tracy Alloway?

  Nice to be back. Yeah, I haven't been back for four years.

• 2:18Joe Weisenthal?

  Yeah.

• 2:18Tracy Alloway?

  Not much has changed, actually. I was kind of surprised.

• 2:21Joe Weisenthal?

  Less than you expected.

• 2:22Tracy Alloway?

  Less than I expected, but I am really glad we went back because obviously one of the big talking points in markets right now is competition between US versus Chinese AI.

• 2:32Joe Weisenthal?

  Yeah.

• 2:32Tracy Alloway?

  And we finally got a chance to talk to a couple of high-level executives of Chinese tech companies who are actually making all the big capital allocation decisions when it comes to the AI race.

• 2:44Joe Weisenthal?

  Right. It felt like we're in this moment where there's been the, I mean, the way I think about it, there's been Chinese internet giants, but they concentrated on China, right? There's been American internet giants that basically had the rest of the world. And whether we're talking about AI or self-driving cars, we're going to see the first sort of like real head-to-head battle in internet companies specifically. And whether like competing for, playing the same game on some of the same markets. And of course, we know American companies can use AI models built by China, et cetera. And so there are all kinds of options for people. So it's like really interesting to see like, okay, this clash is actually like, it's happening.

• 3:20Tracy Alloway?

  It's a good time to talk to a Chinese tech executive, for sure.

• 3:23Joe Weisenthal?

  That's right. So the reason we were back in Hong Kong is because we were at the Bloomberg Invest Conference, though we also threw an Odd Lots trivia night while we were in Hong Kong.

• 3:31Tracy Alloway?

  Our first non-US overseas Odd Lots Quiz Night.

• 3:35Joe Weisenthal?

  Yeah, that was a lot of fun and I'm sure we'll come back and do that again. But we were at the Bloomberg Invest Conference and so we had the chance to speak with the CFO of Baidu, Henry He. So check it out. We truly have the perfect guest. We're going to be speaking with Baidu CFO Henry He. So Henry, thank you so much for coming on Odd Lots.

• 3:53Speaker 03

  Thanks for having me and it's a great season. I think Hong Kong, it definitely is great to see both Joe and Tracy.

• 3:59Joe Weisenthal?

  Thank you. Very nice of you to say. So why don't we start with this? You know, obviously I feel like half the conversations are probably about AI these days. But within AI, Baidu is a full-stack player, right? You have cloud, you have The application layer, you have your own chips and of course your own model. As the CFO, you might have to think about prioritization, et cetera. Is there one layer of the stack that you feel is a must win for Baidu? When you think about resource allocation, is there a layer where it's like, okay, this is an area where we have to win?

• 4:34Speaker 03

  Thank you so much, and I think you'll probably put the tough question in end, but I think it's probably the most difficult question to start with. So I think the very unique thing today is I think the entire AI has been shifting from infrastructure to applications. And from model to agents, I think that's actually the backdrop. I think within that, frankly speaking, right now, it's very difficult to say at this moment, which part is the must have. Because in my view, the chip is infrastructures. You need to have a great model to bridge the capability. The cloud is a deployment of that capability. And obviously, the monetization and all the ROI questions, especially for the people like me as CFO, we focus on that, is on the application layers.

• 5:17Speaker 03

  So without any of that, this ROI cannot work. So to answer a question, I think the key thing, if I have to pick one, is cloud. Because cloud at this moment is a platform. You can not only hosting Ernie, which is our own model, but also I can work in a very open to hosting other models. And my chip, which connecting to my cloud platform can also help on inference. Because right now, the pre-training is important, but eighty percent of the incremental demand today on a token are inference related. I think this part of the full picture is what I want to emphasize, but you know, given the tough question, if I want to pick one as a student, A, B, C, D, I want to pick number C, which is my cloud.

• 5:56Tracy Alloway?

  I'm going to ask a question which I think is going to become standard for a financial journalist in the same way we ask about headcount and expansion plans. What's your token budget? Is it bigger than Joe's?

• 6:09Speaker 03

  You mean the token?

• 6:10Tracy Alloway?

  The token budget for Baidu?

• 6:12Speaker 03

  Yes.

• 6:12Tracy Alloway?

  Or how do you measure? I'll ask it in a slightly different way. How do you measure what you're gaining from your token spend? How do you measure productivity?

• 6:20Speaker 03

  Yeah, sure. I want to categorize probably in two buckets. One is we consume computing power to reach a higher level of technology standard. You know, the AGI, the how good model perform, and also how hard it can be designed to deliver better results. So these are R and D efforts. However, as also a tech house, we also deliver those know-how to our external clients with different verticals. I think if I'm measuring our internal consumption of the token, I really want to look at how better and how efficient our technology can be developed. So that's on one side. However, on the other end, what I think the ROI is more relevant is how many real tasks

• 7:05Speaker 03

  that the OpenClaw and, for example, our own application called DoMate, also is a real agents, you human digit and other things can do the task. So I think these two different measurements are important in a way that right now there are two things are better than last year. When is a foundation model getting much better? And number two is the framework, i.e. OpenClaw and other things, can link up the foundation model capability to the real world task. From chatting on something to doing something and completing on something. I think completion part of the tokens is more important today. And I think consumption internally will actually encourage the people do that. But think about that, even last year or a year before, everyone is actually beefing up the R and D budgets.

• 7:49Speaker 03

  I think that budget is always there, but the completion new task is more important.

• 7:53Joe Weisenthal?

  But let me just press you on this question a little bit further. So let's say Tracy and I are, let's say we worked for Baidu in the same department, I don't know, some department of yours. Would we have identical token budgets? Or would you have one way of saying, you know what, Joe? Tracy is actually finding ways to get more value out of AI than you are. So I'm going to increase her budget. Like, do you make decisions? Like that and do you have measurement techniques to see like this person really should get ten times the token budget of another person because they have figured out how to get a lot of juice from the squeeze, so to speak.

• 8:30Speaker 03

  You know, Joe, given the question asking, I think probably next time I give you more tokens.

• 8:36Speaker 03

  I think right now the technology evolved very fast. I think that's the beauty part of AI. So we don't want to constrain by ourselves by before thinking through something, we just install certain policy by saying, you know, these are employees with defined the token number by the titles or the seniorities. I don't think that's the way it works.

• 8:54Joe Weisenthal?

  Okay.

• 8:55Speaker 03

  So I think we want to more open and more nimble in a way that given enough token to the individuals to empower their internal R and D efforts. But on the other end, we do have a lot of efforts to make sure the token costs become dramatically coming down. I think the cost is coming down very fast. Before you even think about getting a policy, maybe the unit cost is coming down half in like a few weeks. So we need to think about the speed and the cost and output efficiency, these three parameters as a package, not only on the number of tokens. That's one thing. On the other end, you feel very interesting facts. So right now, you know, we are recruiting a lot of younger talents today, even for Baidu, which is, you know, twenty plus years listed at public company.

• 9:38Joe Weisenthal?

  Yeah.

• 9:38Speaker 03

  So my feeling is the kids actually getting smarter than people expected. So they were not wasted the tokens you give to them. So they have a sensible judgment about what are the tasks they need to prioritize because they're working on agents and the models, the model actually helping them also prioritize all the tasks they have. So I think the power of the technology today is it is not only the tools. So that's actually the key concept on the mention. It is not only a tool, it's a mindset. And the mindset become automatic and more intelligent that if people can work on that well and have a new relationship with agents and with a model, some of the old questions we kind of struggle ourselves will be kind of diminished or less important.

• 10:19Tracy Alloway?

  Okay, so no token maxing at Baidu. But since you brought up talent, one thing I'm very curious about is we know the competition for the top engineers is so Intense right now. And in the US, we see these headlines where engineers are treated like sports stars. You know, they're being traded for millions of dollars or whatever. What is Baidu's pitch to top talent? Like, if you're trying to attract someone to the company, what is it you say to them that makes them want to work for Baidu versus another top tech firm?

• 10:50Speaker 03

  Yes, great question. So let's bring a different perspective. I think, you know, we are a technology company. Previously, I think the priority is we empower our clients to be more intelligent. We give them more technology tools to help them to remove a move from the, you know, the traditional IT to the cloud environment, you know, such as that. But right now, I think AI, especially for the big corporation like us, also changes us as well. We need to think about the cultural change, organization change, not only as an organization and a company, but also how AI empower ourselves. So it's actually equally important to do something for client versus think about the new tools affecting ourselves.

• 11:32Speaker 03

  So Trace is right. I think there are a few things we're actually making a lot of different thinkings and some of the new initiatives. First of all, we're probably among a few companies in China, still very open and even increasing the campus recruiting and the focus on the younger talents. And number two, recently, we also tasked the senior people not only look at, you know, the current reporting structure, but also in the real mentor relationship with the younger growing piece of the human capital in a company. But more importantly, I think it's really about giving people more autonomy to work in a company. So more trust and more autonomy and give them more real work. And you know, there's a one concept called a one-person company, right?

• 12:15Speaker 03

  So we are very happy to working with one-person company because they actually use our AI tool very nicely and they're willing to pay a lot of revenue to our products, given the quality. However, within the company, we also encourage people to be the one-person team. So they can actually use agents to work a lot of internal tasks. So internally, we have this little tool called Dudu, right? In Chinese, a very kind of nickname, which is actually. Our internal kind of open cloud similar tools and which actually enhancing people's efficiency. And to a point, I think give me more people, more autonomy, more trust. And the more room to grow and attracting new talents, I think equally all all kind of very important to change ourselves. But also, you know, reporting lines and organizational structure need to come with it to make sure that people can deliver the the results.

• 13:00Speaker 03

  And the the last note I want to mention, the key things that people see the application is important. They can work on the full stack in Baidu, which is very unique value in the China tech space.

• 13:09Joe Weisenthal?

  You know, it just occurred to me, American companies are kind of becoming more Chinese in the sense that they're doing more vertical integration, like that's sort of a long history here of sort of the whole thing. And now we see one of this phenomenon is that every American company like they want to even start designing and selling their own chips, their own silicon, which is something that you're doing, you have your own business and you've had it for a while. And I'm trying to wrap my head like, what is the rationale? How much is it about just wanting to be able to control your own fate more? And so wanting to like control more of the supply chain versus having a chip

• 13:49Joe Weisenthal?

  that optimally aligns with the model that you're working on, because those are distinct priorities. So what is the real rationale for having custom silicon?

• 13:59Speaker 03

  Yeah, I think thanks for the tech trend in the past kind of year and two. So if you look at entire computing power consumed. For example, last year, most of the consumptions actually relating to the pre-training of large

• 14:14Joe Weisenthal?

  Yeah.

• 14:14Speaker 03

  Foundation model, but right now, Joe, you know, many of them going to the inference and complete tasks. And if you look at the different stacks, I think right now we are actually fitting to a incremental growing piece of the market, which is well defined with a clear boundary, which is not focused on pre-training for a very super scale foundation model. However, the inference application is important. So to a point, I think our chip product supporting our cloud focusing on the inference and application is a unique way of we see the positive network effects. I think that's where the area. Where we want to invest. And also, given the issue you mentioned, I think within that defined areas, we'll feel pretty confident regarding all the issues you mentioned. And because on the supply and demand side,

• 14:59Speaker 03

  we can find the good match within the emerging market category within inference and application markets.

• 15:20Tracy Alloway?

  There are some market stories where you want every detail. Joe and I have made quite a few podcasts on that basis. But sometimes you've only got 10 minutes and just want to know what's moving markets fast. That's the Barclays Brief podcast. Every week, experts from Barclays Markets and Research get you up to speed on what's happening and what to watch next. Concise, focused, and brief. Search Barclays Brief wherever you get your podcasts.

• 15:46Speaker 01

  This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Business Week's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices.

• 16:30Speaker 01

  But according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company and Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, "must be willing to work extended hours and weekends as needed." One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at chatgpt.com.

• 17:10Tracy Alloway?

  So hypothetically, you could try to do everything, right? The full stack. And I guess the capital investment you would need to do that is also hypothetically unlimited at this moment in time. And we hear these crazy numbers in the US about the hyperscalers spending hundreds of billions of dollars this year alone. But when you're looking at the different parts of the business, so you have a very mature internet search business, and then you have everything that you're doing with AI, including infrastructure. How are you actually allocating capital? And then how are you actually, I guess, balancing that with returning capital at the same time to shareholders?

• 17:48Speaker 03

  Yeah. So I call it impossible triangle. So I kind of scratch my head every few months, every few quick weeks. Depends on also see headline numbers on Bloomberg News with other peers as well. So sometimes I make a little bit kind of hesitating to make a statement, but I just want to tell the facts and tell the views. I want to separate them out. Sure. So in the recent quarter earnings, we, you know, we mentioned, we actually solve partially on this impossible triangles. One is our operating profit increased almost doubled on the Q on Q base. And number two, our cloud revenue grew about 79% on a YOY basis, which is almost double of the YOY growth rate for the cloud market in China. And number three is since Q3 last year, our operating cash flow has turned positive.

• 18:33Speaker 03

  So positive operating cash flow, incremental operating profits, and the higher growth in the market. However, my CapEx is not seeing kind of double even third multiple times. So I think the way of resolving that is as a CFO or as a management team of a heavy CapEx investor AI tech company right now, need to find a way on one hand, really drive the growth, but also keep the density of the investment into AI in a reasonable pacing. However, when you do that, you need to keep a conscious regarding the ROI and I'll in mind to look at entire cash cycle. For example, every dollar we spend today, we probably need to wait for another probably 20, 30, 40 months, depends on the category, to get full cash back. And during that frame,

• 19:16Speaker 03

  Obviously, there's a, you know, price hikes, some memories, there's difficulty on IDC centers and the huge spending on servers. So my point is, as a CFO, on every project, you need to look at the entire lifecycle, not only at one time, but also the pacing important because the foundation model R and D always taking a few months, right? So these are the things you need to keep in mind. But my, my statement today is, as by do, we want to invest probably in a more responsible manner to the shareholders, but do not diminish our ambitions to investment into AI. Keep the right density is important, but given the results for this quarter, I think we kind of resolved that, at least for this quarter. So hopefully we can keep on working on that and maybe, you know, half a year later, we, when we check on this point, we can still keep on the same pattern, you know, high growth,

• 20:01Speaker 03

  less dollar spend, but better IOI. I think that's probably the angle we want to achieve.

• 20:05Joe Weisenthal?

  Can I ask you about something I'm very curious about? You know, I'd say the heads of the American AI labs maybe have varying degrees of AI psychosis. They have a lot of worries that the, what they would call alignment research, et cetera. Do you work on similar things or do you have the same concerns? Do you also have AI psychosis? Yeah, no, but like, do you like, you know, for, you're true. Speaking of like trying to make money, like, do you invest in or how much do you invest in what they would call AI safety or alignment and essentially making sure that the models that you're building don't go rogue and always work on behalf of human flourishing? Is that a thing that you allocate capital to?

• 20:50Speaker 03

  Yeah, it's a great question. So there's emerging area, for example, in this data sanity and all the kind of post-training efforts need to work on that, you know, alignment obviously is one of that. But my point is, if you look at this new concept of harness, right? It's not only about pre-training and getting model on the leaderboard, but also more importantly to measure the robustness and all the things you mentioned. I think in the context in China, tech. Sector, the engineering has to be and has been a good competitive advantage. So the harness from the data flywell to the alignment, to the data quality and the labeling. I think the entire ecosystem has been robust for if you think about even in the mobile internet world, right?

• 21:35Speaker 03

  So as simple as data labeling to the alignment checks and the post-training and SFT. I think this kind of the full chain of the capability in terms of the talents and the pool of resources and the cost of data sanity and all the checks has been, in my view, a little bit kind of more efficient in a way that the ecosystem has been in place there. So the cost efficiency has been there. So my view is this is engineering, not a theoretical quantum leap, right? So on that, the engineering capability from the China tech world and industry has been there with the key elements I mentioned, right? Talents, lower cost, more efficient. I think these are the few things I just want to point out actually can help solve the issue.

• 22:19Speaker 03

  But as I mentioned, the things are evolved very quickly, right? So, you know, we don't worry too much about the issue you you you mentioned in local market.

• 22:26Joe Weisenthal?

  Yeah, so this is interesting. I'm curious, I want to press further on this because the American AI lab seem very anxious about this. And they published these model reports and it says things that in the chain of thought, we were able to see that 4% of the time the model was able to identify that it was being tested and therefore it changed its behavior in response to recognizing that it was tested. And this is a sign of potential misalignment. Are you doing the same sort of research and spending to establish that, again, the models work for people and don't have a rogue goal, so to speak?

• 23:04Speaker 03

  Yeah, sure. I think right now, if you look at this, right? So we are also part of the open source community. So many of the good model, especially publishing recently, also will publish their thoughts about that. So we kind of follow the new thoughts, but also doing our own tests as well. So overall, I think people in the open source community today, in my view, is very collegial. So people still want to do a better model, frontier model for everyone globally, not really on one country, two two different places, yeah.

• 23:31Tracy Alloway?

  So actually, related to this, I'm going to ask something, maybe it's slightly sensitive, but I think it's very important. So in the US, the AI companies, even as they talk about safety, they're basically self-regulating, right? Like, they choose to put out these reports and judge their own models and things like that. In China, tell me if I'm wrong, but it feels very different. It feels like the government is more hands-on when it comes to AI. China has been very explicit about this as an area- Proactive. -national security, national strategy. So you're operating in an environment where you're firmly embedded in China's technological and industrial policy. How does that influence the development of your AI models and your broader tech?

• 24:14Speaker 03

  So obviously, we're not in a position to comment on public policy, but I definitely happy to share some of my thoughts I have. I think in the world, in the China AI today, we believe we have a great group of very superior talents, not only the engineers, but also people actually design, you know, the framework, right? So that's actually very important, because it's not only about algorithm itself, it's about the whole system regarding infrastructures, regarding the data regulation, regarding the model and the cloud. I think, given the past kind of 10, 20 years in China, given this entire infrastructure has been upgraded to a level that is kind of where we're leading. I think the policy supporting to getting the moment we have today is already proven, we have a proven

• 24:56Speaker 03

  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 10, 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? Who own the data, who use the data, who can access that? But today is a new tools to actually cover all the things we are doing.

• 25:40Speaker 03

  So I think it is not a new concept for the policymakers to think about. It's a new model, it is a new thing. It is really a new and a better tools to utilize and access the resources we're already building. And existing resources will have been building on existing platforms, which has been hundred percent compliant. But also we have a lot of support, you know, from the policymakers, industry practitioners, academics. They actually all contributing to that. So overall, my feeling is it's a very transparent and open environment, not only China, but also globally. And academics 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.

• 26:25Joe Weisenthal?

  I know this is a business conference and we want to keep things very professional here and not engage in gossip, etc. 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 a, you know, is there any Dario gossip that people talk about in the office from his stint at Baidu?

• 27:01Speaker 03

  So that's why I want to put the ball back to a court. I want to share another gossip, which probably you want to hear. So probably in the past kind of hundred days, right? It's 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 way, you have a new way calling, you know, not only the cloud, but other nicknames, right? So one day I saw Peter, who is the founder of the community, which drive the open cloud to be prevail. Put, I think Instagram or 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. the skills, right?

• 27:46Speaker 03

  So everyone is contributing to the skills and the cloud is actually grab all the skills and do the work. Alright, so I think one day we are pretty happy, you know, see, oh, Peter drop us a note very in a positive way because he kind of on one side noticed that the search is important capability of the skills, i.e. the skills in the open cloud environment. So actually he asking Baidu to work with him to beef up the the search skills in order for open cloud to do a better work to accessing the real time information. Because today, the foundation models, one kind of carve out is every few months you train a new model. And the model itself in his mindset doesn't have the real time information.

• 28:28Speaker 03

  For example, the foundation model yesterday doesn't capture, you know, Joe and Tracy were talking about today. You need to have a new skills accessing the onslaughts, what is happening in real time.

• 28:38Joe Weisenthal?

  That's right.

• 28:38Speaker 03

  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 cloud. So I think that's actually one of the thing we pretty much happy to about. So, you know, next day, we ask our engineers to link up with Peter and we actually part of this skill marketplace doing pretty okay. And right now, I just want to share our foundation model called earning five point one. Right now, it's ranked as the globally number one in a tax format of the global L M arena and globally number five in the search skill capabilities globally in the L M arena as well. So I think that's want to give you another gossip. So but for the period, so I probably can talk with you after this open.

• 29:18Joe Weisenthal?

  Yeah, I know you didn't give us any Dario gossip, but implicitly, because I know that the open claw guy, you know, it's originally called Open Claude and then Anthropic 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 Open Claw is not the biggest fan of Dario's approach. So I by by giving us that answer, you at least give us a little drama there. Thank you.

• 29:46Tracy Alloway?

  You've mentioned search a number of times already and data is obviously very important to AI. We spoke with Grace Xiao earlier in the week. She writes about AI on her Substack. And 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 like actually carried out?

• 30:25Speaker 03

  Yeah, sure. I probably will talk about something the market has not noticed enough. And I'll talk about what's the real challenge, right? So it's always two sides of the story. I 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 on the value a little bit regarding the same components. We actually matching with the same structure of Google is monetizing and have this integrated capacity. So first of all, Google has its own TPU, right? Which power that cloud. So the GCP growth, the Google cloud is growing faster, which is part of the reason is the TPU. And so Baidu, we have our own trip department.

• 31:11Speaker 03

  And you know, based on the public information, we recently did the public filing, want to spin off this assets, right? So the trip, we have the same with Google. For the foundation model, we have our earnings, this is mentioned. However, in the physical AI called applications or called word model. So we have our robot taxi called Apollo Go. Just want to share one number, I think in 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 in US, Waymo from Google deliver about 500,000 trips per week. And in the last quarter, Baidu's Apollo Go in a globally 27 cities deliver about 350,000 trips, which is only about 25% fewer than Google. Yeah.

• 31:56Speaker 03

  The part of that is not only about robot taxis, 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 the more important, if you look at the traditional search. Right now, on this quarter, also the market didn't notice that. You know, still even my friends telling me, oh, Henry, congratulations for that, for your earnings, but your search is probably still eighty and ninety percent of the revenue, but the choices for this quarter is declined to about forty eight percent, so it's already below fifty percent. So the new growing area, for example, the digital humans and also our AI application, the software is becoming a powerhouse and growing very fast.

• 32:36Speaker 03

  So my point on that is, if you look at key components or the blocks from the chip, cloud, robot taxi for AI, physical AI applications and the software. And also, one more thing I want to mention is Google linking with YouTube for the multimodal contents. And we actually have our controlled subsidy called I Q in China, which is actually over fifty percent of market share in China for certain long form contents in China as well. So we also have our closed loop of the data flywheel as well, probably 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, there are certain data and elements are in their own kind of pockets.

• 33:18Speaker 03

  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. But 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.

• 33:57Speaker 03

  Last note I want to share is, before AI came, the public cloud penetration in China is about twenty, thirty percent versus in US is kind of ninety percent. 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 narrowed, because everything will be on cloud environment. Everyone access real time information, but also for Baidu, we have a full stack and each components, given the Google pass has been proven to be right and more efficient. We just want to follow the same pattern and access and the benefits from the different layer of the data itself.

• 34:54Speaker 01

  This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Business Week's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs and hands on experience matters more to recruiters than advanced degrees with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices, but according

• 35:37Speaker 01

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• 36:17Joe Weisenthal?

  So I am very glad that you brought up the robo taxis because first of all, I just love robo taxis, period. They're very fun to ride in.

• 36:25Tracy Alloway?

  You took me on my first Waymo ride. I remember.

• 36:27Joe Weisenthal?

  And I was a big, I was like, Tracy, you gotta ride in Waymo. You gotta ride in a Waymo. And I think you were convinced they're pretty cool.

• 36:32Tracy Alloway?

  Now we have to ride in an Apollo Go, right?

• 36:34Joe Weisenthal?

  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, etc. But, you know, separate markets, right? Google isn't in China. People in the US 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 battle. And so this is exciting because I feel like, okay, the tech internet, the consumer facing internet giants of the US and the consumer facing internet giants of China are for the first time going to really be competing in certain identical consumer markets. And

• 37:19Joe Weisenthal?

  so what I'm curious about is like, not who you think is going to win, 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?

• 37:45Speaker 03

  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 license as well. So every time I actually drive a little bit. So it's quite nice, enjoyable. Because I think that probably the remaining car you can see use gasoline and drive yourself. Probably 20 years from now. So before getting there, I think the key word is change the car ownership.

• 38:11Joe Weisenthal?

  Okay.

• 38:12Speaker 03

  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.

• 38:29Joe Weisenthal?

  Okay.

• 38:29Speaker 03

  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 robo taxi cost today, because the scale is still very small, is about, you know, One, two, or two point five dollar per mile. Okay. It's as a wrench, about one to two dollar. 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 robotax could deliver, uh, average price per mile coming down to, let's say, sixty, eighty cents US per mile. Then many people were thinking buying a car because today is very simple. You know, Joe and Tracy, you're probably in Hong Kong, you know, the parking is so expensive, even more expensive than Yeah. the gas.

• 39:14Speaker 03

  And the gas in Hong Kong are also very expensive. So first of all, the car right now is all EV drive car. Number two, you don't have a park parking because you and me can drive and the car can go out. And number three, while we're having this forty minutes, my car actually can go out, pick up passengers, and it can make some money for me. Yeah. So it's a new agents. So that's why I'm saying it's a physical AI agents 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. So that's one, one thing, right? So we and Waymo and all other players globally are going to that direction. So that's my vision for, for the market going forward. However, as you mentioned about the market as a player in the near term. Competition. Competition.

• 39:57Speaker 03

  My view is right now the, the market is due very early and the TAM is very high. So in the last quarter, we ship our car in London. And as you know, you know, both Waymo and us are starting open the market in London. Hopefully next year you will see a, a car and, you know, we have good partner with both Uber and the 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. So 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 twenty-four hours. So it's expanding a new market. And right now it's still a very low percentage of penetration. So still cool, you have a lot of room to go.

• 40:43Speaker 03

  Uh, on the other end, to your question about the success factor, I think the two things. One is a technology need to cutting edge and improving. And number two is operation efficiency, right? So it's actually. A lot of work need to be operational driven. For 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 thirteen years so far. And I can tell you one interesting fact globally, there are only two cities right now have over, you know, thousand cars in that scale, which is San Francisco and a wind city in China, which is Google operating in San Francisco and Apollo from Baidu operating one city in China.

• 41:27Speaker 03

  But I think our kind of partnership with both, you know, Lyft and Uber globally with different cities, I think has been very collegial because the demand is much higher than the than the supply.

• 41:37Tracy Alloway?

  Yeah. Joe, I'm going to admit something.

• 41:40Joe Weisenthal?

  Yeah.

• 41:41Tracy Alloway?

  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.

• 41:58Joe Weisenthal?

  It's coming.

• 41:59Tracy Alloway?

  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.

• 42:33Speaker 03

  Yeah. So in the mobile internet where, you know, everyone look at, for example, the DAU, 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. So 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 thought leadership. That DAA, which is the daily active agents, are the new kind of matrix to defining the success of agents. So I I I kind of very uh uh much agree on that. The reason is, if you look at the tasks, it's actually spread out into different verticals, right?

• 43:18Speaker 03

  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. The agent is smart enough can think about the planning, the task and completing the task. And obviously, in the way of interacting with human beings, it actually become more smarter and in a way that are working with more efficient planning of that. So to your question, overall, uh my 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.

• 44:03Speaker 03

  So I just want to share a few things. For for example, right now, we have three or four different key products. One of them, we we in China called a FAMO, it's really solving complicated issues for enterprises. It's very similar to AlphaGo, which actually in the previous years, yeah, is 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 ports. So the ports actually willing to share a certain profit generation with us.

• 44:43Speaker 03

  So the key things I'm observing is, in the previous meetings, even I'm the CFO, but actually I'm attending a lot of, you know, the meetings to to meet with client. 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, it 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. Bydo is 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 become relatively more efficient in a way that we get into the number one decision makers.

• 45:27Speaker 03

  He has a budget and he knows that driving the product efficiency is important for his task. So he's willing to share certain economics with us. So I think the customization is also diminished because right now the agents can be used different parts. 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.

• 45:58Joe Weisenthal?

  This is actually an interesting question because I've seen debate on this within AI about what is 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, et cetera. 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

• 46:41Joe Weisenthal?

  a sort of per task or sort of very clearly linked to the efficiency gain?

• 46:46Speaker 03

  Yeah, 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 probably is very energetic, right? If you do that like ten, twenty times in two weeks, it's very exhaustive, right? Because you need to think about.

• 47:04Joe Weisenthal?

  Wait, you're saying we're gonna be replaced?

• 47:05Speaker 03

  You share my views, right?

• 47:06Joe Weisenthal?

  Wait, wait, is that what you're insinuating? We're gonna get replaced because we get exhausted, but the AI agent won't get exhausted?

• 47:12Speaker 03

  So, so, you know, so, so my point is the humans, their, the 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.

• 47:39Joe Weisenthal?

  Yeah.

• 47:40Speaker 03

  And a lot of live performance is really selling the products.

• 47:43Joe Weisenthal?

  Yeah, it looks fun.

• 47:44Speaker 03

  But you know, the the caveat is the the KOL cannot work like twenty-four hours, right? So and people cannot buy stuff like twenty-four hours. But if you think about, you have a great quality of the human employee can help the merchant owners to selling to 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, you know, 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 pushing on that and selling all the the goods. And it actually can perform pretty well because on the, you know, the Q and A sessions, on the questions, it's actually reacting

• 48:30Speaker 03

  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.

• 48:45Tracy Alloway?

  I've tried to buy things for twenty-four hours straight before. I think when I first used Taobao.

• 48:50Speaker 03

  Yeah.

• 48:51Tracy Alloway?

  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 five hundred square feet large.

• 48:59Speaker 03

  So so my little suggestion, you need to have another agent help you to sell your right products. So that's another way you probably can monetize on that, so.

• 49:06Tracy Alloway?

  Are you gonna spin out the chips business? We're at Bloomberg Invest, it's our first live recording of Odd Lots, let's break some news.

• 49:12Speaker 03

  All right, so it's coming to the to the money part.

• 49:17Speaker 03

  So I was not, to be frank, I was not even trained by by finance, I become self-employed by accident.

• 49:22Joe Weisenthal?

  You're a chips guy.

• 49:23Speaker 03

  So actually, my both bachelor and master training was a chip designer myself. So I think after joining Baidu, I definitely realized that Baidu's. Chip product has been really, really high quality and really good for the influence, for the, for the, all the things we talked about, the, the helping our DAA to grow as well. So 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 enhancing that ecosystem.

• 50:08Speaker 03

  And as you know, chip is not only the hardware. I deeply understand it is about ecosystems.

• 50:13Joe Weisenthal?

  Yeah.

• 50:14Speaker 03

  We need to work pretty well with our customers and the suppliers and the software developers all at a one goal. And I think to be a separate listed 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 more usage on their own cases.

• 50:36Joe Weisenthal?

  Yeah, I seem to recall reading that you figured out a way that developers can easily port over their CUDA stack over to your stack without much trouble. Henry, thank you so much for coming on Odd Lots, our first live recording anywhere in Asia. Really appreciate it.

• 50:54Speaker 03

  Again, thanks.

• 50:55Joe Weisenthal?

  Truly the perfect guest.

• 50:56Speaker 03

  Yeah, again, thanks for having me. Thank you, Joe. Thank you, Tracy. Thank you.

• 51:10Tracy Alloway?

  That was our conversation with Henry Hutt, the CFO of Baidu, recorded live at Bloomberg Asia Invest. I'm Tracy Alloway. You can follow me at Tracy Alloway.

• 51:21Joe Weisenthal?

  And I'm Joe Weisenthal. You can follow me at TheStalwart. Follow our producers, Carmen Rodriguez at Carmen Armin, Dashal Bennett at Dashbot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And for more Odd Lots content, go to Bloomberg.com/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.

• 51:43Tracy Alloway?

  And if you enjoy All Lots, 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. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.

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