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

Odd Lots - Bloomberg

Baidu's CFO Henry Heh discusses the company's full-stack AI strategy, emphasizing cloud infrastructure as a key differentiator. He highlights Baidu's focus on inference, talent development, and the strategic importance of its custom chips and digital employees.

Key takeaways

• Cloud infrastructure is Baidu's must-win layer for AI deployment and monetization.
• Baidu measures AI ROI through task completion and efficiency, not just token spend.
• Talent acquisition focuses on autonomy, mentorship, and empowering 'one-person teams'.

Transcript preview

I'm Francine Lacroix, an award-winning journalist, and I've got a new podcast, Leaders with Francine Lacroix from Bloomberg Podcasts. I've interviewed everyone from heads of state to fashion icons about the news of the moment. But I've always been curious who are these people as leaders. I don't think there's one right way to be a leader. Make decisions. A poor decision is always better than no decision. Listen to new episodes every other Monday. Follow leaders with Francine Lacroix wherever you get your podcasts. Bloomberg Audio Studios. Podcasts, Radio News. Hello and welcome to another episode of The Odd Lost Podcasts. has changed actually I was kind of surprised 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 and we finally got a chance to talk to a couple high-level executives of Chinese tech companies who are actually making all the big capital allocation decisions when it comes to the AI race right it felt like we're in this moment where there's been the I mean the way I think the way I think about it So 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 on internet companies specifically and where they're 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, etc. And so there are all kinds of options for people. So it's like really interesting to see like, okay, okay, okay, okay, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, this clash, like it's happening. It's a good time to talk to a Chinese tech executive for sure. 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 oddlots trivia night while we were in Hong Kong. Our first non-US overseas Oddlots quiz night. 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 Heh. So, so check it out. So Henry, thank you so much for coming on O'Lott. Thanks for having me and it's great season. I think in Hong Kong, it definitely is great to seeing both Joe and Tracy. Thank you, very nice of you to say. So why do 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 your own chips and of course your own model. As the CFO, you might have, you might have to think, you might have to think about prioritization, etc. 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? 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 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 trip 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 I-O-I questions, especially for the people like me, a CFO, we focus on that, is on application layers. So without any. So without any of that, this I can not 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 trip, which connecting to my cloud platform can also help on inference. Because right now the pre-training is important, but 80% of the incremental demand today on a token are inference related. I think this part. what I want to emphasize but you know given a tough question if I want a big one as a student ABCD I want big number C which is my cloud I'm gonna ask you a question which I think is gonna become standard for financial journalists in the same way we ask about head count and expansion plans what's your token budget is it bigger than Joe's you mean a token? The token budget the token budget for Baidu yes 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 do you measure productivity? Yeah, sure. I want to categorize probably two buckets. One is we consume computing power to reach a higher level of technology standard, you know, the AGI, the Hawkwood model perform, and also how harness can be designed to deliver better results. So this are our and the effort. However, as also a tech house, we also deliver those know-how to our external clients with different verticals. I think it is. I'm measuring our internal consumption of the token. I really want to like that 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 that the open claw and for example our own application called Doomate also is a real agent's human digit and other things can do the task. So I think these two different measurements are important in the way that right now, there are two different measurements are in the way that right now that right now that right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now, right now things are better than last year. When is a foundation model getting much better? And number two is the framework, i.e. open cloud 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 to do that. But think about that even last year or a year before, everyone is actually before. I think that budget is always there but the completion new task is more important. 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 gonna increase her budget? that and do you have measurement techniques to see like this person really should get 10 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. You know to give in the question asking I think probably next time I give you more tokens. 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 a certain policy by saying you know these are these are the employees the token number by the titles or the seniorities. I don't think that's a way works. So I think we want to more open and more nimble in the way that given enough token to the individuals to empower their internal R&D efforts. But on the other end, we do have a lot of efforts to make sure the token costs become dramatic coming down. I think the cost is coming out very fast. Before you even think about getting a policy, maybe the unit cost is coming down, maybe the unit cost is coming down half. 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, we are recruiting a lot of younger talents today, even for Baidu, which is 20 plus years listed a public company. 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. what are the tasks they need to prioritize because they are 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 at 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 important. 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 by do top tech firm? Yes, great question. So let's bring a different perspective. I think, you know, we are a technology company. Previously, I think the priorities 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 change us as well. We need to think about the cultural change us as well. We need to think about the cultural change us. 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 a client versus think about new tools affecting ourselves. So Tris 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, we also task the senior people not only look at 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 is 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 so we're very happy to working with one person company because they actually use our AI too very 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 the agents to work a lot of internal tasks. So internally we have a little tool called Doudou, right? In Chinese, a very kind of a nicky name, which is actually our internal kind of open clock, similar tools and which actually enhancing people's efficiency. And to a point I think give me more people more autonomy, more trust and more trust and more room and more room. grow and attracting new talents, I think equally all kind of very important to change ourselves, but also, you know, reporting lines and the organization structure need to come with it to make sure that people can deliver the results. And 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. You know, it just occurred