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

**Henry He** (0:02)
Bloomberg Audio Studios, podcasts, radio, news.

**Joe Weisenthal** (0:18)
Hello, and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.

**Tracy Alloway** (0:22)
And I'm Tracy Alloway.

**Joe Weisenthal** (0:23)
So we were in Hong Kong recently. That was a lot of fun.

**Tracy Alloway** (0:25)
Nice to be back.

**Joe Weisenthal** (0:26)
I love visiting Hong Kong.

**Tracy Alloway** (0:26)
Yeah, I haven't been back for four years. Not much has changed, actually. I was kind of surprised.

**Joe Weisenthal** (0:31)
Less than you expected?

**Tracy Alloway** (0:32)
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 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.

**Joe Weisenthal** (0:55)
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 on Internet companies specifically, and where they're like competing, 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, this clash is actually like it's happening.

**Tracy Alloway** (1:31)
It's a good time to talk to a Chinese tech executive for sure.

**Joe Weisenthal** (1:34)
That's right. So the reason we were back in Hong Kong is because we were at the Bloomberg Invest Conference, we also threw an Odd Lots Trivia Night while we were in Hong Kong.

**Tracy Alloway** (1:42)
Our first non-U.S. overseas Odd Lots Quiz Night.

**Joe Weisenthal** (1:45)
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.

**Henry He** (2:04)
Thanks for having me. And it's a great season, I think, Hong Kong. It definitely is great to see both Joe and Tracy.

**Joe Weisenthal** (2:10)
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 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, 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?

**Henry He** (2:45)
Thank you so much. I think you'll probably put the tough question in the end, but I think it's probably the most difficult question to start with.
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 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 ROI questions, especially for the people like me as CFO, we focus on that, is on application layers. So without any of that, this ROI cannot work. So to answer your 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 host in Ernie, which is our own model, but also I can work very open to hosting other models. And the MyTrip, 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 of the full picture is what I want to emphasize, but given the tough question, if I want to pick one as a student, ABCD, I want to pick number C, which is my Cloud.