Future of Business: Baidu’s Robin Li on the Technology Trends that Will Transform Business

**Alison Beard** (0:10)
Welcome to the HBR IdeaCast from Harvard Business Review. I'm Alison Beard.
Baidu launched in 2000 as a search engine platform. Fast forward two decades, and it's now one of the few companies in the world that offers a full AI stack. Its core businesses span mobile, cloud, intelligent driving, and other growth initiatives, and its products and services have attracted hundreds of millions of users, and hundreds of thousands of enterprise customers. Today's guest is leading all of that. For the third episode in our special series on the future of business, we'll hear from Robin Li, the co-founder, chief executive, and chairman of Baidu. He explains how his company has built generative AI into its business, the technology trends he's keeping an eye on, and how he anticipates these tools will transform our lives. Robin spoke to HBR editor-in-chief Adi Ignatius and took questions from the audience during our recent virtual Future of Business conference. Here's their conversation.

**Adi Ignatius** (1:14)
So Robin Li, I know it is very late your time in Beijing, so we appreciate you're joining us live for this. Welcome.

**Robin Li** (1:21)
Hi, Adi. Thank you for having me. It's great to be here.

**Adi Ignatius** (1:24)
Well, it's great to have you. Before we start, let me just remind everyone in the audience to put any questions you have for Robin in the Ask the Speaker chat, and I will try to get to as many as I can later. But Robin, let's get to it. So Baidu, your company introduced a chat GPT-like product, ERNIE Bot, last year that last I saw has more than 300 million users. I assume it's been a learning experience for you. Can you talk a little bit about what you've learned since the first version came out and how it has evolved and just tell us a little bit about all that?

**Robin Li** (1:56)
Yeah, sure. We launched ERNIE Bot, I think March 16th of last year. I think that was the first chat GPT-like chat bot for all the public companies around the world. Because we've been investing in AI, especially natural language-related AI for quite a few years. We were able to quickly launch a chat bot based on our large language models. Over the past year and a half, a lot has happened. The technology has evolved very quickly and dramatically. Things we learned, there are a lot of things I should mention.
The first is that a lot of people, users, developers, customers, they not only care about the efficacy of the model, they also care about the response speed. They also care about the cost of the inference cost. So, after March 12th last year, we have rolled out a series of language models or foundation models to satisfy all kinds of different needs in different scenarios, meaning that the model size could vary greatly and the inference cost could be very different too. And in certain cases, users don't mind to wait 10 seconds to get the best answer. And in other scenarios, you will have to do it very, very quickly, sub-second response time. And also, in terms of cost, we've been able to reduce the cost by about 99%, meaning the current inference cost is about 1% of the original cost when we first launched that. I mean, said all of that, I would say that probably the most significant change we're saying over the past 18 to 20 months is the accuracy of those answers from the large language models. And I think over the past 18 months, that problem has pretty much been solved, meaning that when you talk to a chatbot, a frontier model-based chatbot, you can basically trust the answer. That's a huge difference.

**Adi Ignatius** (4:29)
Now, from my perspective, maybe this is a US perspective, there was a huge wave of excitement about AI, particularly with the release of generative AI products. You know, you've talked about search. There don't seem to be a lot of or as many interesting use cases as maybe some of us had expected by now. So I'm interested in your view. You know, are we in an AI bubble at this point? You know, what's the trajectory of the technology?

**Robin Li** (5:00)
I think like many other technology waves, bubble is kind of inevitable when you pass the stage of initial excitement. People would be disappointed that the technology doesn't meet the high expectation generated through the initial excitement. We've seen this many times when the Internet took off in the mid to late 90s, and there was a huge bubble. For mobile Internet, similar things happened. And this time for generative AI, I think we will also go through that kind of period, too. But I think it's also helps. It will wash out a lot of those fake innovation or products that doesn't have a market fit. After that, probably 1% of the companies will stand out and become huge and will create a lot of value, will create tremendous value for the people, for the society. And I think we are just going through this kind of process. This year, the sector is probably cooler than last year, but I think it's also healthier than last year.