Transcription
Wow, what a big room. Mojour, are you enjoying today? Yeah, a bit trippy. Okay, now you will have a great, great, great session. Jai from Alibaba with Kristoff Jacobine from Leico.
As you know, Vivate is a worldwide platform, and we are pleased to welcome more than 170 countries. And when you walk through the aisles, you will see a lot of pavilions from countries and a lot of nationalities. We hear a lot about our friends from the US, from Europe, of course, but too often we tend to forget the other, other half of the world. And that's why our next guest is here. He co-founded Alibaba. People do not know very well his name, but they will remember forever because he has helped transforming Alibaba, and Alibaba has created Quen. And I'm sure that you don't know, but Quen is the most widely used open-source model in the world. The most widely open-source AI model. It's not chip. It's not cloud. It is Quen. And Alibaba released its latest version of Quen a few months ago. And we are pleased to welcome someone who has been at the helm of the company since its inception, and he was the man behind the open-source of AI. So please welcome very warmly Christoph Jacobiz from Leico and a big round of applause for Joe Tsai, chairman and co-founder of Alibaba. Joe, welcome.
Hello everyone. Thank you to be here. We're very, very pleased to, as Maurice said, to, uh, to welcome Joe Tsai, the co-founder and chairman of Alibaba. Um, Alibaba went through many revolutions, and of course, we'll speak about the last one, about the open-source LLM model. Uh, but first, can we talk about your history? Because, um, many people in France still think you are a marketplace, B2B, B2C. We know AI Express here. I know you have the largest, uh, marketplace in the in China. So, could you tell us more about your, the evolution of your company, of your group?
Yeah, thanks Kristoff. It's, uh, Maurice, it's great to be here. Uh, so Alibaba started in 1999 as a B2B marketplace, and at the time, the business idea was very simple. We put these small Chinese manufacturers and trading companies online, uh, to sell to the whole world wholesale. So that kind of was on the cusp of China entering the WTO. So the export business was about to boom. And then we got into the, uh, consumer B2C, uh, uh, business and launched a, a website called Taobao, and which today is the largest, uh, e-consumer e-commerce business in China.
How many consumers?
We serve 820 million Chinese consumers. And by the way, this platform helps European companies and brands to sell 30 billion euros to Chinese consumers every year. So you would say that Alibaba is quite important, uh, for European companies doing business, uh, around the world. Uh, but you, what we are, are went big into AI and cloud, uh, and this is, uh, actually, it's quite a long history. We've been investing in cloud technology since 17 years ago, and that's because of necessity. Uh, we were seeing that we were managing so much data from our e-commerce business and transactions on a daily basis, uh, that if we continue to be dependent on other people's technology, like database and storage technology from others, uh, we would end up giving all of our profits, uh, to the technology providers. And, uh, hence, there was an effort to develop our own, uh, proprietary technology to manage all the data. All right, and, and that's when our cloud business was born. Uh, basically, we ate our own dog food, uh, before we launched the business to offer that service to third-party, uh, customers. But I think that that's sort of from the micro perspective. From a macro perspective, we're all in on AI. Uh, it's actually the logic is very simple. Uh, AI is today, if you ask me how big is the market, what is the demand, what is the TAM, total addressable market, uh, I would tell you that it's much, much bigger than anybody's IT budgets. It's much, much bigger than the software market because what is AI? AI is producing units of human intelligence and human productivity. And if you look at global GDP, over a hundred trillion dollars of GDP, uh, at least half of, at 50 trillion, 50 trillion dollars is about human productivity and human intelligence, and that is the TAM of AI, and that's why we're all in on AI.
So, so you think AI will really make us have a higher productivity? Because we, we just had like one hour ago a round table where we were questioning that, people are investing a lot, but they don't see the results yet.
They don't see the results yet. I think a lot of corporate CEOs will tell you that their engineers are burning a lot of tokens, cost goes up. Uh, but I think I would say we're at the cusp of, uh, real productivity gains. Uh, right now, a lot of people are experimenting, and there are, uh, definitely, like we see it in our company, our own engineers. There are super users that, uh, use the coding tool, for example, and they are, uh, not just doing their work that's within their domain, but they're also experimenting with other stuff because when you give engineers toys, they will always play, uh, with it more than, and, and they didn't realize, uh, that the company's actually paying for it, right? So this is what's happening right now. But I think what, what I truly believe, this is really a belief of whether, you know, uh, production of artificial units of intelligence will be able to add value to human intelligence. And, um, it's like religion. I don't, I don't want to convince all of you that that's going to happen, but we believe that that's going to happen.
So if we go back to the Alibaba evolution, in which layer of AI do you, do you invest most? Is it infrastructure, models, cloud services?
So we are in at least four layers of AI. Um, at the, uh, at the, uh, the bottom, we're not involved in energy because in the China context, energy is actually very efficient, less expensive, and the Chinese government has has invested over the last 15 years in the national grid that makes energy delivery, production, and delivery very, very efficient to all the users. Uh, but we are at the, from the bottom, we're involved in chips, uh, infrastructure in terms of our cloud business, and also the model. We have, uh, as Maurice very, uh, you know, uh, you know, kindly pointed out that we, our Quen model is actually one of the most popular open-source models in the world. And then at the application layer, we have an e-commerce ecosystem, uh, we have an ecosystem for online shopping, grocery delivery, uh, travel, maps, and all of that, uh, that can where we can infuse and deploy AI for our users. So we're involved in all those stacks, uh, of, uh, technology, and, uh, we, we think that there's huge benefits to the full stack tech, uh, approach as opposed to just taking one layer, uh, of the stack, uh, because I think over time, nobody can tell you right now where the value will accrue, which part of the stack. Is it in chips? Is it in cloud? Or is it in the model? Uh, right now, the model companies, pure model companies, are very hot. They seem to accrue, uh, a lot of the value, uh, but over time, that may not be the case. Uh, so having an integrated approach of being involved in the full stack, uh, makes a lot of sense to us, and that's our core strategy.
That's very interesting. You're right, we don't really know where the value will be. But when you see, you know, the investment in infrastructure for AI, do, do you think there is a kind of bubble? There is, do we have all those needs to make the model work? Because some models are more efficient than others, and they need less, uh, capacity than others. So what about that?
I don't think so. Uh, I mean, the numbers really are quite astounding, because if you just look at the American hyperscalers, the four or five companies combined will invest over $800 billion of capex, and next year it's going to go to over a trillion dollars. It, it's, it's eyepopping type of capex investment. And, and I think it's natural that people will ask whether there's going to be overcapacity. But again, like I said, we're going against, we're, we're trying to tackle a total addressable market of 50 trillion US dollars, and that's, uh, that's why we're optimistic. And in the China context, uh, we're actually very underinvested in, uh, infrastructure and in the supply chain of AI. Uh, and so it actually behooves all the companies in China to step up their investment. Uh, obviously, we're not investing at the same level as some of the American hyperscalers, but it is still very, uh, uh, very substantial.
Why don't you?
Oh, well, you know, sometimes you're limited by, uh, the, your, your capital. Uh, you're limited by the free cash flow that you're generating. Uh, and the good lucky thing is Alibaba is one of the very few companies that actually has a core business, which it is e-commerce. We generate $25 billion of free cash flow every year from our e-commerce business that can fuel our investments in AI. So, we're, we're actually one of the better positioned companies, uh, out there.
I think today, your, your, your business in, in, um, marketplace is still 80, 85% of your, of your total.
Yeah, it, it is still 80 plus percent of our revenues in the e-commerce marketplace. Uh, uh, we're very lucky that that gen produces a cash flow that allows us to make, uh, future investments.
To invest in AI and cloud business.
Yes, absolutely.
What about your, your, Maurice mentioned the, the Quen offer and the Quen model? What, what, because it's open source now. So, so,
Yeah, what kind of customer and you can have and you can help with that?
Well, I thought Maurice was too charitable in crediting me as the open behind the open-source movement. That, that's totally untrue. Uh, I would say that our colleagues at Alibaba have worked the last several years in pushing, uh, the open-source movement in, uh, these frontier models and to, to a high degree of success, and we're continuing to do that. Um, what's the significance of open source? So, I've been spending the last couple of weeks in Europe. And as I talk to European companies and CEOs and, uh, uh, scientists, people in Europe, one of the biggest keywords here is sovereignty. Uh, but what is sovereignty? If you ask 10 Europeans about what sovereignty means, you'll get 12 different answers. And, um, uh, but to me, they mean basically two things. One is technology independence. Uh, they, they are all worried about the kill switch. Uh, that being relied on some other country's technology, uh, they could turn, shut off the kill switch. We just saw a very live example of that in the recent days.
Yeah, Fable, right? And, uh, the, uh, the second is data privacy. People wanted to be able to use AI, use technology with data that's proprietary to them within their own environment, and hence build up the firewall to protect their own data. Uh, I think open source solves both problems because it is basically a free piece of software that you can download into your data center. You can develop, uh, you could download the Quen model in your own notebook computer, for example. Uh, and that, that's completely independent from, uh, the original maker. Uh, so if you use our open-source Quen, open-source model, it will have nothing to do with Alibaba. I mean, we have to figure out how we charge for it, but we can't. Um, so that's number one. That's independence. What's important is you can take the open-source model and then you could take your own data and train it further, train it, fine-tune it, do post-training of the model, and, and keep all your entire data private within your own firewalls. And I think that's a really, really important point, uh, for companies in Europe to recognize that, uh, open source is actually one, I'm not saying it's the panacea, it's not the only approach, it's one of the approaches to achieve some degree of sovereignty. And, uh, today, uh, the open-source movement is actually driven by Chinese companies. All the American players, uh, have closed-sourced their their model. So they want you to use, uh, their models through an API. And you have no idea where your data is going when you, when you're chatting with a, you know, a chatbot. Uh, all of your most private questions and your confessions, uh, go into some, you know, some pool where they use that to further train their model. So you have no idea where that, that's going.
But to be honest, we, we, you know, Europe sovereignty is a very great concern today, and I think we just realize how dependent we can be from the US or from China, from the industry, for instance. So, um, how, I mean, I, I agree with the open, I mean, the open model, etc. But, but still, we, we can be worried. There is, you know, bypass for the Chinese company to maybe, to one day, if they want to cut the access or to be able to stop the model to function. How can, or can we trust China as we, because we were deported by the US in the last days? But, but we could be also by China. I mean, it's, it's a big risk for Europe.
Yeah, you can't. That, that's the short answer because you cannot be relying on a, a third-party government to say that they won't do something that's detrimental to you. But here's the thing. Right now, all of your eggs are in one basket. Why not get a second basket to put your eggs in? Two baskets. Even though Europe, at, in, in the long term, may, uh, develop their own basket, but at least now you have two eggs, sorry, two baskets to put your eggs in.
That's true.
Maybe we can, you, you can give examples of how you work with the German company like BMW, you, you help them, or Siemens in Germany. What, what was the basis of the collaboration and cooperation you did with them?
Yeah, so these German manufacturing businesses are absolutely fascinating. They're all clients of ours, Alibaba Cloud in China, in their Chinese operations, uh, and we work with them in, in the manufacturing context, uh, in terms of design, testing, quality control, and, uh, uh, we think that, uh, this is in the future, is going to be a very interesting segment because today, most of the applications in AI, you know, you have ChatGPT, that's consumer. You have like Cloud Code, that's, uh, uh, focused on, uh, coding and the knowledge worker space. But in the future, uh, these manufacturing businesses are very valuable because they will have very valuable data that's proprietary to them in the manufacturing process, and that data is, is very, very good, high-quality data that you can use to train your own model, to improve your manufacturing process. And this is the approach that we're taking, uh, with these companies. Uh, you, you also, uh, mentioned BMW, Siemens, we also have worked with Bosch. Last week I was at the Bosch Connect World conference, uh, we work with them because they are, uh, using AI, uh, to develop their, uh, assisted driving, autonomous driving, and that requires a lot of compute. Uh, so, you know, uh, there's a lot of very interesting going on in the manufacturing sector.
So if I understand you, you consider the ban on entropy class model by the US an opportunity for you and your model to be, to be adopted by other European customers.
Our model, your model. Yeah.
Uh, yeah. Well, there's two approaches to it. Uh, one is, uh, through, you know, they could just take our open-source model and then, uh, they will put that, deploy that into their own infrastructure if they have their own data center, whatever. And, uh, but our infrastructure is developed hand, sort of, you know, hand-in-glove with the model. So we actually have one of the most efficient infra to help people train their models. And, uh, so if they use our open-source model, they could also buy compute from us, right? So that's a symbiotic, very symbiotic relationship between the model and infra. Um, so, uh, that's one approach. Another approach is there are now emerging a number of, uh, uh, companies that, uh, develop, uh, these, uh, inferenceing platforms that offer people a choice of models, different kind. You don't have to use Quen, you could use somebody else's. They also can access closed-source models as long as there's an agreement between the model maker and the inferencing platform to open up the weights, the gates to the weights, in a private context, and then customers can go on the go onto these inferencing platforms to use the models.
I have a more philosophical question about, um, your vision of the future of AI, LLM, balance between humans and and agents, and even humanity. How do you see the, the next 10 years of humanity?
Uh, so today I was, um, I had a, a talk with, uh, the Alibaba Paris office colleagues. It's located, we just moved to a new office. It's located in the, I think the second or third floor of a beautiful building. And I looked out the window. There's a cafe, and people are sitting in the cafe, uh, outdoors because the weather is pretty nice, having a great time. And I point to them and I tell my colleagues, this is the future of AI. They may be, you think they may be drinking coffee and, you know, having a good time, not doing anything, not being productive, but the reality is, they have deployed agents that are doing the work. So when you're going to sleep, you still have agents working for you.
Yeah.
So think about the productivity gains if, uh, 24/7, you can actually have somebody else work for you.
So you have, you have the same philosophy that the, the people from the Silicon Valley, you think that many people won't work and we will make the agent and robot work for them.
Well, I, I think it'll free definitely free up, uh, people's time, uh, to do, to enjoy life, to enjoy their family, to do more entertainment. This is why I'm very big on live entertainment. I mean, when people, uh, spend less time in the office, where do they want to go? They don't want to just sit at home. They want to go to concerts. They want to go to, uh, football matches. They want to go to basketball games. Uh,
Don't tell that to French people because they will, they will want to work less.
Well, a lot of them are focused on the World Cup right now. So.
I think you Chinese work, work a lot. When you, when you look at the Chinese engineer, they, they have lots of working hours, even with agents, even with AI.
Uh, there will always be people that will work a lot more than others. Uh, but I think most of us want to be able to enjoy life a little bit, want to be able to spend time with our family more.
I think you, you're a very big, a big fan of the basket, Brooklyn Nets, and even the Liberty New York supporter. I think you even support a player, I even don't know, Lacrosse. Um, what about soccer World Cup? Are you, are you enjoying the, the soccer?
Well, first of all, about basketball, I went to the French league championship game last night between Paris and, uh, Monaco. This is the second game of the five-game series. And I thought it was very interesting. And then I realized that our women's basketball team, the New York Liberty, have three French players. Three players that play for the French national team. And then we have on the men's, uh, Brooklyn Nets have one French player. So there's a lot of very big French connection. I think, uh, France is probably, uh, the most important non-American influence in the NBA and also in the WNBA, uh, today. So it's very interesting. Uh, so about the World Cup,
Um, I, uh, I don't have a horse in this race. That's the problem. Uh, I think I just saw some social media, um, that says there's a Chinese referee in the World Cup, and he is getting sponsorships. And I hope at some point China will have a strong team, but, uh, I think the development will take some time. Yeah.
Thank you very much. Thank you. Thanks to you. Thank you.