Alibaba Chairman Joe Tsai Spoke at Edward K Y Chen Distinguished Lecture 2025

Ladies and gentlemen, welcome to the Edward KY Distinguished Lecture 2025. I'm Xiaawing Chu Kevin, a year three student in the International Business and Global Management program.

And I am Emmy Hagawa, a year 4 student in the International Business and Global Management program. We are happy to be the MC's for today's event, and we are delighted to have Mr. Joe Thai, co-founder and chairman of Alibaba Group, to share with us his valuable insights. As a business school student, it is such an honor to be able to learn from an industry-shaping business leader firsthand. Before the lecture commences, may we first invite Professor Hing Thai, Dean of HU Business Studio, to deliver a welcome remark. Professor Tai, please.

Professor Edward Chen, Mr. Joe Thai, Executive Committee member, distinguished guests, colleagues, alumni, friends, ladies and gentlemen. Good afternoon. Welcome to Hong Kong U. Welcome to this historical Loyal Hall, and welcome to this annual signature event, the Edward Chen Distinguished Lecture Series.

Now, this lecture series was established to honor the legendary role Professor Edward Chen has played in educating, mentoring, and nurturing leaders. For some reason, Edward has lots of secret tricks. So, he has been so successful that many of his students went on to become influential leaders in all sectors of Hong Kong. And Edward's legacy has inspired generations of teachers at Hong Kong U Business School and has become a cornerstone of our tradition.

Recently, Hong Kong U has enjoyed lots of good news. Our rising, you know, rankings, QS number 11, surpassing many of the leading schools in the world. And there's very little room to go further up, but we certainly will continue to work hard. And Hong Kong Business School also, you know, seen our ranking in research and other things, and has risen up over the years. But with all this, we must never lose sight of our core mission. Our core mission is always in education. Our mission is to educate and nurture the next generation of leaders for Hong Kong, for China, and then for the world. So, let's continue to follow Edward's example, committing ourselves to making positive impacts on our students, and they can go on to make positive impacts in the world. So, please join me in giving a warm round of applause to the forever young Professor Edward Chen.

And today, we're truly, truly honored to welcome Mr. Joe Thai, co-founder and chairman of Alibaba Group, as our distinguished speaker. I think what I'm most impressed about Joe is his extraordinary ability to reinvent himself and reinvent Alibaba time and again. So, from his early days as a lawyer, as a banker, I was asking Joe why he made that jump to join a small startup in Hangzhou, which was led by someone who couldn't find a job himself, and to join and then to really transform e-commerce in China, and then later on investing in global sports franchises, and then when Alibaba needed him, went back to Alibaba to steer Alibaba to this AI and cloud era. So, I think his journey is really a masterclass of courage, of vision, of adaptability, of great leadership for change. I think in today's fast-evolving world, and this is very essential for any personal and business success.

So, at the Hong Kong Business School, we too embrace this spirit of reinvention. So, as AI and global dynamics shift at an unprecedented pace, we've been launching new programs, reforming our curriculum, refocusing our research to remain at the forefront of business education. From our roots in Hong Kong, we've deepened our presence in mainland China with centers in Beijing, in Shanghai, in Shenzhen, while also expanding globally with a center in Vietnam and our Hong Kong Europe center or campus in Barcelona. So, to our students, alumni today, whether you are navigating a competitive job market or a fast-changing industry, I think the ability to embrace change and reinvent yourself and your business is absolutely crucial. So, I'm sure Joe's insights will inspire all of us. So, thank you so much, Joe, for joining us. We are so delighted that you are here. Let's get started. Thank you. Thank you, Joe.

Thank you, Professor Tai. Please be seated.

Wow, Emmy, our hall is bustling today. Let's make this moment unforgettable with a group photo from the stage. Everyone, please be ready for our official photographer.

Hey, hey, hey. May we now invite Mr. Hing Wang Fung, convenor of the Edward Chen Distinguished Lecture Series Organizing Committee, to introduce our speaker today. Mr. Fung, please.

Good afternoon, everyone. It is a genuine privilege to welcome all our distinguished guests, esteemed faculty, fellow alumni, and students to this Edward Chen Distinguished Lecture. While there are many distinguished guests in this hall, in the interest of time, allow me not to address any of them individually, but just say, all protocols observed. I trust none of you would want me to stand between you and our speaker for too long. Let me now start with my pleasant duty of introducing the speaker.

Ladies and gentlemen, we're living in a moment of profound global transformation. The question of what drives economic growth in the world's second largest economy is not just an academic exercise. It is a critical puzzle for business leaders, investors, and policymakers worldwide. To explore this vital topic today, we are incredibly fortunate to have with us a visionary who has not only witnessed China's economic metamorphosis but has been one of its principal architects. It is my pleasure and honor to introduce our guest speaker, Mr. Joe Chai, the co-founder and chairman of the Alibaba Group.

Many of you know the story. In 1999, when the internet was dawning, a former teacher named Jack Ma had a bold vision. He found his perfect partner in Joe Chai, a young, educated lawyer with a deep background in private equity. While Jack was the charismatic heart of Alibaba, Joe was the strategic and financial backbone. He structured the company, secured its early funding, and for over two decades has been the steady hand guiding its growth from a humble apartment startup to a global technology titan.

Some of you may recall that Jack Ma was on this stage addressing a similar audience 17 years ago, in the year 2008, as the speaker of our second distinguished lecture. We must thank Alibaba for the great support given to this distinguished lecture series, as we have had both of his co-founders as our speakers.

As chairman of the Alibaba Group, Joe's purview extends far beyond e-commerce. He oversees Alibaba's strategic acquisitions, its global expansion, and its long-term vision. But to define Joe Chai solely by Alibaba would be to tell only half the story. Beyond Alibaba, Joe is a renowned investor and philanthropist. Through his family office, the Bluepool Capital, he has a panoramic view of global technology and innovation trends. Furthermore, as the owner of the Brooklyn Nets, the New York Liberty, and a number of other sports organizations, he understands the power of building global brands and fostering community, a skill set highly relevant in today's interconnected world. He is also a proud member of the university community, holding both a JD from the Yale Law School and a BA in Economics and East Asian Studies. He has conferred an honorary degree in Social Science by the Education University of Hong Kong. His journey from the classroom to the pinnacle of global business is a powerful testament to the impact of world-class education and a tremendous inspiration for our students here today. His diverse roles—founder, chairman, investor, and philanthropist—give him a unique and invaluable perspective. He sees the big picture from the boardroom, the granular details on the balance sheet, and the human impact from his philanthropic work. This is why there is no one better to guide us through today's topic than the logical drivers for China's economic growth in the next 10 years. He won't just be speaking about theories; he'll be sharing insights forged in the marketplace.

In a moment, he will join Professor Haiyan, an associate dean of the Business School. Professor Tang is also an associate vice president of the University of Hong Kong. The two of them will have a fireside chat, a conversation that promises to be not just informative but illuminating. Ladies and gentlemen, please join me in giving a very warm welcome to the man who helped shape the digital landscape of China and beyond, Joe Chai.

Thank you, Mr. Fung. Please be seated.

Without further ado, let's welcome Mr. Joe Thai, co-founder and chairman of Alibaba Group, to proceed to the stage for the fireside chat. Please, may we also invite the moderator, Professor Hai Wii Tang, Associate Vice President Global of the University of Hong Kong and Associate Dean of HKU Business School, to proceed to the stage.

We will now pass the floor to Professor Hai Ten. Professor Ten, please.

All right. Uh, so first of all, I have never seen so many people in Lugo Hall. You know, Joe, uh, this is our oldest lecture hall at Hong Kong University. Uh, we could have picked a bigger lecture hall, uh, because we have never seen such a quick and massive response after we sent out only one email about this event. Within two hours, we had more than 1,200 people sign up for this event. If we let it last for two more days, I bet we'll have more than 100,000 people sign up for this event. And then we'll have to rent the new Kiteak Sports Stadium for you. Uh, but anyhow, you know, welcome to Hong Kong University. Uh, so glad to have this opportunity to speak with you. Uh, so today's topic is very timely and it's a grand topic. I know you just rushed in from another event. So I'm going to give you a soft start to talk about something that is truly deep in your heart, and that is sports. Uh, everyone knows that you are not only the chairman of Alibaba but also the owner of the Brooklyn Nets. Uh, and most recently, you brought your own team to Macau to compete with Fenus Sun, and I was told that it won, right?

We won one game and lost one game.

Okay. Uh, so I knew the one that your team won. Uh, but my first question to you, which is also very interesting for our audience, is that, you know, when did you get interested in investing in professional sports?

Yeah. And what kind of opportunities do you think the NBA can bring to China?

Uh, Professor Deng, before I, uh, get into the question, I, I first just want to express my, uh, deepest appreciation. I, I feel extremely honored to be able to be on this stage. Um, I'm no Jack Ma. Uh, so, uh, but, uh, to have this opportunity to, uh, share ideas. When, when you guys approached me, uh, this is a lecture series, and I said I didn't want to stand up on the podium to lecture people. Uh, I would prefer to do a fireside chat format so that we could sort of exchange ideas and, uh, in honor of, uh, Professor Chen. And, uh, so I look forward to, you know, this exchange and also a little, I understand there's a little bit of Q&A later on with the students, uh, in the audience, so I really look forward to that.

So, um, thank you very much. Thank you. Uh, yeah, so, uh, the NBA has been in China for a long time. They've actually, uh, played games in China for many, many years. Uh, and then there was a hiatus after 2019. Um, this year was the first time in six years that the, uh, NBA brought two teams, two NBA teams, one of them is mine, the Brooklyn Nets, to play in the Chinese territory. And, uh, they chose to play in Macau. Uh, they have a deal with the Macau Sands organization to play in Macau for the next five years. But part of the deal is that there's a chance for the NBA to also opt to play in mainland China. So at some point, I expect that in the not too distant future, the NBA will be back in mainland China. And, uh, from the NBA's perspective, the logic is very clear. China has the probably the largest basketball fan base in the world, and everybody follows the NBA. Why is that? Because the NBA is the league where the best players in the world play. Uh, about 30% of the NBA's players are non-American. They come from all over the world. They come from, uh, Europe, Eastern Europe, Australia. Not many Asian players, but of course, we hope that in the future, China would develop its basketball program and we can see another Yao Ming in the NBA. So the fan base is huge in, uh, in in in in China. So it makes a lot of sense for the NBA to come back to China and play games so that the players can interact in person with the fan base. And, uh, and of course, during all these years, the NBA's games are always broadcast in China, um, through, uh, Central Television and also on streaming media. Uh, from China's perspective, it's equally as important for China to be engaged to the rest of the world and to bring the best part of sports and other aspects of culture from around the world to China to interact with the fan base in China.

And, uh, so, so this time, we got a huge, very warm welcome from, uh, from the China side of things. And, uh, because the NBA is so popular and the games are a huge success, and we actually gave the fans a very, very good showing in terms of the competitive level. One game went into overtime. The other game was, I think we actually won, we lost the overtime game, but we won the game by like three points the second night. So, it was a great experience, and I'm just very positive about, uh, this kind of cultural exchange and sporting exchange. Uh, I just wanted to mention this idea of using sports to bring cultures together is very, very important. Uh, a big part of my philanthropy in China is all about sports, investing in sports as part of education. And I have a program to bring middle school kids, eighth graders that are about to go into the ninth grade, for them to send them to the United States for high school, four years of high school to play basketball, but more importantly, to get an education in the US. There's a little bit of, uh, replicating my own experience because I, when I was young, I left Taiwan when I was 13 years old, and then I went to the US for boarding school and university and so on. And, uh, this program has, uh, is actually both developing the next generation of basketball talent in China, but also giving the kids an opportunity to see what's outside. And also, I think the biggest beneficiaries are the high school kids in the US. The Americans, they see these kids coming from China. They've all read about China, but they don't know, they haven't interacted with people, individuals. And, uh, we select the best of the best, both from an academic standpoint and also basketball skills standpoint, and they come into the US environment, and they become part of the community, and they're well-loved in the community. So this is great. This kind of people-to-people exchange is so important. Uh, and I believe, uh, you know, if, if I have the resource and ability to do that, I will always support that program.

Great. So how many kids can get your scholarship to go to the US?

It's very selective, competitive. So every year, we select between six to eight kids.

Oh, okay. Those are really the best.

Yeah.

Yeah. I was hoping that my nine-year-old son would have a chance, but I guess it's too challenging.

We can always try. You, you're holding them back.

Okay, great. Yeah, very encouraging. Um, so great. Well, I didn't know about the philanthropy part of your sports business, but, you know, I hope that you can keep bringing your team to China.

Yeah.

Uh, to show us the best of the professional basketball in the world, right? Uh, so my second question before we really get to the grand topic is about Alibaba. Uh, you know, uh, you know, your friend Jack Ma came here in 2008, and obviously, you may still remember in 2008 what Alibaba was. But my understanding is, you know, in the last 26 years, Alibaba was transformed from a pretty simple B2B e-commerce company to today, one of the largest AI plus cloud computing company. Could you, could you share with us a little bit about, you know, how Alibaba has been so transformative and, you know, what are sort of the secret sauce of Alibaba that managed to turn itself into different kinds of companies every five to 10 years?

Yeah, just a little bit of historical context. When I joined Alibaba in 1999, China's GDP per capita was $800, and today it's $13,000. The growth has been tremendous. And I always tell my friends that I'm in a very fortunate position because I lived through the confluence of the rise of China as a manufacturing power and the economy of China rising, and the advent of the internet, you know, the growth driven by the internet. And sort of sitting at the intersection of that, I was able to, you know, from the Alibaba vantage point, witness this, uh, sort of dual engine growth. It was quite tremendous. And, uh, Alibaba's original idea, like you said, is a B2B website, because we, Jack thought that he wanted to use the internet to level the playing field for all the small businesses in China, trading companies, small manufacturers, which, if you recall, Paul, before the WTO, China entered the WTO in 2001. But before that, international trade had to be done through state-owned trading companies. But once China entered the WTO, it opened up trade, and that was the beginning of China's development as a manufacturing base. Because people started to set up factories. They could see opportunities to trade using the internet to trade with the rest of the world. So Alibaba's inception was a business-to-business website. We sold things or we helped small businesses sell things wholesale. And, and by the way, Alibaba's first website was in English language for, you know, because we, it was facing to buyers around the world, right? It was an outside-facing website.

Um, and then we evolved from B2B commerce to consumer commerce, which became the largest consumer shopping platform, Taobao, today. Uh, we also developed payment because there was a pain point. Buyers and sellers didn't trust each other. Buyers didn't want to pay first, and sellers didn't want to ship the product. So we invented a thing called Alipay, which in its original form was an escrow system to allow the trade to happen. And then we got involved in logistics and so on and so forth. And you ask about the secret sauce. I think the secret sauce is that a company, a good company, always develops when they follow customer needs and customer demands. We, we, we basically follow what our customers wanted, and we developed everything organically.

Um, I would always, uh, you know, if you, uh, people in the audience here, the students, later on, you will go out and found companies, you would always want to favor organic development over acquisitions. Now, of course, we've also made some acquisitions. Some of them are successful, and some of them failed spectacularly. But always favor the organic development because it's, it, because you're developing it through your team, and your team has the best DNA in terms of the Alibaba culture and innovation.

So, uh, that's how we sort of evolved. And then the reason we got into the cloud computing business was also to service our own need. It's not because someone decided, "Oh, cloud is a good business, we should, you know, it's a good industry to be in," and we went into it. That's not the case. We developed the cloud business 16 years ago. 16 years ago, nobody was talking about cloud computing, and we said we were looking at all the data we were managing, and the consumer platform was handling massive amounts of transactions, and our CTO came to us and said, "If we continue to use third-party software and hardware," you know, we were using servers from Dell and IBM, storage devices from EMC, database software from Oracle. "If we continue to use that, we will later on hand over all of our profits to these technology vendors." So we developed cloud computing really out of necessity, out of the need to become self-reliant in technology, which is later on we'll talk about that as a sort of national thing. And, uh, so we, uh, develop, we had a team that, uh, focused on that development of an operating software. Not, you know, when you think about operating software, you think about a single computer, but this is an operating software that worked across data centers, worked across multiple computers. And, uh, why? Because we need to do parallel compute in order to manage the large amount of data that we have. That's the genesis of our cloud business. We really ate our own dog food, right, and used it, the technology ourselves, and then later on, we decided, "Why don't we? This technology is so good, why don't we open it up to third-party customers?" And that's how we went into the cloud business.

So, I'm going to come back to the open-source strategy. And we had a conversation last week about this. But today's theme is broad and deep, and it is obviously very, very important. Let me give a short introduction about, you know, why we picked this topic. Last week, when we had a conversation, the first thing that Joe told me is, you know, "I'm not a good trade or macroeconomist." But you got a degree from Yale, major in economics. Uh, so I don't know how that can be. And, you know, very quickly, you convinced me that you're actually a very smart and, you know, astute, you know, economist, you know, may not be a macroeconomist. And then I explained to him that, you know, Edward Chen is, you know, one of the most influential economists and trained so many generations of great students who have become very successful in the private sector and also in the government. So I said, you know, we don't have a lot of leeway to adjust the theme. It has to be about China's economic growth. So we added the technological drivers, you know, knowing that you invest a lot in technologies, and obviously, you know, Alibaba has been doing great on that front. Why 10 years, right? You know, in 10 years, 2035, the Communist Party, the Chinese government, has targeted that to be the year to turn China into a middle-level developed economy. What does it mean? I actually don't know. But, you know, just imagine that, you know, we need China to have a GDP per capita around $30,000 US, which is possible. And interestingly, you know, between the meeting we had last week and today, the Premier of China, Li Qiang, gave a speech in Shanghai saying that in five years, 2030, China should have around 24 trillion US dollars in GDP. So what does it mean? It means that from now, which is around 20 trillion US dollars GDP, to grow to 24 trillion, and you are calculating the math in your head right now, I can tell. So that needs around 5-plus% nominal GDP growth, which is not impossible, right? So suppose you have 4% real GDP growth plus 1 or 2% inflation, then you will get it in five years. So it's not a dream, it's totally feasible. But to have 4% real GDP growth, we need a lot of innovation, and the innovation needs to be turned into productivity growth. So here comes the general question for you. Okay. What are the key or influential features in China's national tech plans that you think will guarantee that kind of success in the next five years or in the next 10 years?

Yeah. Well, well, I think this is a very topical question, uh, because China just published the 15th Five-Year Plan from the Central Committee. And, uh, I think some of you might have read the whole plan. Um, I read a summary of it. But there are really two major takeaways from the Five-Year Plan. Number one, China wants to continue to be a manufacturing powerhouse. Uh, I think the emphasis on the manufacturing economy, which is part of the real economy, is right there. That's what the leadership in China has clearly stated. This is where we want to be. Um, you know, you compare China to the rest of the world, consumption is actually a very small percentage of GDP, less than 40%. Whereas in the United States, consumption is 70% of GDP, right? So China is actually making things. China is looking at GDP growth from production and to an extent exporting that production to the rest of the world. Because China is, I believe today and 10, 20 years from now, China will continue to be the manufacturing base for to supply the rest of the world.

Um, so that's, that's number one. Number two, the plan says we want to become technology self-reliant. Um, I think this is very much both a foresight of the leadership as well as a reaction to what's going on with geopolitics, where the United States and some of the European countries are restricting critical technology from China. So China believes that we have to develop our own technology, which is China is already today very much well on the path of doing that.

Um, now, going back to the first goal of maintaining a manufacturing base, if you look at the history of China, how China has become a wealthy country, I said $800 GDP per capita to $13,000 today, and we'll get to $30,000, you know, in the next 10 years, the path of wealth creation has been in production and making things and supplying that to the rest of the world. And I actually think that this is, but but there's a lot of criticism around that. They say, "Oh, China has excess capacity. They're exporting excess capacity to the rest of the world," as though that's a terrible thing. Well, if you think about it, did everybody criticize the German car industry for having excess capacity when Germans exported all their cars? I mean, definitionally, excess capacity simply means you have production capacity that your domestic economy cannot absorb. Therefore, you resort to exports. But the use of the word "excess" seems to be like a dirty word, but it's not. It shouldn't be, because how a country goes, gets, becomes wealthy is to make things and collect money from the rest of the world to make their own citizens wealthy. And I, and I truly believe that continuing on this path of being a manufacturing center for the world, and now high-tech manufacturing, not making shoes or t-shirts, if we continue on that path, China will continue to grow its economy, and the citizens will continue to gain wealth and gain disposable income, and at some point, consumption will come. You know, today, we, through the Alibaba platform, we see a lot of consumption. You know, there, I give you a data point. There are something like 56 million, there are 56 million people on our platform that are spending more than $6,000 US per year on Taobao. Okay? That's way more than the average disposable income of Chinese citizens. But we already have the scale that many people that are spending that that amount of money. So at some point, consumption will come. But I think the leadership in China understands the foundation to a healthy economy, growth, and wealth creation stands with having a strong manufacturing base, and today it's high-tech manufacturing. So, China is the best in the world when it comes to making electric vehicles, batteries, solar panels, and, you know, all those things that the rest of the world needs.

So, everyone talks about AI, and obviously China has been investing a lot in AI, and the DeepSeek moment has really shocked the world. And I guess a more general question about the national tech agenda in China is again, you know, I asked you the secret sauce question for Alibaba, now I'm going to ask you the secret sauce question for China's technological policy. How did they do it? Right? I mean, you know, there were export controls by foreign companies, foreign countries, and China, just 10 years ago, was, you know, really doing simple manufacturing. And now, as you said, advanced manufacturing with different aspects of AI that appear to be competitive and even challenging to the US in terms of their technological leadership. So could you, I mean, may I push the question a little bit forward to ask you to focus a little bit on AI, and, you know, what are sort of the secret sauce of the national policies that promote that kind of growth?

Well, uh, obviously when you talk about national policy, China, uh, the government has identified areas for investment, for example, in semiconductors, in semiconductor manufacturing process, in equipment that makes semiconductors, all that. I think that's all good. But the part that I focus on, that I really thought was very interesting, is a couple of months ago, the State Council came up with a, uh, a sort of AI plan. And Chinese people are very practical. It's very goal-oriented. The AI plan simply said, by, uh, 2030, which is five years from now, we should see 90% penetration of AI agents and devices. That's what the State Council said. So they basically said, "Here's the goal. We'll let the market figure it out." Whether the market is state-owned enterprises or private entrepreneurs, they will figure out how to proliferate and make high penetration of AI in China. And I think that's a great policy because all of us, as we are, we are all part of sort of the so-called AI race, right? The race between China and US AI. Uh, at the end of the day, you don't keep score by looking at, you know, how good these large language models are. The score is being kept by the adoption rate. The more people that adopt AI, the more society will benefit. Uh, so China's whole approach is the proliferation of AI, and I think that's a great policy.

Mhm. So I remember I talked to you last week about the uniqueness of China's AI ecosystem. And then you talked a lot about, you know, the talent pool, the infrastructure, the fact that China has advanced manufacturing while a lot of advanced economies don't have today, as well as, you know, the ability to generate energy efficiently. So could you share with us, you know, with the audience, about the comparative advantage of China in terms of, you know, becoming an AI superpower?

Yeah. Uh, yeah. So right now, I think the way Americans want to define who's winning the AI race is purely by looking at how good the large language model is. So one day it's OpenAI, the next day it's Anthropic. And then, you know, the Alibaba Qwen model becomes, by the way, the Alibaba Qwen model just won a, like a two-week contest of trading cryptocurrencies and stocks.

Wow.

Uh, they asked something like 10 different models, you know, American models and Chinese models. The Alibaba model actually beat, became the winner of the whole thing, and DeepSeek is second. Um, by the way, huge amount of respect for DeepSeek, our neighbor in Hangzhou. They're doing incredible work. So, um, if you compare, so, you know, we don't look at the AI race according to the American definition. We look at the entire stack of whether where China has the advantage. You start with energy. Uh, China has an advantage in electricity generation, and that's because 15 years ago, the government had the foresight to invest massively in energy transmission. When you generate electricity in the north, it has to be somehow, it has to be transported to the south, right? And when you generate electricity, especially in clean energy where there's sun, there's wind, there's water, not necessarily is where they need the electricity, so it has to be transmitted to somewhere else. So the State Grid in China, there are two grids, right? There's a north, north and south. They make $90 billion of capex annually. The United States, $30 billion only. So the United States is massively underinvesting in electricity transmission. And, but China has been doing this for the last 15 years.

Uh, so, and the result of that is China's installed base of electricity generation capacity is 2.6 times that of the United States. And even better, the net additions to capacity that China is putting in is nine times that of the United States. So, so, so China's growth in electricity capacity is much, much faster than what's going on in the US. And most of the net ad increase is in clean energy, solar power.

Okay. Uh, the whole, the end result of all of this is that China's electricity, on a per kilowatt hour basis, is about 40% cheaper than that of the United States. So China has an energy advantage in AI because, you know, when you burn all these GPUs, train large language models, and run inference, you're burning energy, lots of energy. The big difference between machines is machines eat a lot of energy, but the brain operates on very low energy.

Um, so, so that's the one thing. And then we look at how much it costs to build a data center. So, it's 60% cheaper to build data centers in China. Um, this is before you buy the chips, the cheap GPUs. And, uh, and then you look at the model development. I, you know, actually think that the Chinese models are not very far behind the United States.

Uh, and there's a reason for that. China has a lot of engineers, and it's the country that produced the most STEM students every year. And, uh, training, you would think that developing AI and training models is a very sort of high-level research type exercise, but a lot of the work is actually in the engineering. You have to work on the system to make the system very efficient in training the model with hundreds of billions of parameters, even a trillion parameters. If the system is not efficient, it will cost you a lot of GPU resources. So China, being lacking in GPUs, actually creates an advantage of starvation. When you don't have a lot of resources, you are forced to innovate at the systems level, and this is where China is strong, and you know, lots of engineers, talent globally. So, very interesting thing, globally, almost half of the AI scientists and researchers have had a degree from a Chinese university.

Globally?

Globally, whether they work in US companies or they work in Chinese companies or anywhere globally. So what that means is, you go to a company in the US, uh, many of them are ethnic Chinese, and, you know, and that's very, and I just recently saw a social media post, someone working at Meta, which is Facebook, is complaining that his, this is not a non-Chinese person, he's complaining that the AI team that he's working in, everybody is speaking Chinese, and they're sharing ideas in Chinese, he doesn't understand.

But they're so smart in creating all these AI tools. They should be able to real-time translate Chinese into any languages.

Yeah. But still, you know, in a sort of water cooler conversation where you sit down in the cafeteria, it's like it's hard to, you know, capture everything, right? So, I mean, so what that means is a lot of the idea sharing and exchange is happening in Chinese globally in AI. This is the first time Chinese language is an advantage. It has, it had been a disadvantage for Chinese companies to expand overseas because when Alibaba goes to open up an office in Italy or in Japan or in the US, the people that we hire locally, they can't speak Chinese, so they, so they speak English. So our people sitting in Hangzhou have to communicate to them in our second language, which is not ideal. And, and I think that's a huge hindrance for Chinese companies who expand overseas. But now, knowing Chinese has become an advantage in the AI world, and that's very, very interesting, right? So anyway, I've just listed a number of these sort of advantages that China has. But the biggest advantage is that I believe the approach that Chinese companies are taking toward the large language models, which is open-source, will accelerate the adoption of AI and will make, will really make the proliferation, really realize the proliferation of AI that would benefit broader society.

Okay. And, uh, uh, the reason open-source is so important is that it is cheap. It actually doesn't cost anything to use open-source models. Alibaba has our version of, we publish many, many versions in open-source, and we're available in all the open-source marketplaces in the United States, around the world. People can just take our model, download it, and put it on their infrastructure or put it on their notebook computer and start running AI at no cost.

Um, so, so the open-source approach is helping the proliferation of AI, whereas in the United States, if you want to use AI, you got to pay OpenAI a lot of money to use AI. So the, I think that's ultimately the advantage of China, because the winner is not about who has the best model. The winner is about who could use it the best in their own industries, in their own lives. And that's going to be in China.

So what is the fundamental reason behind the differences between, you know, the Chinese AI model that emphasizes on open source and the US model that is more private, closed source with data, and, you know, all these models that are sold on market price? I mean, is there a significant difference between, you know, the way that companies compete in different countries, or are there incentives again from the government that encourage them to be, you know, more generous about, you know, their resources?

Okay. Well, let's say, I'll give you an example. Uh, take, uh, some a Middle Eastern country, let's say people in Saudi Arabia. They say, "Well, we want to develop AI, and we want our AI to be sovereign," meaning that it's solidly developed AI. But of course, most countries in the world don't have the actual talent to develop their own sovereign AI. So if they're choosing between using OpenAI through an API or just taking the Alibaba open-source model, just taking that and developing on top of it, I think the cost-benefit is clearly in favor of open-source. And there's also another reason, data privacy. If you are using OpenAI and doing further training on the model, you're feeding your data into an API. You have no idea, it's a black hole. You have no idea where that data is going. Whereas if you work with open-source AI, you can better control data privacy, and you could set up your own private cloud to store your data. And, so, so that, so globally, as you know, both public like governments and also private enterprises look at which AI I should adopt, I think they will lean toward developing open-source AI or developing on top of open-source AI.

Certainly. But, uh, let's take Alibaba as an example. How do you guys make money by being so generous, right? Allowing people to use your open-source AI? You must be making money somewhere else, right?

Yeah. So that is a great question. And so we don't make money from AI. That's the answer. But no, no, we, we, we remember we run a cloud computing business. So when you run models, you need to have cloud infrastructure. And it's a very sophisticated infrastructure. It's not, it's not something that any company can just hire a few engineers to build. Uh, you need both the expertise in that infrastructure of running AI and also the scale. Uh, because this is a scale game. With, just like individually, we don't build our own hotels. You go stay, rent a hotel, you go stay in a hotel because the hotel operators have scale. Same thing as the data center business, the cloud business. It's all about aggregating infrastructures, and as you have many, many customers, you have that operating leverage to lower the unit econ, unit cost of serving your customers. So through our cloud service, if people are running AI and they happen to want to use Alibaba Cloud, we have a whole suite of products from storage to data management to security to networking to containers, which is a term that I really don't understand anyway. I'll just say it. Um, and, uh, so, so all these suite of products will help you run your AI more efficiently on our infrastructure, and that's how we monetize.

Great. So, so my last question before I turn to the Q&A from the iPad, by the way, sorry, is, uh, there are a lot of students here. In fact, 80% of the audience are students, ranging from undergrads all the way to PhDs. Um, and Joe told me he's very excited about seeing so many students because he's used to seeing, you know, government officials and businessmen, investors, and, you know, students, you know, not, you know, some people who he commonly see. So he's very happy to provide advice. So what kind of skills do you think young people should get in preparation for the AI era, or, you know, what majors should they specialize in?

Yeah, I think those are two different questions, like skill set and expertise in a subject matter. There's those are two slightly different questions. Uh, from a skill set standpoint, I still think you should learn, number one, how to acquire knowledge, and number two, develop an analytical framework for analyzing information, coming to your own conclusions, right? And a number of things that you could do to help you do that. There's no one lesson or one thing that helps you with improving your analytical capabilities. Um, uh, for example, I, I always still tell people that they should learn some kind of computer code. It's like learning a foreign language. A foreign language is, you know, you learn to communicate, you know, let's say in Spanish with someone in Spain, French with someone in France. A computer language is you're communicating with a machine. You're telling the machine what you're instructing the machine what to do, and there's a lot of logic behind, you know, that language, how do you construct the right instruction to tell the machine to do the right thing, and that process itself is a thinking process. So I still advise kids to learn coding, even though today with all these no-code tools, you actually don't need to learn computer code. You just use natural language to tell the tool how to write. The purpose is not to actually, you know, operate a machine. The purpose is going through that thinking process. Uh, I come from a legal and finance background. In finance, what do people use? Spreadsheets. I actually learn, I tell my kids, you should learn how to work a spreadsheet because constructing a formula in a spreadsheet and make it work. You just type in one number, and it just, you know, the number just sort of calculates itself, the formula calculates, and then you have the results. It's a beautiful thing, and if you, if you know how to work a really good spreadsheet, that's a, that's a thing, you know, you're going through that thinking process. So skill set-wise, I think learn how to acquire knowledge, learn how to analyze and think. Um, and also an important

The skill is to ask the right questions. Um, so, um, uh, that's one thing. The other, the other is sort of subject matter. Um, uh, I, I, I, I have been telling kids, young people, uh, two subject matters that they should study. Uh, one is data science. Uh, it's a fancy term for statistics. Used to be called statistics. Now people call it data science. Uh, because in the future, we're going to see a data explosion. The more digitized the world, uh, the more data, uh, uh, you will acquire or the company will acquire, and understanding how to manage that, uh, and analyze data is very important.

Now, having done the data side, you wanted to touch upon the human side of things. So, study of psychology is important. Uh, psychology and biology helps you understand how the human brain works. I still think, as I said, it is still the most efficient, energy-efficient machine there is, and understanding how the brain works is quite important.

>> Uh, a third thing is, uh, just it just came up, uh, uh, I think a lot of kids today are, uh, not learning computer science, but instead, they're learning, uh, material science. Uh, in the future, you know, it's the world is, you know, you is being dominated by bits, but in the future, what makes the bits move faster is going to be atoms. Uh, you know, understanding how the atoms work is, is going to be, uh, quite important. You know, people make semiconductors, there's going to be a lot of innovation in the semiconductor, uh, space. So, uh, uh, I think material science will be an interesting, uh, thing to learn.

>> Great. Uh, basically material science, cognitive science, data science, and we still need to learn how to code, not because we are needed, but we need to have logic, uh, in order to understand what AI is doing.

>> Right.

>> To us. Uh, so I think that's a very good set of, uh, recommendations.

>> Uh, so Joe actually has a very tight schedule, and I know there are over a thousand people here. Uh, so today, we have a very special arrangement. Uh, there was a QR code, uh, for some of you, uh, to scan to ask questions, but it may be already too late because I already received 10 questions here. Uh, so, uh, you don't need to come out to the microphone because there's none. Uh, so I'm just, I'm just going to pick the best questions. Uh, some of them are, you know, a bit, uh, interesting, but don't blame me for asking them. Uh, if you don't feel comfortable, don't answer them. But I'm pretty sure you have a way to deal with it. Uh, so, uh, first, uh, a little bit of promotion. Joe, do you know, uh, we actually have a John's degree, uh, with Alibaba Cloud Computing? Um, so it's not a degree, sorry, it's a course, but you can get credit, uh, in order to get a degree. Uh, thank you very much for Alibaba's support. Uh, there's a student from that course who asked a question. Alibaba Group has been a driver of changes across industries. What would be the next big change driven by cloud computing that would influence, influence people's behavior and businesses?

So, I, you know, we see cloud computing as a utility, and it is like electricity. It's powering, uh, different activities, different technologies. Uh, and the hottest area in cloud computing is obviously AI, because cloud is powering, uh, the usage, uh, both the training of AI models, but also the usage, which is the applications, the inferencing of AI.

Um, so I'll, I'll mention probably the next sort of big transformation in, in AI is when people start to use AI not as just a tool, but as a friend. Uh, you're, uh, right now, AI seems to be more of a tool. Uh, we, we all want to use it to make ourselves more efficient, our company more efficient. AI is already helping us to code, you know, so we don't have to have as many software engineers. Um, but when does AI become sort of your companion? Uh, that's when most, you know, what, what if most people start to see AI just like it's another human being? That's going to really transform the world. It's going to transform behavior. Uh, sometimes it's scary to think about that. Um, but we, uh, I see that happening.

>> So it's called ASI, like artificial super intelligence. And this is something that >> Or, or AGI, artificial general intelligence, when AI, you know, the, the traditional Turing test, the AI is behaving or acting in a certain way that you can't tell if it's a human being or not.

>> Yeah. Uh, right? You can't tell. You, you, so it, it, uh, when you're interacting with it, when you're doing a back and forth interaction, uh, AI is coming up with answers just like it's your friend.

>> Uh, that is both exciting, but also kind of scary.

>> Okay. So the second question is very interesting, and I wanted to ask this question, but the theme was set by, you know, the committee led by Professor Chen. But this question, which is a career advice question, many students and some mid-career people like me, uh, have been thinking about starting a business or joining a startup. Uh, in the late 90s, uh, you had a very good job, I was told, in Hong Kong, and then you went to HJO, you met, you know, then your co-founder Jack Ma. Why did you decide to give up a pretty lucrative salary to join a startup that may or may not have such a bright future? You know, what determined, uh, your decision? And, you know, for people who want to join a startup, you know, what should be the right moment and what are the critical, uh, considerations that they should have?

>> Um, when, when young people, or, or even old people like me, make decisions, we're assessing risk and upside. Uh, if you make a decision and things don't go your way, you're taking a risk. But if things go well, uh, then what is the upside? So you can pretty much, I mean, it's not exactly a mathematical thing, but you can pretty much assess the, the downside and the upside. When I joined Alibaba, I thought that the downside risk was very limited. Why? Because I have a, a good university degree. I went to law school. I have a law degree, and worst comes to worst, I can always work as a lawyer. Uh, so the downside is limited, but the upside is, you know, you can't imagine it's unlimited. And, and so I was facing an asymmetrical risk situation. Just, uh, the finance students here, it's just like a call option, right? You know, so, um, so the decision is very easy for me. Asymmetrical risk-reward, and you always wanted to, uh, find those asymmetrical risk-reward situations. But I think, uh, if you really try hard to find it, you may not be able to find it. The opportunities come to you. So the most important thing for the young people here is preparedness. You have to be prepared to seize that opportunity when it comes along. You don't know when it's going to come along.

>> Yeah. So this question is about whether AI is the next internet bubble. You know, we have gone through, you know, the early 2000 bubble booming and then burst. Uh, and, you know, if you pay attention to the stock prices of the Mic 7, they have been rising like crazy, and I regretted so much, uh, for selling my Nvidia stocks too early. Uh, so, you know, we are not asking for stock market tips. Uh, but do you think there's a bubble? And if it is not, why do you think this time is different?

>> Yeah. Well, there's a, there's a, is it a, there's really two, I, two concepts of a bubble. There's a real bubble, and then there's a financial market bubble. Uh, I have no idea whether there is a financial market bubble. What? Because valuation of stocks is kind of an art, you know. Uh, you, you have to, even though it's very, you know, there are established theories on how you value a stock, that it's, uh, you can assign a stock a 50 times P multiple because you think the growth rate is very, very high. Does that make sense? I don't know. Uh, there may be a financial market bubble relating to AI, but the AI phenomenon is real. So all the infrastructure people are building, uh, all the development, uh, resources that go into models, it's not going to go to waste because it's a real phenomenon. Mhm.

>> Uh, just like the internet, in two, in the year 2000, around March, there was an internet bubble burst bursting. It was a stock market, uh, bubble bursting, but the internet today, the internet is here. In fact, the internet is even stronger today, right? So, uh, so the, so the technology itself is not a bubble.

>> So this question is very interesting. You know, our students are read this part, you know, they ask more interesting questions than, uh, so about management style in, um, you know, managing different types of companies, right? So you have your professional sports investment, I don't know how involved you are in managing your basketball teams, and also a lacrosse team, and also managing a tech company. What are the similarities between managing the two different types of companies, and what are the dissimilarities? And how important is it to build a team and a corporate culture? So I guess it's a very broad question about leadership, management, in at least two very different sectors that you have businesses in.

>> Yeah.

>> Yeah. Um, when, when I bought the, uh, Brooklyn Nets, the NBA, people try to give me unsolicited advice. They say, "Oh, you know, professional sports is totally different. It, it's, you know, you, you're used to business managing a company, but in pro sports, there are stars. It takes a different kind of approach to manage, uh, a professional sports team, and Joe, you really don't understand how it works, so you have to entrust it to the people." And then I found out that the people that are involved in the sports world, uh, they don't know anything. All they know is, all they have relationships, they have thick rolodex, so they know who to call. They have relationships with the players' agents and, you know, all that. Uh, now, what I'm seeing is managing a sports team, the, the philosophies are converging, uh, between, uh, the business world and the professional sports world when it comes to good management. Number one, you have to pick good people. Uh, so in my, uh, Brooklyn Nets organization, I have a, a very good general manager that manages the basketball aspects. So which players to sign, trades, draft picks, and things like that. That's the basketball part. And then I have a CEO that manages the business part. That's selling tickets, selling sponsorships, marketing, fan base development, things like that. Uh, same thing. I mean, you know, just like in, in, in a business, uh, you really have to rely on people, and you really need to, uh, find people that are better, more skilled, more talented, and smarter than you are. Uh, otherwise, you become the bottleneck to the growth of the organization. Uh, so in basketball, I am not an expert in basketball, right? Uh, much less an expert in playing basketball. But so, so there are a lot, you know, you want to find the most expert people, and then develop that trust with your management team.

>> So basically, a visionary leader that motivates the team to move in the same direction, at least, uh, for a long time. Uh, how about compensation? Do you have to pay your employees at Alibaba as much as you pay your NBA players?

>> Yes. So.

>> Yeah, I mean, look, it, it is, uh, uh, uh, you know, the, the, uh, this is what I worry about is how do, how do we, uh, retain talent? Good people, they're always in demand. There's always going to be competitors that will be calling them. So, uh, the developing a compensation, uh, philosophy, and also, you have to customize a lot of the compensation when, when it comes to, you know, very senior talent in the company. Um, it's, uh, I see my job as, uh, because every time, you know, we have a comp, compensation committee off the board that's independent directors, but the independent directors are not very familiar with the operations of the company and with individuals in the company. So my job is to communicate how important our team is to our independent board and the comp committee, so that I can convince them to pay them a lot of money because they're worth it.

>> Great. Uh, so we have a few minutes left. Uh, I guess let me ask you an easy question for you, and, you know, in two minutes, can you tell us a little bit about what's Alibaba's AI strategy? What are you guys focusing on right now, and what's the next step, without revealing too much trade secret, obviously?

>> No, our, our AI strategy is very simple. Uh, number one, we do both large language model and cloud, so that, uh, we can make money, uh, on the cloud piece, on inf, providing the infrastructure, uh, for, for AI and for the digital age. Uh, and then on the model, we open source it so that more people adopt it. It's pretty simple. That's the strategy.

>> Well, how do you know it's so simple? I wish, uh, you know, I know how to run Alibaba. Um, and you guys are really the dominant player, uh, in that field, although you didn't say that. Uh, I would like to conclude, but usually, uh, for the tradition of this, uh, lecture series, I will invite Professor Edward Chen to give a concluding remark. Um, and, uh, thank you, Mr. Joe Chai, and Professor Tang. And please remain seated on stage.

>> Thank you. Um, thank you very much, Mr. Chai, for coming to honor this occasion. Uh, your presentation was so clear. Actually, it needs no summary. But my students may not be happy with it. They told me if you don't make a summary, they may not want to continue the lecture series. So I had better, uh, try my very best to sum up, uh, what you have said. Now, even you have a lot of insights, even from the preamble questions, I learned a lot. That is, I learned when you do things, don't just consider private benefits, social and public benefits are important. Like you invest in basketball games, it's a cultural exchange, you know, underpinning the whole business. When you start Alibaba, it's not only just making money, but the e-commerce B2B platform will also facilitate the small-scale, you know, merchants' business. So it, it, it's really, you know, the story of success is not only yourself, but also the private, not only, but also the public benefits. But the subject of today is technological drivers for China's economic growth in the coming 10 years. There was no explicit question, uh, anyway, but implicit in the dialogue, it is very simple. The major, single most important driver, technological or financial or economic, must be AI. That is the driver for China's economic growth in the coming 10 years or even longer. From the dialogue, I understand that there are four major factors, factors to account for the success of China's AI development. The first factor is a very determined national strategy, top-down, right? There's a very clear-cut objective, for example, in five years' time, 90% proliferation of AI in China. And besides investing in infrastructure, also inspiring private companies to do R&D. So that's the first one is national strategy. The second factor is electricity. Electricity, the foresight of China in providing ample supply of electricity is very important. Now, no wonder in the past two days, I was involved attending the, uh, financial, the Global Financial Leaders Summit. The fund managers told us, don't just eye your investment in AI companies, you should buy more energy company shares. So that is the tips, and that echoes exactly what Mr. Chai said today. So the second factor is the foresight of China in the provision of electricity. The third factor accounting for China's success is the supply of engineers, and at the system level, engineers are very important in AI development. When I was young, in the old days, people told me in America, if you have a problem, the first thing you think of is to find a lawyer. You were a lawyer before. But in Japan, when you have a problem, the first thing that you think of would be engineers.

>> Right?

>> Now it's not Japan, but China. So when we have a problem, we think of engineers. So the third factor is the supply of engineers. The last factor, the fourth factor for China's success is the open-source language model adopted by most of China's AI firms, including, of course, Alibaba. This open-source language model is very important in my view, uh, to promote the further development of AI, because the open-source system enables other people to modify, to improve on your model, and therefore speeding up AI development. But also, if you adopt the o AI, open, uh, source model, you also speed up the proliferation of AI into the whole population. So these are the four major factors, if I understand, accounting for China's success. So China has a very bright future in AI, and I'm sure in a, in a not too long future, China will overtake the United States in AI development. I hope that is your conclusion.

>> Thank you. Thank you.

>> Thank you, Professor Chen. Please remain on stage for souvenir presentation and some group photos.

>> Now, may we invite Mr. Tai to receive the souvenir and take a photo with Professor Chen, please. Mr. Tai, please. Thank you, Mr. Tai and Professor Chen. May we now also invite Dean Thai, Professor Tang, and the executive committee members of the Edward K.Y. Chen Distinguished Lecture, including Mr. Hing Wang Bong, Professor Patrick Nip, Professor Bernadette Troy, Mr. Adrien Lee, and Mr. Anthony Lung to take a photo together, please. Heat. Heat. Heat. Heat. This is the end of tonight's lecture. Thank you once again for joining us.

>> Have a great evening and see you all next year.