First of all, President Chen, thank you so much for inviting me. Actually, you invited me several times to come to NTEU, and I was honored every time to come here. But sometimes when I come to Taiwan it's very, very busy, especially around Computex timing it's always very busy. So this is actually a great time that I can visit. And thank you for the warm invitation, and Professor Woo as well. Thank you so much. It's really my pleasure to be here to meet all of you very talented students. You make me feel very old, but hopefully I can give you a few stories for your career.
Maybe I should say my background was in electrical engineering and computer science. So that's where I went to school for bachelor's, master's, and PhD at MIT, and my specialty was semiconductor devices. So when I was a young student, that is what I studied. Now for AMD, I've been in the semiconductor industry for over 30 years, and what you find is that the technology moves so fast. For AMD, I've been with the company since 2012 and CEO since 2014. And probably the most important thing with any company is to decide what do you want to be when you grow up. For AMD, my belief is that our specialty is in high performance computing. And high performance computing is really at the center of all of our lives today. I'd like to say that AMD's technology touches billions of people every day. Whether you're talking about cloud data centers, or anywhere in the edge of the network, or PCs, automotive, or industrial, you probably can touch some of AMD's technology. But from a technology company, the most important thing is you have to have a long-term strategy and roadmap. So our focus was really on three things. First is high performance computing. The second is to have really excellent partnerships. So TSMC is at the center of our partnership overall. And then the third piece is that the semiconductor industry is changing, and many of you have heard that Moore's law is slowing down and changing, and we made a big bet on chiplet technology as a very key area going forward. So these are some of the things that were important for AMD. And today, I'm very happy to say that when you look at the top supercomputers in the world, we have five out of the top 10 supercomputers based on AMD's technology. From that standpoint, I really feel that high performance computing is at the center of what's most important going forward.
I heard that many students still view that chip design is the most exciting thing. I would say that there's always a movement. Sometimes hardware is more exciting, sometimes software is more exciting. I think from my standpoint, the most exciting part of design is actually holistic design. So you have to really design hardware and software and systems together. Especially when we're talking about AI going forward, you cannot design each piece separately. You actually have to think about what is the overall system application, especially thinking about the algorithms and the applications, and then you can think about how you want to design your chips.
The one thing I can say about the AI industry is every week there is new technology and innovation that is coming out. I think DeepSeek was one of those areas when it came out in January. I think there was some surprise. Yes, there was some surprise. And when you look at what they've done, it's actually pretty clever technology in terms of really gathering all of the different innovations using the mixture of expert models and so on and so forth. But the main thing that we saw with DeepSeek is that when you can find a way to make AI more accessible and actually cheaper, you actually will have more usage and application of AI. So the main thing that DeepSeek has done is it really has accelerated the application of AI. Of course, that's not a market statement, that's a technology statement. From everything that we see, the key point about AI is that there's no one-size-fits-all for the computing ecosystem. You have the very large frontier models where the few people who can invest at that level, hundreds of billions of dollars, are going to go as fast as possible because they want to build the best model. But you also find that that is just one application of AI. You also see there will be many different medium-size models, smaller models, and you will see that people will use different algorithms to get there. So my expectation is that there will continue to be a very significant investment, including very large investments as well as more affordable investments going forward. So the most important thing I can say about AI is that the market is huge. We expect that the market over the next three or four years will be $500 billion. And in that type of market, you need all different kinds of computing. There's no one company that has all of the solutions. Actually, my view is that you need every kind of computing: you need CPUs, you need GPUs, you need ASICs, you need FPGAs. And in that framework, I think our AI strategy is number one to have a very complete solution. Complete solution includes hardware, software, and systems. And the second piece is to have an open ecosystem. One of the most important things is to foster collaboration and to have an open ecosystem, and that way people can learn from each other. That was also another important part about DeepSeek: it was an open model, and as a result, many people innovated on top of that. So my answer to your question is the main thing to say is the market is huge, and AI is throughout every aspect of our business, including the largest data centers to even at the PC level. We believe that there will be a lot of AI, so there's a lot of market for all of us.
I think the Taiwan ecosystem is very special. When you look at the Taiwan ecosystem, starting from the TSMC ecosystem, which really has built this incredible manufacturing capability, and then including all of the ODM, OEM ecosystem, manufacturing ecosystem, design ecosystem, and I think more investment on the software and system side will come. From an AMD standpoint, we're very proud of our team here in Taiwan; it's a very important piece of our overall R&D. But the other thing I would say is in this world today, the ecosystems are very interconnected. From a United States standpoint, I think we do rely on a lot of the Taiwan manufacturing ecosystem, and trying to build resilience into that ecosystem is important.
I'm happy to say that I was born in Tainan, and my parents immigrated to the United States. As you can imagine, that was a very big move for them. When we went to the US as a family, the key part that my parents always instilled upon me is that education is so important. For all of you in school, I remember when I was in school at MIT, I very much wanted to finish school. So after my bachelor's degree, I actually thought I should finish school and go to work. And my parents said, 'No, Lisa, you cannot do that.' They strongly, strongly suggested I get a PhD. And at the time I was very impatient. I was like, 'Oh, school is enough. It's enough.' Maybe some of you feel the same way. And the truth is, my parents were right, because what you get from your university and your graduate school is really an opportunity to learn many different things and to build the confidence to really solve the future problems. So even though I was not happy with my parents at the time, I think they were absolutely right.
As the experience to be CEO of AMD, I would say it was kind of my dream job to start from a semiconductor engineer to become a business person and then become a semiconductor leader. But it was not easy, especially in those early years. My parents and family have always been very supportive of that, and I'm very lucky in that way.
My thinking is that there are many different kinds of leaders. We have a lot of respect for all kinds of leaders. But I truly believe that the university education is so helpful. These years that you're in the university is really the best time to learn and to decide what you enjoy the most so that you can decide your next step in your career.
First of all, I have a tremendous respect for Jensen. Tremendous respect. I think as a founder of Nvidia, he has really built an amazing company. I would say that we run independent companies though. Probably as a semiconductor industry, we do have a semiconductor industry association in the US, and all semiconductor companies are there, and together in that forum we would exchange some ideas.
In my experience, I had one piece of probably the best advice that I received from a mentor was to tell me, 'Lisa, whatever you do, I would suggest that you pick the hardest problems.' So the advice they gave me is to run towards problems. And actually, I think that's the best advice that I can give to students, because there's so many interesting things to do in the world. Choosing a project or a problem or a company where you can make a big impact, you will learn so much and be able to contribute so much. And I can say for sure that I learned the most from the biggest mistakes I made. So mistakes are not a bad thing. Mistakes are actually a good thing because you can learn from those lessons and be better in the future.
Political science is not the easiest question. Technology is actually a little easier. I think I would maybe not talk about the individual countries, but I would talk to you a little bit about my thinking on AI, because AI is such a new technology. If you think about the last few years, we're all learning together. Countries are learning, companies are learning, individuals are learning. The initial thought process is AI could be quite dangerous if there are not good guardrails. However, you also don't want to stop innovation. From my standpoint, I think AI is the type of technology where we have to innovate and go as fast as possible and understand that there does have to be regulation, but not too much regulation so that you slow down the progress. So in general, that's my philosophy. I think when you look across the world, people are recognizing it's a very dynamic time. Every week, sometimes every day, something changes. But generally speaking, I think countries that embrace technology are going to really benefit from it. Many countries around the world are all building their AI policies. I think everybody should be educated in AI. It doesn't matter which department you're in. When you say you're in the literature and linguistics department, I think AI can also be very beneficial to understand how to apply AI in your field. Most of what we see today is, as I said, people are still learning very much what you can use AI for in each field. So we talk a lot about the development of AI, but there's also a whole field on the application of AI going forward. So I would certainly encourage all students to do that.
I'm not so sure that I can say that, but I will say that I think Taiwanese Americans and Taiwanese in general are extremely hardworking and really thinking about how to contribute to their fields and their professions. I think that's something that we can be very proud of. Although some people say that I'm more American than Taiwanese, but I'd like to think I'm Taiwanese American.
Probably the most difficult time for AMD was when I started in 2014 time frame. At that time, the company had a roadmap that was not competitive. If you're in a technology company, your product is the most important thing. I would say that's the number one thing. So our goal was to really reframe our product roadmap and ensure that I had three priorities. The first one was to build great products. The second was to have very deep customer relationships, because I think together in this world, there's no one company that has all of the good ideas. Collaboration is very important. And the third is to be very agile and move very quickly. From that standpoint, our biggest job was to give ourselves time to build this great roadmap. And we are now, I would say, our CPU roadmap is based on our Zen technology. We're now on the fifth generation of Zen technology. I can say we went from not the best to today, I feel that we have the best CPU technology in the world, and we have a much broader roadmap going forward. So I think the key in those times is to be very clear about what you're trying to achieve. For us, it was always in a technology company to build great products. That's the number one foundation.
In terms of the semiconductor trends, I think there are a few key trends. I would say we start with the idea that we have to have a very holistic design environment. So hardware, software, systems all need to be optimized together. Probably one of the most exciting parts about AI is we're still in the very early innings. I would say we still have probably 10 years of very significant innovation in AI. And on the application space, we're going to go from today we talk about AI making our businesses more productive or making our people more productive, as we go forward over the next many years, I think we can see much larger changes in terms of what AI can do for us. Probably one of my most exciting areas or most interesting areas is in healthcare and life sciences. I know that there's a medical school here, and the application of AI together with medicine, I think can help us solve things like cure diseases and find new drug therapeutics, also help diagnose future health problems much sooner. So that's just one example of what AI can do going forward.
I would say the following: I would encourage you to be very ambitious in what you would like to achieve. The most important thing for young students or early in your career is you can do anything. So have very big dreams. And if you tell people, tell your colleagues or your managers or your future mentors, people will help you to achieve those opportunities. So that's one of the things I would say, because sometimes Taiwanese or Asian people are sometimes a little shy.
Well, I would say that when you have the right people, the right people are very important because not everyone has the same motivation. Some people are motivated for their project, some people are motivated to start a company, some people may be motivated for other reasons. At AMD, we try to have the right people to build that team. For our engineers, back to this question, when we started, we wanted to build the best. That was our ambition. But we also thought we should be very realistic that you cannot go overnight from not competitive to be the best. So you have to build a plan to do that. And I think that's what we were able to do. But engineers basically love to solve problems. We have to give them good problems to solve. I think we're all motivated by seeing success, and success comes in different ways. Success comes in recognition of the product, success comes in great people wanting to join the company, and yes, success comes in revenue growth, which leads to market share growth, which leads to stock price growth. But my personal opinion is a PhD is actually pretty useful. That's my personal opinion, because you get to work on some problem during your PhD thesis that nobody else is really working on in the world, and that gives you a lot of opportunity to explore much more broadly than sometimes in a company you become much more focused. So I actually think a PhD is pretty useful, but it's different for every person.
You said soft skills. So I would say a few things. One is you really have to think that the world changes very fast. So it's important to be actually quite agile in your thinking. Maybe today you think this is the right path, but you will learn something every day. I have a big philosophy that says you need to continuously learn all the time. Every day you're going to learn something new, and you can decide how you might change your path. That's something that I use very much, and I would suggest that that's an important soft skill. And then to your second question about how do you deal with setbacks, I said earlier you actually learn the most when you have a setback, when you have a failure. I can tell you so many examples of my setbacks, but my advice to you is you can be sad for just a short time. Of course, we're all human beings, so if you have something that you're working on that didn't go the way you wanted, you might be a little bit unhappy, but only for a very short time. And then after that, you learn and you get really focused on your next thing. I think that's the key piece.
I'm just an okay student. Meaning pretty good but not A++, maybe like A minus. I actually think everyone is different. The most important thing is to take whatever you learn and apply it in the real world. So I would say that's what I learned the most. Even my device physics was a very hard class. I don't know if any of you are taking device physics class. I thought the written problem was very hard, but working in the lab on a project, I was really good. So everyone has their specialty.
Let me say one thing. I'm a big believer that it's not the number of people that you have for anything. If you think about a company or a project, it's not the number of people that you have, it's do you have the right people to do the things. When I first started at AMD, we had 8,000 people. People used to say, 'Oh my goodness, you're so small compared to Intel.' Actually at that time, I think Intel maybe had 10 times the people of AMD. And they said, 'Lisa, you're crazy. Why are you doing that? You cannot possibly win.' And I said, 'Really? Why do you say that?' I actually don't feel that way. I don't feel that it's a number of people. I feel that it's the right people with the right project, with the right focus, and the right vision. And to the point about how do you optimize, I think everyone has in your mind what you can see as your path, and every company's path is different. So I think from my standpoint, and maybe since this is the last question, I will make it a little bit broader. We are incredibly lucky to be in this technology field. I hope all of you feel this way, because we're working on things that are touching billions of people every day. It is having an impact on people's lives. It will make companies better, it will make your life better, it will make our future healthcare better, it will make our future sustainability better. From all of those aspects, we're very lucky to work on this type of technology. So we have to find what it is that we're going to do best. For us at AMD, it's around high performance computing. I don't believe that we can do everything, but I do believe that in high performance computing, it can have a very wonderful impact on people's lives. And that's what we choose to do.
