AMD chair and CEO Lisa Su came to Taiwan this week for business meetings, as well as to receive an honorary doctorate degree from the National Yangming Chiaotung University in Hsinchu. NYCU is the first university in Taiwan to teach the engineering of semiconductors and is the alma mater of many important tech entrepreneurs and executives in Taiwan, including Acer's Stan Shih, UMC founder Robert Tsao, Asus founder Johnny Shih, Wistron chairman Simon Lin, TSMC CEO C. C. Wei, and Phison founder K. S. Pua, etc.
Su shared her views on the prospects of the semiconductors industry, the key role of the ecosystem in Taiwan, and the tremendous opportunities that come along with artificial intelligence (AI) in the next 10 years. She also gave advice to students on the importance of interdisciplinary collaborations in innovations as well as the cooperation between academia and the industry.
To serve readers worldwide who would like to get the holistic content of her insights, DIGITIMES Asia has compiled the transcription of her speech at the conferral ceremony and the Q&A session as follows:
Transcription of Lisa Su's speech:
Thank you all very much for this great honor. I'm extremely proud and humbled to receive this honorary doctorate from such an incredible university in Taiwan, and also throughout the world. This week that I've been in Taiwan has been truly fantastic. As someone who was born in Taiwan and grew up in the United States, every time I come to Taiwan, it's like coming home. This time, coming home actually feels more special. Because it's been too long since we could be here. After a great week, meeting with our partners and our customers and our employees, this honorary doctorate is truly the best way to finish the week for me. Thank you so much. I'm truly honored to accept this recognition. And I'm deeply grateful.
The principles of National Yangming Chiaotung University (NYCU) are truly close to my heart. Because you are founded on the idea that a great university is a place where people come together across multiple disciplines to solve real-world problems. And I truly believe that whether you're in research or you're in business, the way to really bring about the most groundbreaking innovation actually requires this holistic approach across multiple disciplines and multiple perspectives. NYCU is a pioneer in bringing together multiple disciplines and to learn those disciplines in school is really the best preparation for the future. I really have tremendous respect and admiration for President Lin and Dean Wang, and all of the faculty and staff of NYCU, who are shaping the next generation of leaders. I would not be where I am today without the support of my professors who guided me when I was a young student at MIT. Now, it's also really wonderful to see all the students that are here with us today, and you all who are watching us online. Maybe I can take a few minutes to tell you a little bit about my story.
When I was a young electrical engineering student, I was thinking, how could I make a difference in the world. Actually, there were so many smart people at MIT, I felt that it was really hard to decide what to do. However, my inspiration came from the first time I went into a semiconductor lab. What I realized then is my true passion was to build things. And semiconductor chips were things that I could build in a lab and touch and feel. And I then decided I wanted to get a Ph.D. in semiconductors. And at the time, nobody thought semiconductors were interesting. Actually, most people did not even know what is a semiconductor. However, I really believed that semiconductors could change the world. And now you fast forward to today. And what the last few years has taught us is that semiconductors are truly essential to every part of our life.
And being in Taiwan this week reminds me that Taiwan is truly the center of the global semiconductor ecosystem. The talent, the resources, the innovation, the culture, and the spirit in Taiwan are really what makes the semiconductor ecosystem here truly amazing. I've been in this industry now for almost 30 years. And I must say, I'm incredibly proud to be in this industry. And together, we really do change the world.
Now, as exciting as the last few years have been, I actually believe the next 10 years will be much, much more exciting. The innovation opportunities ahead of us are truly enormous. And the computing industry is changing very fast. And perhaps the most important aspect is AI. AI is really the defining megatrend for the next 10 years and more. And generative AI has really reshaped how we think about this, where we see that every product, every service, and every business in the world will be impacted by AI. And the technology is actually evolving faster than anything that I've ever seen before. Now, AI also requires that all disciplines come together, including hardware, software, systems, applications, and even business models. And this is the perfect example of the multidisciplinary approach and different perspectives that NYCU is all about.
So it's an incredibly exciting time for all of us in the technology industry. And it's also an opportunity for all of us to come together to drive the industry faster. So let me finish by saying thank you. I really want to acknowledge my AMD team, our partners, and all of our friends and colleagues in Taiwan. This recognition is really for all of the work that we have done together. And of course, I also want to thank my parents and my family for all of their support. And some of my relatives are here today. Thank you for being here. I'm very, very happy today to become part of the NICU family. And I'm very, very optimistic about the future and the role that we now as alumni of NYCU will play in using technology to solve the world's toughest challenges. It's truly an honor to be here today. Thank you again, President Lin and Dean Wang, and to all of the faculty, staff, and students at NYCU.
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Q&A session with a panel of NYCU students:
Q: How did you go from a technical engineer to the CEO of AMD? And how did you develop the business mindset?
First of all, it's great to meet all of you. I think you make us all feel younger, to talk to you. And I should also say that I'm very, very happy to see my friend Jack Sun again. Jack was my first boss at IBM. So he was a very, very important mentor for me when I was a very young engineer at IBM. So to answer your question, Charlie, I would say that, I actually believe that engineering is the hardest profession. If you think about, all of the rigors from the classes, and then the research, and then your oral exams, and all that you have to do. Once you graduate with your degree, you're actually already extremely, extremely capable. And then when you go into industry, you will also learn a lot by every project that you do. Relative to engineering, I actually think business is a bit easier. When you think about how to go from engineering to business, it's really what your preference is. In my case, I love to build products and I love to work in teams. But I also realized that to make the most impact, you also have to have some view of strategy and customers and where's the market going. And so, it really is learning on the job. After many years of learning and many mistakes, you actually become much smarter after each one. But definitely, engineering is the hardest part of it.
Q: The field of artificial intelligence is experiencing unprecedented growth. What is your advice for students on how to leverage the resources they have, and how to prepare for their careers in this rapidly evolving field?
It is really incredible, as we can all see that the field of AI is moving so quickly, even from six months ago to three months ago to one month ago, there are a lot of changes. I think, as students, you have so much freedom. And for AI, there are so many aspects of AI. There's hardware and architecture, there's software, libraries, and models, and applications and systems. My recommendation for students is to really try to have a broad view of the technology field because what we always learn is that it's not today's problem that you're trying to solve. Actually, you're trying to solve tomorrow's problem. And so the more the different disciplines and different perspectives that you have, will prepare you very well for the future. But as I said, I think you guys have the most exciting time because you can do all of these different aspects. And there will be so much innovation over the next 10 years.
Q: My question is about interdisciplinary collaborations. During the recent World Artificial Intelligent Conference 2023, I heard you highlight the importance of interdisciplinary collaboration, as we discussed the importance of AI. We know AI can involve in the design process, which requires the collaboration of professionals or talents from diverse fields. So in your perspective, should we focus more on cross-field learning to broaden our knowledge base? Or should we focus on a specific major, to deepen our expertise?
I think it really depends on the individual because you can decide what you enjoy more. Some people like to be really very, very deep in one field. And, for me, I like to see a lot of different fields, because I think the most creativity comes when you can connect different pieces. So again, as we talked about, as it relates to AI, you know, when you think about how can we advance the field of AI, it's not just a hardware solution or a software solution, you actually need to optimize the two together. And so the more that you can understand that, the more you can move faster. So I think interdisciplinary learning is very helpful. And you have so many resources here when you're in school.
Credit: DIGITIMES
Q: What are the valuable contributions and strengths that female engineers bring to the industry?
Ah, you mean the female engineers are smarter right? One of the reasons I love engineering is because actually, engineering is very black and white. When you work on a product, either the product works or doesn't work. There's no kind of maybe, and I think that actually makes engineering an excellent profession for women as well as men. And in particular, what I have experienced is that the best teams have people with all different perspectives because that's how you get the best ideas. If you only have people with the same background, then they all think the same way. So we've made a lot of progress with women in engineering. I'm actually very, very happy to see two out of three students are women, today.
Well, we can do more. And I think we can encourage more women in engineering and more people to realize that this is really a very exciting and fun profession. And you can really make a big difference. And so we should encourage more people to join.
Q: How do you see the future of the semiconductor industry in Taiwan, given the continuous advancement of artificial intelligence and other high-performance computing platforms?
Yeah, so you know, the semiconductor industry in Taiwan is really amazing. I mean, if you think about just even in this area, in Hsinchu (Science) Park, and all throughout Taiwan, you have so much talent and so many resources. And, you know, just a wonderful culture for innovation. You know, Jack will remember when we were working together, people always said, semiconductor scaling is ending. They actually said it was going to end 20 years ago.
And then they said, it was going to end 10 years ago. And then definitely, it should end now. The truth is that semiconductor innovation is not ending, because people are very smart, they always come up with new ideas. So even if traditional scaling is reaching some of its limits, we do 2.5D or 3D packaging to scale a different way. Or we add different types of materials or different integration processes. So I think the future of semiconductors is, this is the most essential field that is impacting every aspect of our life. And so, in Taiwan, the progress in semiconductors is so incredibly fast, and also extremely efficient. I think this is what makes the Taiwan ecosystem so important. And I think AI is just on top of that and adds not just hardware, but all the software and systems capabilities as well.
Q: Could you provide a more specific insight regarding the differences between AI in academia and AI in the industry? As a Ph.D. candidate nearing graduation, I noticed that there is a discrepancy between the job description (in a company) and academic research. So I'm curious to know, how do you see this difference? What caused the difference? And should we be concerned about it? Or how can we better prepare for ourselves?
Maybe I can ask you which one you like better? I think both academic research, as well as industry, have positives and also some differences. I think, on the positive side, no matter what you do, you're going to be doing something that's very, very exciting. So whether in academia or in industry, I think in academia, maybe you have a bit more freedom to pursue longer-range topics, and look at some more fundamental and foundational topics, if that's your interest. And in industry, sometimes we're always thinking, how quickly can we bring something to product and ensuring that you know, we understand the business model and application so it just depends on your personal preference. But actually, I think AI is one of those fields where you'll see a lot of collaboration between industry and academia. Actually, you know, for AMD, we have a lot of collaboration in the industry, but we also like to really seek the input of academia to help shape our long-term thinking so both are excellent choices.
Sun: I agree with Lisa's wisdom and advice. Both semiconductors and AI are really synonymous with innovation. And it's, as Lisa kept emphasizing, cross-disciplinary connection, co-innovation, and co-creation are very important.
Q: How could engineers develop their business mindset? And specifically, what did you do for developing a business mindset?
I had many different opportunities when I spent much of my career at IBM. So I was, as I mentioned, with Jack and with others, and you know, the thing about once you leave school, you don't stop learning. Actually, you keep learning every year in every job assignment. So from my standpoint, I really like to develop products, this is my passion. But I also like to see the products end up in the customers' hands to find a good home. And so I had the opportunity to learn from some of the best teachers in the industry. And I would say again, that the best learning for business is on-the-job training. And you have to heed one of the advice that I got when I was a student. One of my bosses told me that "Lisa, it's very, very important, for you to run towards problems". And what that means is that to develop either your business capability or even your overall technical capability, you want to choose some very hard problems, and try to solve them. And every time you learn, you will become better the next time. So that's how I would suggest you can learn either engineering or business, it's the same: Try to pick some very interesting and hard problems and learn through each one.
