LISA T. SU: All right. Good afternoon, everyone. President
Kornbluth, Chairman Gorenberg, trustees, faculty, family, friends, and most
importantly, the MIT Class of 2026, congratulations. You've earned this. And I
can tell you that standing here feels very different than I expected. I've
given a lot of talks over the years, but this one is quite personal. And as you
can imagine with Murphy's law, I somehow managed to lose my voice this week. So
please bear with me if I sound a little rough. But I couldn't be happier to be
here with you, and if I give you a little bit of my story. I came to MIT in the
fall of 1986. My parents dropped me off at Next House. I was 17 years old, born
in Taiwan, raised in Queens, and I was pretty sure I was good at math. Then, of
course, I walked into 6001 and 6002, and within about two weeks, I realized
there were a lot of people at MIT who were very, very good at math. And I
remember staring at those first problem sets thinking, my goodness. These are
super hard. And I'd never really pulled an all-nighter until freshman year. It
was a new experience, but it was a lot of fun doing it together with your
classmates. Now, MIT has this incredible way of pushing you further than you
thought you could go. You wrestled with a problem. You blew up a circuit or
two. Yes, some of you may have. And then somehow the thing worked. And suddenly
you realized that you could build something real. And that's when I started
feeling like an engineer.
One of the best parts of MIT is actually UROP, the
opportunity as an undergraduate to work on real research, and that actuatly
truly changed my life. My first UROP was in Professor Hank Smith's lab in
Building 39, which Anantha tells me we are decommissioning and moving, making
X-ray lithography mask blanks for a grad student. To be absolutely clear, at
the time I had no idea what that actually meant. But I got to put on my first
bunny suit and walk into a clean room and start building devices on little 2-inch
wafer which at the time was pretty state of the art. And I learned very quickly
to be careful, because those wafers were actually really delicate, and I
definitely didn't want to be the one who broke them. But I ran a bunch of
experiments. Most of them didn't work the way we expected and so we adjusted
and we tried again. And it was the coolest thing ever. For the first time, I
wasn't just learning about technology in a classroom. I was part of a team
trying to discover something new. And I remember thinking, wow, we can build
things this small, things tiny enough to fit on a die the size of a coin, but
powerful enough to change the world And that's when I fell in love with
semiconductors.
Later, I had the privilege of working with Professor Dimitri
Antoniadis, who became my PhD advisor. And that was where I really learned how
to solve problems. I remember spending weeks in the clean room, fabricating
devices, and then bringing my wafers up to the test lab, only to discover they
didn't behave the way I expected at all. And so I'd go back to Dimitri's
office, and we'd figure out what we should do next. And looking back, that was
probably where I grew the most at MIT. Because little by little, I went from a
new grad student learning about the field to someone doing original research and
actually contributing something new to the field.
And along the way, I started believing in myself, no the
confidence that I would always
know the answer, but the confidence that even when I didn't
know the answer, I could figure it out. What I realize now is MIT was teaching me
something much bigger than semiconductor device physics mens et manus, mind and
hand. When I was a student, I thought it was just a motto. Now I think it
captures exactly what makes MIT so special. MIT teaches you to think deeply,
but it also teaches you to build, to test ideas, to keep going when the first
experiment, or even the fifth experiment doesn't work. And over time, you start
believing that you can solve problems that once felt impossible. I carried that
feeling with me long after I left campus.
When I joined IBM, I found myself starting all over again. IBM
had hundreds of thousands of employees. I was 25 years old, wondering how I
could possibly make a difference in a company that big. But I learned something
important very quickly. Engineering actually doesn't care how old you are. It
actually cares whether you have good ideas. And one of my mentors told me
something that I've never forgotten. Run towards the hardest problems. At
the time, I'm not sure I really knew what that meant, but I now realize this
was the best advice I've ever received. Hard problems really teach you what
you're capable of. So fast forward a bit.
12 years ago, I got a chance to put that lesson to the test.
I had the opportunity to become CEO of AMD. AMD had a lot of potential, but the
company had been through a few tough years And some of my mentors thought
taking that job was actually kind of risky. But for me, this was my dream job. This
is what I'd been training for all those years, the opportunity to work at the
bleeding edge of technology on problems that really mattered. And the first
thing we had to do was figure out what we wanted to be when we grew up. This is
a big company that had to figure this out. We made a long-term bet that
high-performance computing would be the most important technology of the
future, and we gave our talented team the room to think big.
And over the next several years, we built technology to
enable the most powerful computers in the world. And I can tell you through all
of it, I used every skill that MIT ever taught me and then some. I was trying
to put it in words. And I decided that calling it the engineer's instinct was
the right thing. It's the ability to face what seemed like an unsolvable
problem, break it down, and methodically work through it step by step. But I
also learned something else. The engineer's instinct is even more powerful when
it becomes shared by a team. And the greatest satisfaction of my career has
been bringing people together to do something more than any of us thought was
possible. And that brings me to today and where you guys are.
Over the last few decades, we've experienced several major
technology shifts. The internet changed how we communicate. Mobile computing
changed how we live. Cloud computing changed how we work. And now we're at the
beginning of the AI wave And to me, AI is really different from all those other
waves. The way I think about it is it's not just a tool that can help us do
things faster because we have lots of tools. It's actually deeper than that. It
has the potential to accelerate discovery in every field and help us solve
problems that we've never been able to solve before. And to make it personal,
the area that excites me the most is actually what we can do in medicine and
health.
I think we've all experienced firsthand what it feels like
when someone you love is sick. And even with incredible doctors and the best
care, you realize how hard it is for any one person, or any one team, to bring
together all of the knowledge that has been gathered to help in that critical
time of need. AI can help us change that. It can help doctors and researchers bring
the world's best expertise to each patient and each love one and deliver the
care that we want for the best chance of a successful outcome. And this, I
think, is the promise of AI at its best. Now, the way to think about it makes
each of us more capable. Whether you're talking about medicine, science,
energy, climate, I think you can say we may discover more in the next 10 years
than we have in the last 30. But let me be clear about something.
Technology itself does not decide what the future looks like.
The best people do. For everything that
AI can do, AI can't decide which problems are worth solving. It can't make the
hard judgments when the data is not there. It can't take responsibility for the
outcomes. These are actually our responsibilities, and they matter now more
than ever. This is why I feel this is such an extraordinary moment to graduate
from MIT. Because the world does not just need people who know how to use
powerful tools. It needs people who know what to use them for people with a
sense of purpose, judgment, courage, people who look at a hard problem and say,
I know this is really, really important, and we can figure this out. And
that is exactly who you have become here at MIT.
So here's what I want to leave you with. I've been very
fortunate in many ways. I have great parents. I received an extraordinary
education. I've had the chance to work with great people. But I also believe
I've been very lucky in my career. When people ask me for career advice, I
often tell them, yes, you need to work really hard, but also understand that
luck matters And over time, I've come to believe that the best people find ways
to make their luck. Luck is not just being in the right place at the right time
It is taking the risk to work on something really hard. It's challenging
yourself. It's choosing problems where you may not know the answer. It's
surrounding yourself with people who make you better. And yes, it's believing
that you, the Class of 2026, can change the world. So be incredibly ambitious
about what problems you choose to solve. Run toward the hardest ones, and trust
what MIT has taught you, that engineer's instinct. That's how you make your own
luck. I want to take a moment to acknowledge all the families and loved ones
who are here in the audience today.None of these graduates got here without
you. Thank you for believing them, supporting them, and helping them reach this
moment. This achievement belongs to you, too.
And to the Class of 2026, remember somewhere in the years
ahead, you're going to walk into another room where you have absolutely no idea
what you're doing. You've done this before. Go figure it out. And as one MITer
to another, I am incredibly honored to be here with you today. Congratulations,
Class of 2026.
Summary :
🎓 Lisa Su
(CEO of AMD, MIT alumna)
- Personal
journey at MIT: She shared her early struggles with
tough coursework, late nights, and learning through hands-on research
(UROP). These experiences taught her resilience and problem-solving.
- Engineer’s
instinct: She emphasized MIT’s motto mens et
manus (mind and hand), highlighting the ability to break down
seemingly impossible problems step by step.
- Career
lessons: At IBM and later AMD, she learned to
“run toward the hardest problems.” Taking risks and tackling challenges
shaped her leadership.
- AI and
the future: She described AI as a transformative
wave, especially in medicine, with potential to accelerate discovery and
improve healthcare.
- Advice
to graduates: Be ambitious, choose hard problems,
make your own luck, and trust the instincts MIT has instilled in you. She
closed by urging graduates to believe they can change the world.
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