夜雨聆风Commencement address by Lisa Su ’90, SM ’91, PhD ’94
“Technology itself does not decide what the future looks like,” the chair and CEO of Advanced Micro Devices told the Class of 2026.
Good afternoon.
President Kornbluth, ChairmanGorenberg, trustees, faculty, families, friends … and most importantly, the MIT Class of 2026.
Congratulations.
You earned this.
Standing here feels different than I expected.
I've given a lot of talks over the years … but this one is personal. And as Murphy’s Law would have it, I somehow managed to lose my voice this week … so please bear with me if my voice sounds a little rough.
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 pretty sure I was good at math.
Then I walked into 6.001 and 6.002.
Within about two weeks, I realized there were a lot of people at MIT who were very, very good at math.
I remember staring at those first problem sets thinking … man, these are super hard.
I had never really pulled all-nighters until freshman year … it was a new experience, but it was a lot of fun doing it together with your classmates.
MIT has this incredible way of pushing you further than you thought you could go.
You wrestled with the problem.
You blew up a circuit or two.
And then, somehow … the thing worked.
And suddenly, you realized you could build something real.
And, that’s when I started feeling like an engineer.
One of the best parts of MIT is UROP.
The opportunity, as an undergraduate, to work on real research.
That changed my life.
My first UROP was in Professor Hank Smith’s lab in Building 39 … making X-ray lithography mask blanks for a graduate student.
To be clear, at the time I had absolutely no idea what thatactually meant.
But I got to put on my first bunny suit, walk into the clean room, and start building devices on little 2-inch wafers.
I learned very quickly to be careful because those wafers were delicate, and Idefinitely didnot want to be responsible for breaking them.
I ran a bunch of experiments. Most of them didn’t work the way we expected. So, we adjusted. And tried again.
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.
I remember thinking: wow, we can build things this small?
Things tiny enough to fit on adiethe size of a coin … but powerful enough to change the world.
And that is when I fell in love with semiconductors.
Later, I had the privilege of working with Professor Dimitri Antoniadis, who became my PhD advisor.
That was where I really learned how to solve problems.
I remember spending weeks in the clean room fabricating devices, then bringing my wafers up to the test lab, only to discover they didn’t behave the way I expected at all.
So, I’d go back to Dimitri’s office, and we’d figure out what experiment we should trynext.
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 andactually contributingsomething new to the field.
And along the way, I started believing in myself.
Not the confidence that I would always know the answer.
But the confidence that even when I didn’t know the answer yet…I could figure it out.
What I realize now is that MIT was teaching me something much bigger than semiconductor physics.
Mensetmanus.
Mind and hand.
When I was a student, I thought it was just a motto.
Now I think it captures exactly what makes MIT 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 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 doesn’t care how old you are.
It cares whether your ideas work.
And one of my mentors told me something that I’ve never forgotten:
Run toward the hardest problems.
At the time, I didn’t fully understand what that meant.
But over time, I realized this was the best advice I ever received.
Hard problems teach you what you're capable of.
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 enormous potential, but the company had been through some tough years.
Some of my mentors thought taking the job was risky.
But for me, this was my dream job.
This was what I’d been training for all those years.
The opportunity to work at the bleeding edge of technology on problems that really mattered.
The first thing we had to figure out was what we wanted to be when we grew up.
We made a long-term bet that high-performance computing would be the most important technology of the future.
We gave our talented team the room to think big.
Over the next several years, we built technology to enable the most powerful computers in the world.
And, through all of it, I used every skill that MIT ever taught me … And then some.
I call it the engineer’s instinct.
The ability to face what seemed like an unsolvable problem, break it down, and methodically work through it step by step.
But, at AMD, I 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.
Which brings me to today.
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 are at the beginning of the AI wave.
To me, AI is different from those earlier technology waves.
It is not just a tool that can help us do things faster. It is deeper than that.
It has the potential to accelerate discovery in every field and help us solve problems we have never been able to solve before.
To make it personal, one of the areas that excites me most is medicine and healthcare.
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 to bring togetherall ofthe knowledge that exists in the world 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 deliver care with the best chance of a successful outcome.
That is the promise of AI at its best.
It does not replace people.
It makes each of us more capable.
Medicine.
Science.
Energy.
Climate.
We may discover more in the next ten years than we have in the last thirty.
Now let me be clear.
Technology itself does not decide what the future looks like.
People do.
For all the promise of AI …
AI cannot decide which problems are worth solving.
It cannot make the hard judgment calls with imperfect information.
It cannot take responsibility for the outcome.
These are our responsibilities.
And they matter more now than ever.
That is why 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 important, and we can figure this out.
And that is exactly who you have become here.
So here is what I want to leave you with.
I am fortunate in many ways.
I am fortunate to have great parents.
I received an extraordinary education.
I have 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: work 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 hard.
It is challenging yourself.
Choosing problems at the edge of what you know.
Surrounding yourself with people who make you better.
And believing that, yes … you can change the world.
So be ambitious about the problems you choose.
Run toward the hardest ones.
And trust your engineer’s instinct.
That is how you make your luck.
I want to take a moment to acknowledge all the families and loved ones here in the audience today.
None of these graduates got here alone.
Thank you for believing in 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.
As oneMITerto another … I am incredibly honored to be here with you today.
Congratulations, Class of 2026.
中文稿
苏姿丰（LisaSu，90届本科，91届硕士，94届博士）毕业典礼致辞
“科技本身并不能决定未来，”这位AMD公司董事长兼首席执行官对2026届毕业生说道。
下午好。
尊敬的科恩布鲁斯校长、戈伦伯格主席、各位理事、各位教职员工、各位家长、各位朋友……以及最重要的，麻省理工学院2026届的同学们。
祝贺你们。
这是你们应得的。
站在这里的感觉与我预想的截然不同。
这些年来，我做过很多演讲……但这次的演讲对我来说意义非凡。而且，真是应了墨菲定律所说，这周我的嗓子好像哑了……所以如果我的声音听起来有点沙哑，请大家多多包涵。
1986年秋天，我来到麻省理工学院。父母把我送到Next House宿舍。当时我17岁。我出生在台湾，在皇后区长大……而且我非常确定自己数学很好。
然后我走进了代号是6.001和6.002的课堂。（电气工程与计算机科学系两门最有代表性的课程）
大约两周后，我意识到麻省理工学院里有很多数学非常非常厉害的人。
我记得当时盯着那些作业题，心想……天哪，这也太难了吧。
直到大一，我才真正开始熬夜……这是一种全新的体验，但和同学们一起熬夜真的很有趣。
麻省理工学院有一种神奇的力量，能让你超越自己想象的极限。
你苦苦钻研问题。
你甚至弄坏了一两个电路。
然后，不知怎么的……它居然成功了。
突然间，你意识到自己可以创造出真正有用的东西。
就在那时，我开始觉得自己像个工程师。
麻省理工学院最棒的项目之一就是本科生研究机会项目（UROP）。
作为一名本科生，有机会参与真正的科研项目。
这改变了我的人生。
我的第一个本科生研究机会项目（UROP）是在39号楼汉克·史密斯教授的实验室里……为一位研究生制作X射线光刻掩模坯。
说实话，当时我完全不知道那到底意味着什么。
但我第一次穿上了防护服，走进了洁净室，开始在两英寸的小晶圆上制作器件。
我很快就学会了要小心谨慎，因为那些晶圆很脆弱，我绝对不想弄坏它们。
我做了很多实验。大多数实验的结果都不如预期。所以，我们调整了实验方案，然后再次尝试。
这简直太酷了。
我第一次不再只是在教室里学习技术，而是成为了一个团队的一员，共同探索新事物。
我记得当时我在想：哇，我们竟然能制造出这么小的东西？
小到可以印在硬币大小的芯片上……却强大到足以改变世界。
正是在那时，我爱上了半导体。
后来，我有幸与迪米特里·安东尼阿迪斯教授共事，他成为了我的博士生导师。
正是在那里，我真正学会了如何解决问题。
我记得自己曾在洁净室里待了好几个星期，制造器件，然后把晶圆送到测试实验室，结果却发现它们的表现完全出乎我的意料。
于是，我又回到迪米特里的办公室，和他一起探讨下一步该尝试什么实验。
回想起来，那可能是我在麻省理工学院成长最多的地方。
因为我一点一点地从一个刚入行的研究生，逐渐成长为一名从事原创研究，并真正为这个领域做出贡献的人。
在这个过程中，我开始相信自己。
不是那种认为自己总能找到答案的自信。
而是那种即使我不知道答案，也能找到答案的自信。
我现在意识到，麻省理工学院教给我的远不止半导体物理。
“手脑并用”
学生时代，我以为这只是一句校训。
现在，我认为它精准地概括了麻省理工学院的独特之处。
麻省理工学院教你深度思考。
但它也教你动手实践。
检验想法。
即使第一次实验——甚至是第五次实验——失败了，也要坚持下去。
随着时间的推移，你会开始相信自己能够解决那些曾经看似不可能解决的问题。
离开校园很久之后，我仍然带着这种感觉。
加入IBM后，我发现自己又回到了原点。
IBM拥有数十万名员工。当时我25岁，不禁疑惑自己如何在这样一家庞大的公司里有所作为。
但我很快就明白了一个重要的道理：工程学并不在意你的年龄。
它只在意你的想法是否可行。
我的一位导师曾告诉我一句我至今难忘的话：
迎难而上，挑战最棘手的问题。
当时，我并不完全理解这句话的含义。
但随着时间的推移，我意识到这是我听过的最好的建议。
难题会让你了解自己的潜能。
时间快进……12年前，我终于有机会实践这句话。
我获得了成为AMD首席执行官的机会。
AMD拥有巨大的潜力，但公司也经历了一段艰难的时期。
我的一些导师认为接受这份工作风险很大。
但对我来说，这是我梦寐以求的工作。
这正是我多年来努力的目标。
有机会站在技术的最前沿，解决真正棘手的问题很重要。
我们首先要弄清楚的是，长大后我们想成为什么样的人。
我们做出了一个长远的赌注：高性能计算将是未来最重要的技术。
我们给予才华横溢团队充分的空间，让他们敢于大胆设想。
在接下来的几年里，我们开发出了能够驱动世界上最强大计算机的技术。
在这一切过程中，我运用了在麻省理工学院学到的所有技能……甚至更多。
我称之为工程师的直觉。
这种能力能够面对看似无法解决的问题，将其分解，并有条不紊地一步步解决。
但在AMD，我学到了另一点。
当工程师的直觉被团队所共享时，它会变得更加强大。
我职业生涯中最有成就感的事情，就是将人们聚集在一起，完成我们所有人认为不可能的事情。
这就引出了我今天要说的话。
在过去的几十年里，我们经历了几次重大的技术变革。
互联网改变了我们的沟通方式。
移动计算改变了我们的生活方式。
云计算改变了我们的工作方式。
而现在，我们正处于人工智能浪潮的开端。
在我看来，人工智能与之前的那些技术浪潮截然不同。
它不仅仅是一个能帮助我们更快完成工作的工具，它的意义远不止于此。
它有潜力加速各个领域的发现，并帮助我们解决以前从未解决过的问题。
就我个人而言，我最感兴趣的领域之一是医学和医疗保健。
我们都曾亲身经历过挚爱之人患病时的感受。
即使拥有顶尖的医生和最好的护理，你也会意识到，在危急时刻，任何一个人都很难将世界上所有的知识汇集起来提供帮助。
人工智能可以帮助我们改变这一切。
它可以帮助医生和研究人员将世界一流的专业知识带给每一位患者……并提供最有可能取得成功的治疗。
这就是人工智能最美好前景的体现。
它不会取代人类。
它让我们每个人都更有能力。
医学。
科学。
能源。
气候。
未来十年，我们或许会获得比过去三十年更多的发现。
现在，我要明确一点。
技术本身并不能决定未来。
决定未来的是人。
尽管人工智能前景广阔……
但人工智能无法决定哪些问题值得解决。
它无法在信息不完整的情况下做出艰难的判断。
它无法承担后果。
这些是我们的责任。
而且，它们比以往任何时候都更加重要。
正因如此，从麻省理工学院毕业才显得如此意义非凡。
因为世界需要的不仅仅是懂得如何使用强大工具的人。
它需要的是懂得如何运用这些工具的人。
有使命感的人。
有判断力的人。
有勇气的人。
那些面对难题会说：“我知道这很重要，我们一定能解决”的人。
而你们，正是这样的人。
所以，我想和大家分享的是：
我在很多方面都很幸运。
我很幸运拥有伟大的父母。
我接受了卓越的教育。
我有机会与优秀的人共事。
但我相信，我的职业生涯也充满了幸运。
当人们向我寻求职业建议时，我经常告诉他们：努力工作……但也要明白运气很重要。
随着时间的推移，我逐渐相信，最优秀的人总能找到创造运气的方法。
运气不仅仅是在正确的时间出现在正确的地点。
它是敢于冒险去挑战难题。
它是挑战自我。
它是选择那些你知识领域边缘的问题。
它是与那些能让你变得更好的人为伍。
它是相信，是的……你可以改变世界。所以，要对你选择的问题充满雄心壮志。
勇于挑战最难的问题。
相信你的工程师直觉。
这就是你创造好运的方式。
我想借此机会感谢今天在场的所有家人和亲友。
这些毕业生都不是孤军奋战走到今天的。
感谢你们的信任、支持和帮助，让他们走到今天。
这份成就也属于你们。
致2026届的同学们……
记住……在未来的某个时刻，你们会走进另一个房间，完全不知道该做什么。
你们以前也经历过这种情况。
去想办法解决吧。
作为一名麻省理工学院的校友……我非常荣幸今天能与你们在一起。
祝贺2026届的同学们！
