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№ 2026.001 — Massachusetts Institute of Technology — Commencement address
Lisa T. Su
Advanced Micro Devices CEO
AMD chair and CEO Lisa Su, an MIT alumna, reflects on her undergraduate and graduate years at MIT, including her UROP research experiences and the development of what she calls an 'engineer's instinct' to break down hard problems. She discusses her career path through IBM and AMD, the promise of AI to accelerate discovery in fields like medicine, and argues that people, not technology, determine the future. She urges graduates to choose ambitious problems, run toward the hardest ones, and make their own luck.
Key moments
- 01 Recounting her arrival at MIT and early UROP research in semiconductor clean rooms
- 02 The mentor advice to 'run toward the hardest problems'
- 03 Becoming CEO of AMD and betting on high-performance computing
- 04 Framing AI as a tool that makes people more capable, especially in medicine
- 05 Closing advice to be ambitious, take risks, and make your own luck
Visual speech map
Lisa T. Su at MIT, 2026
A commencement address about engineering instinct, hard problems, AI as a human multiplier, and making your own luck.
- 01 MIT roots
- 02 UROP labs
- 03 Engineer instinct
- 04 IBM years
- 05 AMD bet
- 06 AI for discovery
- 07 Hard problems
- 08 Make luck
Origin
MIT trains an engineer's instinct
Su begins with the habits shaped by MIT: breaking down difficult systems, staying close to the work, and learning in research settings where theory meets silicon.
Clean-room research turns coursework into craft and gives technical judgment a physical setting.
The useful habit is decomposition: make a hard problem legible enough to attack.
Repeated contact with demanding work becomes the instinct to keep going.
Career
The path compounds through hard choices
From MIT to IBM to AMD, the career story is built around choosing larger problems before the outcome is obvious.
Mentors push her to run toward the hardest problems instead of optimizing for comfort.
The CEO role joins technical judgment, long time horizons, and appetite for risk.
A company-scale comeback is made from many disciplined engineering bets.
Technology
AI expands what people can solve
Su frames artificial intelligence as a tool for human capacity, especially in medicine and discovery, rather than a substitute for human responsibility.
High-performance computing and AI increase what researchers and builders can attempt.
People, not technology alone, decide how powerful tools shape the future.
Progress needs ambition paired with accountability.
Charge
Be ambitious and make your own luck
Her closing advice asks graduates to pick consequential work, move toward uncertainty, and create openings through preparation and courage.
Choose problems worthy of your talent and training.
Move before every variable is settled.
Luck follows motion, preparation, and hard commitments.
Transcript
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