If you could time travel back to your college years with everything you know now, what would you study? For Jensen Huang, CEO of NVIDIA and a titan of the AI revolution, the answer is not what you’d expect.
Not computer science. Not AI. Not even software engineering.
“If I could be 20 once more, I would pursue studies in the physical sciences,” Huang shared with a crowd in Beijing, an unexpected remark from the individual whose company is now associated with the future of artificial intelligence (AI).
In a society fixated on algorithms and coding, Huang highlights an alternative frontier: one driven by physics, chemistry, and earth sciences to inspire the next wave of innovation. And with insights from a tech visionary who has propelled NVIDIA beyond a $4 trillion market value, people are paying attention
Why the Physical Sciences?
Huang argues that the next wave of innovation, what he calls “physical AI” requires a deep understanding of the real, physical world. As AI expands into robotics, autonomous systems, and real-world applications, success depends on equipping machines with knowledge of physical laws like inertia and energy, not just lines of code.
This suggestion sharply departs from his own education path, Huang studied electrical engineering and built NVIDIA from the ground up. Now, he is urging a generation to consider a discipline he believes is more foundational for the future of tech.
Broader Vision for Tomorrow’s Workforce
For students deciding between computer science, AI, or software engineering, Huang’s view encourages exploration of disciplines that ground AI in the real world. Physics, materials science, chemistry, and mechanics may hold the key to future breakthroughs.
Educators and institutions might take note, too, integrating AI curricula with physical sciences could better prepare students for upcoming cross-disciplinary challenges.
Huang’s advice is a powerful prompt to rethink traditional tech paths. In his words, juggling equations and understanding how gravity, friction, or energy dynamics play out in a real environment might matter more than writing another script in Python.
He is not dismissing software, just urging a deeper lens: one grounded in how the world works.
Why It Matters
| Reason | Why it is Important |
| Visionary Shift | Highlights the transition from software-only AI to physical AI. |
| Future-Proof Advice | Encourages skills that will underpin autonomous systems and robotics. |
| Inclusivity in Tech | Promotes broader academic pathways—not just coding-for-coding’s-sake |
In short, Jensen Huang, who helped build NVIDIA into a global AI powerhouse believes that future-focused education should embrace the physical sciences. This is not just about theory, it is about grounding AI in real-world systems. If you are aiming to ride the next wave in technology, his advice might light a new path.
