The $148 Billion Man Doesn’t Recommend an IT Degree for Students—Here’s What He Suggests Instead
Fundacion Rapala – Jensen Huang, the billionaire CEO of Nvidia, recently gave a bold piece of advice to young students. He said he wouldn’t choose an IT degree if he were 22 today. Instead, he would pick physics as his major.
This statement quickly sparked global discussion. Coming from the head of the world’s most valuable chipmaker, his words carry serious weight.
Why He’d Skip IT for Physics
During an interview with CNBC, Huang was asked what he’d study if he were a young graduate today. Without hesitation, he replied,
“A 20-year-old Jensen would choose physics over software.”
Although surprising, his reasoning makes sense in the context of where AI is heading. He believes the future of AI lies beyond just coding. It will require a deep understanding of the physical world.
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Jensen Huang: From Engineer to AI Visionary
Before launching Nvidia in 1993, Huang earned a degree in electrical engineering from Oregon State University. He later completed his master’s at Stanford University.
Under his leadership, Nvidia became the first company to hit a $4 trillion market cap. Today, it stands at the center of the AI revolution.
AI Has Evolved—So Should Education
Huang explained how AI has evolved in four major waves:
- Perception AI – Began in 2012 with AlexNet, which introduced deep learning for image recognition.
- Generative AI – Allows machines to create language, images, and code based on understanding.
- Reasoning AI – The current phase. AI can now solve problems, understand abstract concepts, and make decisions.
- Physical AI – The next phase. Machines will begin to reason and act in the physical world.
Clearly, the skills needed for this next step go far beyond traditional software development.
What Is Physical AI, Exactly?
According to Huang, Physical AI focuses on how machines interact with the real world. This involves physics-based reasoning. For example:
- Predicting the path of a rolling ball
- Understanding object permanence
- Calculating how much pressure is needed to grip something safely
In short, AI will need to think like humans and move like them too. Therefore, coding alone won’t be enough.
Robotics: The Future Is Physical
Huang emphasized that when AI reasoning is combined with a physical form, you get robotics. These machines will one day operate factories, warehouses, and even homes.
He believes this future is closer than we think.
“In the next 10 years, we’ll build robotic factories to tackle the global labor shortage,” Huang said.
Why Physics Is the Smart Bet
Physics provides the foundation for understanding motion, energy, and cause and effect. These are all essential to creating machines that can function in the real world.
While coding builds the brain of AI, physics builds its senses and body. For this reason, Huang suggests students blend computer science with hard sciences like physics or engineering.
Transitioning from IT to Interdisciplinary Thinking
Many still believe software is the most important skill. However, Huang sees a shift coming. The most valuable innovators will be those who understand how the digital and physical worlds connect.
Therefore, the future of AI won’t be written in code alone. It will be shaped by minds who understand science, logic, and the real world.