NVIDIA CEO Jensen Huang recently shared what he would study if he was starting the university again in 2025 – and it would not be what he actually did decades ago. During an interview CNBC On his visit to Beijing, Huang was asked what he would focus if he was 22 years old today. His answer was clear: he would choose physics. “For young, 20 -year -old Jensen, who is now a graduate, he may have chosen more physics than software science,” Huang said. It comes as a surprise for many people, as Huang studied electrical engineering – earned his degree from Oregon State University in 1984 and later completed his master at Stanford. But since then the world has changed a lot, and so science has shaped modern techniques.

Huang did not explain deeply about why he likes physics today, but it fits with what he has recently talked about – a concept that he calls “physical AI”. This idea is being described as the “next wave” of artificial intelligence. It is not just about generating text or identifying photos – it is about making machines interact with the real world and helping it better.

AI has gone a long way. Earlier, it was mostly focused on perception – for example, identifying images or voice. Then the generative AI came, who could write the lesson, make images and interact. Now, according to Huang, we are in a new phase: logic AI. This version of AI goes one step forward. It just does not identify or generate – it resolves new problems and decides in real time.

He said, “Now we are in this era, which is called ‘Reasoning AI’, where you now have AI that can understand, it can generate, (and) can solve problems and recognize the situations that we have never seen before,” CNBCHuang believes that this new type of AI he calls him “Agentic AI” – smart digital assistants who can act like human workers, can act freely and even take decisions.

But to go beyond the screen for AI and work in the physical world, Huang says that we need to better understand the real world forces. “For the next wave we need to understand things like physics, friction, inertia, causes and rules of effect,” he said. These are building blocks that will help machines safely and effectively move, hold or react to real items.

“And when you take that physical AI and then you put it in a physical object called Robot, you get robotics,” he said. For Huang, this is not just a future thinking. With the lack of global labor and the construction of more factories, he sees the intelligent robot as an essential part of the workforce.

The company that she co-established in 1993 has recently become the most valuable company in the world. Its chips strengthen many of today’s devices, and with Huang’s vision, the future of AI is even more connected to the physical world.