NVIDIA Jensen Huang’s co-founder and CEO spoke with reporters during a trip to Beijing in July.
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if Nvidia CEO Jensen Huang, who is a student today, said he will focus on physical science.
On a trip Beijing On Wednesday, a reporter asked Huang: “If you were 22-year-old Jensen (Who) just graduated today in 2025, but with the same ambitions, what would you focus on?”
To this end, the NVIDIA CEO said: “For Jensen, who is now graduating, he might choose … more sports science than software science,” he added, who actually graduated two years early at the age of 20.
Physical science, contrary to life sciences, is a vast branch focusing on the study of non-biological systems, including physics, chemistry, astronomy and earth sciences.
According to his LinkedIn, Huang received his degree in electrical engineering from Oregon State University in 1984 contour.
About a year later, in April 1993, Huang co-founded NVIDIA with engineers Chris Malachowsky and Curtis Priem. Danny’s Restaurant in San Jose, California. Under Huang’s CEO, chipmakers are now the most valuable company in the world.
NVIDIA also became the first company in the world to reach a market value of $4 trillion last week.
Although Huang didn’t explain why he said he would study physical science if he became a student again today, the founders of technology have always been very optimistic.Physical AI“Or he calls it the “next wave.”
Over the past decade and a half, the world has been running through several stages of artificial intelligence. Explained In April Mountain and Valley Forum In Washington, DC
Huang said on the forum: “About 12 to 14 years ago, modern AI did realize that when Alexnet came out, computer vision saw its huge breakthrough.”
Alexnet is a computer model launched in a 2012 competition that demonstrates the ability of machines to recognize images using deep learning, which helps trigger a modern AI boom.
Huang said the first wave was called “perceptual AI.”
Then the second wave is called “generating AI”, “it is where the AI model understands the meaning of information, but (also) translates it “to different languages, images, codes, etc.
The next wave requires us to understand things like physics, friction, inertia, causality, and effects.
Jansen Huang
NVIDIA Co-founder and CEO
“We are now called ‘inferential AI’ in this era… You now have an understandable AI that can generate and solve problems and recognize conditions we have never seen before.” Artificial intelligence can solve problems with reasoning in its current state.
“Inferential AI enables you to generate a form of digital robots. We call them proxy AI,” Huang said. He added that these AI agents are essentially “digital workforce robots” that can reason. Today, AI agents have become the focus of many technology companies, such as Microsoft and Salesforce.
Looking to the future, the next wave is “physical AI”, Huang said.
“The next wave requires us to understand things like physics, friction, inertia, causality, and so on,” said Huang from Washington, D.C.
He said that in the next stage of artificial intelligence, the fact that physical reasoning capabilities, such as the concept of object persistence, even if the object still exists, will be very large.
Applications of physical reasoning include predicting results such as where the ball will roll, knowing how much force it takes to grab an object without damaging it and inferring the presence of a pedestrian behind the car.
“When you take that physical AI and then put it in a physical object called a robot, you get robotics,” he added. “It’s really important for us now, because we’re building plants and factories throughout the United States.”
“So, hopefully, over the next 10 years, as we build a new generation of plants and factories, which are robots, they are helping us cope with severe labor shortages around the world,” Huang said.
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