Jensen Huang founded an accelerated computing company Nvidia (NVDA -3.75%) in 1993 and has served as CEO and President since then. Nvidia achieved many breakthroughs under his leadership, but particularly significant was the invention of the graphics processing unit (GPU) in 1999.

Nvidia GPUs have long been the gold standard in rendering graphics for 3D design and gaming applications. More recently, they have become the chips of choice for complex data center tasks such as training large language models and running generative artificial intelligence applications.

Jensen Huang gave a keynote address last week at CES 2025, an annual conference in Las Vegas. CES focuses on innovation in the technology sector, and Huang’s speech made it clear that Nvidia’s product pipeline is still full of potential.

Generative AI is just the first phase of a technological revolution

Wall Street’s interest in generative artificial intelligence can be traced to the launch of ChatGPT in late 2022. The conversational application went viral almost immediately, sparking a series of events that led to a huge surge in demand for Nvidia GPUs. The company has posted triple-digit earnings growth over the past six quarters and its stock price has risen 840% over the past two years.

Some investors fear that generative AI is a short-term catalyst or even a bubble, but nothing could be further from the truth. The Internet has only become more important since its inception, and artificial intelligence will be no different. In other words, the generative AI boom is just the first phase of a technological revolution that will last indefinitely. And Nvidia is at the center of this revolution.

Physical AI is the next phase of the technological revolution

Jensen Huang said at CES, “The next frontier of AI is physical AI.” While generative AI can understand and generate media, physical AI can understand, navigate and interact with the physical world. It will ultimately power numerous types of autonomous robots, but the first type of intelligent robot that most people will use will be an autonomous car, according to Huang.

Importantly, Nvidia has products that cover all three layers of the autonomous vehicle computing stack: its GPUs provide the supercomputing infrastructure needed to train AI models. Its Drive platform provides the software development tools needed to build self-driving applications. And its AGX systems provide the in-vehicle computing power that enables cars to navigate the physical world.

Jensen Huang said in a recent interview with Yahoo Finance that Nvidia’s autonomous driving products could reach $5 billion in revenue this year, up from $1.8 billion last quarter. Importantly, automotive and robotics are currently the company’s smallest segment, but that could change quickly. Citigroup It is estimated that the number of autonomous vehicles will increase almost five-fold by 2030 and 14-fold by 2035.

Image source: Getty Images.

Nvidia is ideally positioned to be a leader in AI robotics

Jensen Huang told the audience at CES, “The ChatGPT moment for robotics is upon us.” He then introduced Cosmos, a suite of pre-trained robotics models that can be refined by developers. Huang also explained that Nvidia has products that cover all three layers of the robotics computing stack.

First, Nvidia GPUs provided the supercomputing infrastructure needed to train robotics models. Second, the Isaac platform includes code libraries and pre-trained models that help engineers develop robotics applications in three use cases: industrial manipulator arms, autonomous mobile robots, and autonomous humanoid robots. Isaac also works as a simulation engine that supports synthetic data generation and evaluation of robotics models.

Finally, Jetson’s embedded systems combine GPUs, CPUs and memory on a single chip, providing the computing power robots need to interact with the real world. Nvidia is clearly well-positioned to benefit as the AI ​​boom evolves into a robotics revolution, and humanoid robots could be a huge opportunity for the company. Citigroup estimates spending will top $200 billion by 2035 and $1 trillion by 2040.

Nvidia shares are cheaper today than they were two years ago

Many investors believe that Nvidia is a very expensive stock, as it has returned 840% over the last two years. But shares trade at 55 times earnings, a reasonable valuation considering Wall Street expects 38% annual earnings growth over the next three years. These numbers result in a price-to-earnings-growth (PEG) ratio of 1.4.

By comparison, the stock was trading at 63 times earnings two years ago, and Wall Street was expecting annual earnings growth of 22% at the time. These numbers result in a significantly higher PEG ratio of 2.9.

As a result, Nvidia shares are actually much cheaper today than they were before the generative AI boom began. And given the tailwinds in autonomous driving and robotics that Jensen Huang highlighted at CES, the stock is still a worthwhile long-term investment.