Use cases revolving around artificial intelligence (AI) are exploding. Every industry is seeking to leverage the technology in some fashion. While the rapid pace of innovation is exciting, it’s worth noting that some AI applications will be more impactful than others.
One key opportunity is autonomous driving. Once a concept reserved for science fiction, some of the world’s largest companies, including Tesla and Alphabet, are now leading the charge in the development of self-driving technology.
However, there is another member of the “Magnificent Seven” that is also playing an integral role at the intersection of AI and automobiles: Nvidia(NASDAQ: NVDA).
How does autonomous driving work?
At a high level, modern vehicles are becoming giant computers with built-in software learning to operate these vehicles just like a human driver. This process is an example of machine learning.
Tesla’s cars, for example, come equipped with an array of cameras and sensors. These devices are constantly monitoring road maps, weather conditions, traffic patterns, and more.
These data are then sent back to a supercomputer that processes the information at scale. The end result is that Tesla has created a software program it can integrate into its fleet that offers owners the option to have the car drive itself.
Image source: Getty Images.
How is Nvidia involved in autonomous driving?
Nvidia is mostly known for its graphics processing units (GPU) and data center services. GPUs are used for a variety of generative AI applications, including autonomous driving. These semiconductor chips are capable of immense computing power. Their ability to process loads of information at a high rate makes them necessary to AI models.
Right now, Nvidia’s most in-demand GPUs include its A100 and H100 chips. During Tesla’s first-quarter earnings call, CEO Elon Musk spoke about the company’s self-driving technology. He told investors that Tesla currently utilizes 35,000 H100 chips, and “we expect that to be probably 85,000 or thereabouts by the end of this year.”
Although the exact price point of the H100 fluctuates, multiple media outlets report these chips can cost around $40,000. Using the figures from above, that means Tesla could be spending $2 billion on Nvidia GPUs just this year.
Considering Nvidia owns an estimated 80% of the AI chip market, it’s likely the vendor of choice among the various companies pursuing self-driving technology. Nvidia is looking at a multibillion-dollar opportunity from autonomous driving alone.
Is Nvidia stock a good buy right now?
The chip giant has been at the center of the AI-fueled hype in the stock market. Shares soared 239% in 2023, and they are up another 70% so far this year. Investors should be aware of the risks from buying into momentum, but as Nvidia’s revenue soars to record levels, profits and free cash flow have climbed even faster.
Considering the development of autonomous driving technology is still in its early stages, I see the trends above as encouraging. Widespread adoption of self-driving cars is years away, and yet, Nvidia is already making billions off the opportunity, one that should only grow as autonomous driving becomes increasingly mainstream.
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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Adam Spatacco has positions in Alphabet, Nvidia, and Tesla. The Motley Fool has positions in and recommends Alphabet, Nvidia, and Tesla. The Motley Fool has a disclosure policy.
Wanda Parisien is a computing expert who navigates the vast landscape of hardware and software. With a focus on computer technology, software development, and industry trends, Wanda delivers informative content, tutorials, and analyses to keep readers updated on the latest in the world of computing.
