Nvidia’s CEO Highlights the Impact of AlexNet on the Development of Autonomous Vehicles
Nvidia CEO Jensen Huang’s keynote at the company’s GTC 2025 conference was chock full of announcements, but he also took a moment to reflect on the company’s history.
AlexNet: A Turning Point in AI Research
During the automotive portion of his speech, Huang referred to AlexNet, a neural network architecture that gained widespread attention in 2012 when it won a computer image recognition contest. Designed by computer scientist Alex Krizhevsky in collaboration with Ilya Sutskever and AI researcher Geoffrey Hinton, AlexNet achieved 84.7% accuracy in an academic competition called ImageNET.
The Resurgence of Deep Learning
The breakthrough result led to a resurgence of interest in deep learning, a subset of machine learning that leverages neural networks.
Nvidia’s Decision to Focus on Autonomous Vehicles
Turns out, AlexNet spurred Nvidia to go “all in” on autonomous vehicles, according to Huang. “The moment I saw AlexNet — and we’ve been working on computer vision for a long time — the moment I saw AlexNet was such an inspiring moment, such an exciting moment,” he said on stage. “It caused us to decide to go all in on building self-driving cars. So we’ve been working on self-driving cars now for over a decade. We build technology that almost every single self-driving car company uses.”
Nvidia’s Partnerships and Products
Nvidia has notched partnerships with numerous automakers, automotive suppliers, and tech companies developing autonomous vehicles. Its latest, an expanded collaboration with GM, was announced this afternoon.
Automakers like Tesla and autonomous vehicle developers Wayve and Waymo use Nvidia GPUs for data centers. Other companies tap Nvidia’s Omniverse product to build “digital twins” of factories to virtually test production processes and design vehicles. Meanwhile, Mercedes, Volvo, Toyota, and Zoox have used Nvidia’s Drive Orin computer system-on-chip, which is based on the chipmaker’s Nvidia Ampere supercomputing architecture. Toyota and others are also employing Nvidia’s safety-focused operating system, DriveOS.
The Impact of Nvidia’s Technology
The upshot: Nvidia DNA is embedded in the automotive — and more specifically, the automated driving — industry.
Conclusion
In conclusion, Nvidia’s journey to become a leader in the autonomous vehicle industry was sparked by the success of AlexNet. The company’s technology is now widely used across the industry, from automakers to tech companies developing self-driving cars.
FAQs
Q: What is AlexNet?
A: AlexNet is a neural network architecture that gained widespread attention in 2012 when it won a computer image recognition contest.
Q: What is deep learning?
A: Deep learning is a subset of machine learning that leverages neural networks.
Q: What is Nvidia’s role in the development of autonomous vehicles?
A: Nvidia has notched partnerships with numerous automakers, automotive suppliers, and tech companies developing autonomous vehicles, and its technology is widely used across the industry.
Q: What is Nvidia’s Drive Orin computer system-on-chip?
A: Nvidia’s Drive Orin computer system-on-chip is based on the chipmaker’s Nvidia Ampere supercomputing architecture and is used by companies like Mercedes, Volvo, Toyota, and Zoox for developing autonomous vehicles.
