An AI model from over a decade ago sparked Nvidia’s investment in autonomous vehicles

Nvidia CEO Jensen Huang’s keynote Tuesday at the company’s GTC 2025 conference stuck with tradition and was chock full of announcements. But the company also snuck in a little history lesson.

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 (who’d go on to found OpenAI) and AI researcher Geoffrey Hinton, AlexNet achieved 84.7% accuracy in an academic competition called ImageNET.

The breakthrough result led to a resurgence of interest in deep learning, a subset of machine learning that leverages neural networks.

Turns out, AlexNet spurred Nvidia to go “all in” on autonomous vehicles, the way Huang tells it.

“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 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 is based on the chipmaker’s Nvidia Ampere supercomputing architecture. Toyota and others are also employing Nvidia’s safety-focused operating system, DriveOS.

The upshot: Nvidia DNA is embedded in the automotive — and more specifically, the automated driving — industry.