Nvidia CEO Jensen Huang’s Keynote stuck to tradition at the company’s GTC 2025 conference on Tuesday, packed with announcements. But the company is also sneaking into small history lessons.
During the automotive portion of the speech, Huang mentioned Alexnet. Alexnet is a neural network architecture that attracted widespread attention in 2012, when it won a computer image recognition contest. Designed by computer scientist Alex Krizhevsky, in collaboration with Ilya Sutskever (found Openai) and AI researcher Geoffrey Hinton, Alexnet achieved 84.7% accuracy in an academic competition called Imagenet.
The groundbreaking results have led to a revival of interest in deep learning, a subset of machine learning that utilizes neural networks.
After all, Alecnet spurred nvidia to go “everything” and “everything” with an autonomous vehicle, the way Juan conveys it.
“The moment we saw Alexnet and we’ve been working on computer vision for a long time, but the moment we saw Alexnet was a very exciting and exciting moment,” he said on stage. “It’s because we’ve now been working on self-driving cars that build the technology used by almost every autonomous driving company.
Nvidia has engraved partnerships with numerous automakers, auto suppliers and high-tech companies developing self-driving cars. The latest collaboration, an expanded collaboration with GM, was announced this afternoon.
Automakers like Tesla and automotive developers have used Nvidia GPUs in their data centers by Wayve and Waymo. Other companies tap on Nvidia’s Omniverse products to build “digital twins” in their factories, effectively testing their production processes and designed vehicles. Meanwhile, Mercedes, Volvo, Toyota and Zoox use Nvidia’s Drive Orin computer system-on-chip, based on the chip maker’s Nvidia ampere supercomputing architecture. Toyota and others also use Nvidia’s safety-focused operating system Drivos.
Upshot: Nvidia DNA is embedded in the automobile, and more specifically the automated driving industry.
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