Nvidia CEO Jensen Huang's keynote at the company's GTC 2025 conference was filled with announcements, but it also included a surprising history lesson. During the automotive segment of his speech, Huang credited AlexNet, a neural network architecture, as the catalyst for Nvidia's autonomous vehicle ambitions.

AlexNet, designed by computer scientist Alex Krizhevsky in collaboration with Ilya Sutskever and AI researcher Geoffrey Hinton, made headlines in 2012 when it won a computer image recognition contest with an impressive 84.7% accuracy. This breakthrough result sparked a resurgence of interest in deep learning, a subset of machine learning that leverages neural networks.

Huang revealed that the AlexNet moment was an "inspiring" and "exciting" turning point for Nvidia, prompting the company to go "all in" on building self-driving cars. This decision, made over a decade ago, has since led to Nvidia becoming a crucial player in the autonomous vehicle industry.

Today, Nvidia has notched partnerships with numerous automakers, automotive suppliers, and tech companies developing autonomous vehicles. The company's latest collaboration, an expanded partnership with General Motors, was announced during the conference. Other notable partners include Tesla, Wayve, and Waymo, which utilize Nvidia's GPUs for data centers.

Beyond its GPU technology, Nvidia's Omniverse product is used by companies to build "digital twins" of factories, allowing them to virtually test production processes and design vehicles. Additionally, Mercedes, Volvo, Toyota, and Zoox have employed Nvidia's Drive Orin computer system-on-chip, based on the chipmaker's Nvidia Ampere supercomputing architecture. Toyota and others are also using Nvidia's safety-focused operating system, DriveOS.

The extent of Nvidia's influence in the autonomous vehicle industry is undeniable. As Huang emphasized, Nvidia's DNA is deeply embedded in the sector, with its technology being used by almost every single self-driving car company. This widespread adoption is a testament to the company's commitment to autonomous vehicles, a commitment that can be traced back to the AlexNet breakthrough.

The implications of Nvidia's autonomous vehicle pursuits are far-reaching, with the potential to transform the transportation industry as a whole. As the company continues to push the boundaries of AI and machine learning, its role in shaping the future of autonomous vehicles will only continue to grow.

In conclusion, Nvidia's story serves as a reminder of the profound impact that innovative breakthroughs can have on the technology landscape. The AlexNet moment, which may have seemed like a isolated achievement at the time, has had a lasting influence on the direction of Nvidia and the autonomous vehicle industry as a whole.