MotorTrend presents Jensen Huang with its 2026 person of the year award.

Faith Chihil

While much of GTC has been focused on AI agents and chips, one publication is highlighting Nvidia's role in autonomous vehicles. Automobile magazine MotorTrend presented Huang with its 2026 Person of the Year award on Tuesday during a Q&A session with members of the press.

"Nvidia now has the intelligence needed to scale up self-driving, software-defined vehicles with over-the-air update capability. This is the future of mobility," MotorTrend said in a statement.

The chipmaker recently released a family of AI models called Alpamayo, specifically designed to be integrated into the software that runs self-driving cars. It's focused on real-world scenarios, using reasoning to make decisions quickly. The goal is to transform auto software from data collecting to something that's capable of making data-informed decisions and actions.

As MotorTrend put it, Alpamayo "aims to help automakers develop vehicles that perceive, reason, and act like humans to solve problems, like how to navigate a broken traffic light at a busy intersection without previous experience."

Self-driving cars like those from Waymo or Zoox are becoming less of an oddity and more of a mainstream phenomenon, as CNET's Abrar Al-Heeti reports. AI and AI-based software -- and Nvidia hardware -- are two powerful forces driving its development.

Jensen Huang during a press Q&A during Nvidia GTC 2026.

Faith Chihil

In a Q&A session with members of the press, Huang described his vision for Nvidia in 10 years from now plainly: 75,000 employees working with 7.5 million AI agents.

Nvidia only employs 36,000 people, according to a 2025 estimate. And AI has certainly had a tumultuous effect on the job market, from layoffs to prioritizing AI-savvy candidates. But the bigger story in Huang's estimate is the breakdown -- in that vision, each human employee would ostensibly be working with 100 AI agents. That human-to-agent ratio is one of the highest we've heard, and it's a testament to Nvidia's belief that agentic AI will be able to handle swaths of work.

Nvidia CEO Jensen Huang on stage talking about inference.

Nvidia/Screenshot by CNET

Computing demand has risen dramatically in the past few years, thanks to AI, but the biggest driver now isn't training or creating those AI models, but operating them, Huang said. This is called inference -- when an AI model addresses new information and applies its existing model to do or produce something new. Agentic AI relies heavily on inference because the models have to adjust constantly to new information, and that means demand for the computing power to handle that load is growing dramatically.

"Finally, AI is able to do productive work, and therefore the inflection point of inference has arrived," Huang said. "AI now has to think. In order to think, it has to inference. AI now has to do. In order to do, it has to inference. AI now has to read. In order to read, it has to inference."

We're certain to get some updates on the performance of Nvidia chips during today's keynote, but could we also get new ones? The Verge and The Wall Street Journal have reported that Nvidia is building two new chips, called N1 and N1X, specifically for Windows computers. These chips would fuel Nvidia's return to the consumer market, potentially in Dell and Lenovo computers. 

Nvidia's partnership with MediaTek would likely play a big role in the development of these chips. CNET's computing expert Matthew Elliott explains that these new silicon chips would be "a system-on-chip," meaning they would integrate central, graphics and neural processing units. It will be based on Arm architecture, like Apple and Qualcomm incorporate -- not the x86 architecture used by competitors AMD and Intel, which are in many Windows computers.

"Unlike high-end gaming and creator laptops with dedicated Nvidia GeForce RTX GPUs, laptops with this new Nvidia-designed, MediaTek-manufactured SoC are expected to be thin and light and long running," Elliott said.

Whether you run your AI on-device or in the cloud probably isn't something you think about often. But it should be. There are a lot of benefits to running AI models locally, and Nvidia hardware is helping make that easier for you.

CNET Managing Editor Jon Reed got a close-up look at Nvidia's Project G Assist at CES in January. It's a chatbot-like interface that runs on your device and lets you easily adjust your computer's settings by talking out loud. It's also the tech behind AI chatbot assistants Nvidia is developing for gamers.

"Complex strategy games like Total War: Pharaoh can be particularly challenging for new players to grasp, given that they often come with extensive documentation and intricate mechanics that warrant their own encyclopedias," Reed wrote. "This AI adviser, which runs on-device rather than in the cloud, can answer the player's questions about actual in-game events using the context of all that information."

On-device AI isn't perfect -- it takes up a signification portion of your device's memory, for example. But it's part of a growing movement to give developers and AI users a more secure, inexpensive and quick way to access AI tools without having to rely on AI companies and their data centers. Nvidia's chips in hardware like laptops are one way to make locally running AI easier, along with its more powerful desktop supercomputers, like the DGX Spark, that can be used by individual users and small- to medium-sized companies for more compute-intensive tasks.