March 17, 2026 2:00 p.m. PT

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.

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 kicked off its GTC conference yesterday with a keynote from CEO Jensen Huang. There were a ton of announcements dropped in the nearly 3-hour keynote. Our experts identified the three biggest takeaways from Nvidia GTC. Here’s what you need to know.

Disney and Nvidia are teaming up to combine AI and robotics, resulting in an adorable Olaf droid that joined Huang on stage. Nvidia is also diving deep with a new platform for AI agents, called NemoClaw. Yes, it’s inspired by the viral open-source AI agent OpenClaw — founder Peter Steinberger made a cameo at the preshow, too. Huang also briefly discussed the possibility of data centers in outer space and the biggest challenge to making that a reality. It also dropped DLSS 5, an AI-powered upscaling tool for gamers.

Keep scrolling to see our play-by-play updates during the keynote, and check out our coverage on Instagram and TikTok.

Knowing it’s probably impossible to top Disney robots, Huang closed the keynote shortly thereafter. The AI-generated music video is certainly something, though. 

We got a lot of information in the nearly three-hour keynote, including a robotics partnership with Disney, a new agentic toolkit for developers and a teaser about plans to build data centers in space. Notably absent from today’s keynote was the rumored new N1 and N1X chips, but it’s possible we will see them released later this year.

Thanks for following along, and be sure to check back here as we continue to unpack what all of today’s announcements mean for the future.

Nvidia has announced NemoClaw, a stack for the OpenClaw agent platform to create autonomous AI agents, or “claws.” NemoClaw uses the Nvidia AI Agent Toolkit to optimize OpenClaw with a single command, installing OpenShell for open models and a sandbox for added privacy and security.

“The OpenClaw ‘event’ cannot be understated,” Huang said. “This is as big of a deal as HTML. This is as big of a deal as Linux.”

It’s by far the best part of the keynote so far — Nvidia and Disney are teaming up to create an Olaf droid. The robot version of Disney’s Frozen snowman made an appearance on stage with Huang.

CNET’s Corinne Reichert has all the details on how the project came to be. 

“The robotic snowman runs simulations on Nvidia GPUs and is powered by Nvidia chips. Olaf was brought to life using the Newton Physics Engine, an open-source system developed by Nvidia, Google DeepMind and Disney Research that enables high-performance robot simulations to run quickly on GPUs,” Corinne reports.

Check out her full story, which includes which Disney theme parks may see Olaf droids wandering around.

Nvidia is not content to put its chips in most every data center on the Earth’s surface. The company is making a computer for space. Huang called it Vera Rubin Space-1, and said Nvidia and its partners are already in development. It is “very complicated to do so,” he said.

The big complication? Just as it is on the Earth’s surface, it’s how to avoid overheating.

“In space, there’s no conduction, there’s no convection, it’s just radiation,” Huang said. “So we have to figure out how to cool these systems out in space.”

Nvidia’s Vera Rubin data center platform helps AI companies build and deploy their AI tools. Vera Rubin is getting some new updates to help it handle agentic AI, which are more compute-intensive tasks.

The company introduced a new Vera CPU, which it says “delivers results with twice the efficiency and 50% faster than traditional CPUs.”

Named for the astronomer who discovered dark matter, we first saw the Vera Rubin system at CES in January.

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.”

“Inference is your new workload, tokens are your new commodity … you want to make sure that the architecture is as optimized as you can in the future,” Huang said. “Intelligence will be augmented by tokens.”

Tokens are the building blocks of AI, individual units of data that an AI model can process. Huang said Nvidia has the lowest cost per token in the world, making him a kind of “token king.”

Nvidia introduced DLSS 5, an update to its AI-powered upscaling and optimization software for games. It seems to add element-based understanding — it links characteristics to surfaces (like skin) and maybe objects in order to render more consistent, more realistic lighting and detail throughout a game — by analyzing the initial content. That’s in contrast to the current pixel-by-pixel and frame-by-frame understanding of a scene.

It’s slated to roll out starting this fall. It’s not clear which GPUs it will support, but it’s likely that it’s optimized for the Blackwell architecture of the RTX 50-series.

Nvidia’s GTC keynote is officially rolling. Follow along here for updates, and you can watch the stream live on YouTube.

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.

If there’s one thing that’s absolutely taken over the AI world this year, it’s OpenClaw. This viral, open-source AI agent wowed fans with its agentic AI abilities, able to complete tasks independently and run your entire digital life, if you want that. OpenClaw creator Peter Steinberger appeared in a video interview with Huang, airing on the screen inside the theater at the GTC preshow. His lobster headband is a reference to OpenClaw’s lobster mascot/logo.

OpenAI acquired OpenClaw quickly after it went viral, with Meta picking up its agentic AI social media spin-off, Moltbook.

CNET Social Media Manager Faith Chihil and Jacqueline Goldblatt from our sibling site PCMag are inside the SAP Center waiting for the keynote to begin at 11 a.m. PT.

CEO Jensen Huang will be speaking today about the “latest breakthroughs in AI and accelerated computing.” Nvidia GTC’s keynote is scheduled to begin at 11 a.m. PT (2 p.m. ET, 6 p.m. UK) on Monday, March 16. You can stream the event on YouTube.