On stage at AI's first big event of 2026, Nvidia’s CEO spotlighted technology that didn’t even exist 4 months ago: OpenClaw's personal AI agents.

In his keynote at GTC on Monday, Jensen Huang officially announced NemoClaw, Nvidia’s addition to the claw agent ecosystem. NemoClaw is an agent platform that integrates its open-source Nemotron model family into OpenClaw “self-evolving” autonomous AI agents, popularly known as “claws.”

And Nvidia has high hopes, with Huang saying that OpenClaw “opened the next frontier of AI to everyone … This is the moment the industry has been waiting for: the beginning of a new renaissance in software.”

So what does NemoClaw do? This system installs OpenClaw with Nvidia’s open models, leverages Nvidia’s “agent toolkit” to optimize OpenClaw commands, and installs “OpenShell,” an open-source tech stack with built-in policy-based guardrails, to add a layer of privacy and security controls to these agents.

“[OpenClaw] is the most popular open-source project in the history of humanity, and it did so in just a few weeks,” Huang said in his keynote. Huang was referring to the fact that OpenClaw has rapidly become the project with the most stars on GitHub, but it's a stretch to call it more popular than widespread open-source projects like Linux, Git, and Apache that make up the foundation of the internet.

OpenClaw is not Nvidia’s only bet on agents. Since agents are the most token-hungry AI systems yet, Nvidia is building a booster pack to accelerate them. Huang used part of his three-hour keynote to detail the company's new flagship Vera Rubin platform, a seven-chip, five-computer rack "AI factory" that Huang pitched as built to scale agentic AI.

The platform, available in the second half of this year, was initially announced at CES, but now includes the Groq 3 LPU, a chip designed specifically to run language models fast.

“The future is not just going to be about LLMs,” Huang said in a private press Q&A on Tuesday. “The future is about agentic systems. And [with] agentic systems, the problem space just expanded yet again. So when the problem space expands, you have a greater opportunity to find that big leap.”

Agents can do more, but can also cause more damage. That gives Nvidia a whole lot more to do, from making inference cheaper and more efficient to solving the security pitfalls. To put it simply: more problems, more money (for Nvidia).

Our Deeper View

It makes sense that tech giants such as Nvidia are jumping on the OpenClaw bandwagon. The momentum behind adoption is leaving major gaps to fill. With NemoClaw, Nvidia is meeting AI builders where they’re at, and providing them the resources to tackle one of OpenClaw’s biggest threats: security. Plus, personal AI agents like the various claw agents consume a ton of AI inference, so they push chips like Nvidia’s to the max and drive up demand for the fastest and most powerful systems. In short, by providing the tools to more easily deploy these agents, Nvidia is multiplying its well of high-value customers.