Six Words That Moved Wall Street: “Vera Rubin Is in Full Production”
Nvidia CEO Jensen Huang spent much of his CES keynote talking about real-world AI — from self-driving cars to robotics. But about an hour into the presentation, he delivered the line investors were waiting for:
“Vera Rubin is in full production.”
Nvidia is currently ramping its Blackwell Ultra lineup, but the company’s fast-paced annual release cycle continues. The chip giant is expected to begin shipping Vera Rubin later this year as demand for computing power keeps accelerating.
Huang said the core challenge in AI today is the explosive need for computation — and by extension, Nvidia’s hardware.
“The race is so intense,” he said, as customers push to perform more complex computing tasks at greater speed.
“Rubin arrives at exactly the right moment, as AI computing demand for both training and inference is going through the roof,” Huang added.
The Vera Rubin platform consists of six chips, including the Vera CPU, which Huang said delivers twice the performance per watt of the world’s most advanced CPUs. The platform also includes the Rubin GPU, designed for inference workloads, and a Spectrum-6 Ethernet switch — networking technology that Huang said will help power the next generation of “AI factories.”
The Vera CPU and Rubin GPU were co-designed to share data faster and reduce latency, addressing one of the biggest bottlenecks in large-scale AI systems.
Nvidia’s announcement drew high-profile praise. Tesla CEO Elon Musk said Rubin “will be a rocket engine for AI” and “is the infrastructure you use” to deploy models at scale.
Anthropic CEO Dario Amodei added that the efficiency gains from the Rubin platform will enable “longer memory, better reasoning and more reliable outputs.”
While product updates remain top of mind for investors, Huang also used much of his keynote to paint a broader vision of AI’s future — especially in what he calls physical AI, where machines and robots operate autonomously in the real world.
“The ChatGPT moment for physical AI is here — when machines begin to understand, reason and act in the real world,” Huang said.
Physical AI has been harder to develop because it requires massive real-world simulation data, but it represents a major opportunity for Nvidia as it works to automate factories, vehicles, and even humanoid robots.
Huang showcased advances in self-driving cars, humanlike robots, and AI agents capable of helping design chips. He also introduced a new lineup of open-source autonomous driving models called Alpamayo, which he said will help move the industry toward a future where “every single car” is AI-powered.
“There’s no question in my mind now that this is going to be one of the largest robotics industries,” Huang said of autonomous driving.
He noted that true self-driving depends on reasoning, because it’s impossible to preprogram every possible scenario on the road. Instead, those situations can be broken down into smaller problems that AI systems can learn to reason through.
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