NVIDIA sets the stage for the future of AI

Source: NVIDIA. Huang unveiled the Vera Rubin platform during the keynote.

NVIDIA's annual GTC conference covers every layer of the five-layer AI "cake": compute, memory, storage, networking and security. In his keynote, Jensen Huang, CEO, NVIDIA, first marked the 20th anniversary of CUDA — describing it as the “flywheel” driving accelerated computing and the platform that supports “every single phase of the AI lifecycle.”

Huang then described NVIDIA as “the house that GeForce made”. He linked GeForce's evolution to AI, then introduced DLSS 5, launching a video showing how 3D-guided neural rendering enables real-time, photoreal 4K performance on local hardware.

Next, Huang walked through the data processing landscape and observed how processing is being accelerated for the era of AI. He also shared how IBM, Dell, Google Cloud, AWS, Microsoft Azure, Oracle and CoreWeave are now serving their customers.

Next on, Huang surveyed the accelerated computing ecosystem, which now includes increasingly mature automotive, financial services, healthcare, industrial, media, quantum, retail, robotics and telecom components.

“All of these different vectors of AI have platforms that NVIDIA provides,” Huang said, highlighting NVIDIA’s broad range of CUDA-X libraries, which he described as the “crown jewels” of the company.

Huang said demand for NVIDIA GPUs is “off the charts” as a result of the growth of AI-native companies like OpenAI. “I believe computing demand has increased by 1 million times over the last few years,” he said, and predicted at least US$1 T in revenue from 2025 through 2027.

Huang also noted that NVIDIA’s token cost is the best in the world. “This is the incredible power of extreme codesign,” Huang said, referencing a process where software and silicon are designed in tandem.

The approach has also influenced the full-stack computing roadmap. NVIDIA Vera Rubin is a new full-stack computing platform comprising seven chips, five rack-scale systems and one supercomputer for agentic AI. The platform includes the new NVIDIA Vera CPU and BlueField-4 STX storage architecture.

“When we think Vera Rubin, we think the entire system, vertically integrated, complete with software, extended end to end, optimised as one giant system,” Huang said.

NVIDIA’s next major architecture is Feynman, named after physicist Richard Feynman. It will include a new CPU, NVIDIA Rosa, named for Rosalind Franklin, Huang said, whose X‑ray crystallography revealed the structure of DNA and reshaped modern biology. As Franklin exposed the hidden architecture of life, Rosa is built to move data, tools and tokens efficiently across the full stack of agentic AI infrastructure.

Rosa anchors a new platform that pairs LP40, NVIDIA’s next‑generation language processing unit (LPU), with NVIDIA BlueField‑5 infrastructure accelerators and CX10 network accelerators, connected through NVIDIA Kyber for both copper and co‑packaged optics scale‑up, and NVIDIA Spectrum‑class optical scale‑out, Huang said. Kyber is NVIDIA's rack platform, and Spectrum is a networking platform.

To help accelerate the scale-out of new AI capacity, Huang announced the NVIDIA Vera Rubin DSX AI Factory reference design and the NVIDIA Omniverse DSX Blueprint. DSX Air, part of the broader DSX platform, lets companies simulate AI factories in software before building them in the physical world.

NVIDIA has further set its sights on space. The new Vera Rubin architecture not only honours the astronomer whose work revealed dark matter, but also heralds systems like NVIDIA Space-1 Vera Rubin, systems that are designed to bring AI data centres into orbit.

NVIDIA is further announcing support for OpenClaw across its platform, making it easier for developers to safely build, deploy and accelerate AI agents on NVIDIA‑powered infrastructure. "OpenClaw has open sourced the operating system of agentic computers … Now, OpenClaw has made it possible for us to create personal agents,” Huang said.

Every company in the world must have an OpenClaw strategy, Huang said. To ensure this technology can be deployed securely inside enterprises, Huang introduced the NVIDIA OpenShell runtime and the NVIDIA NemoClaw stack — combining policy enforcement, network guardrails and privacy routing. These technologies can serve as “the policy engine of all the SaaS companies in the world,” Huang said. SaaS stands for software-as-a-service.

In addition, NVIDIA is expanding its open model ecosystem with a new Nemotron coalition, rallying partners around six frontier model families: NVIDIA Nemotron (language and reasoning), NVIDIA Cosmos (world and vision), NVIDIA Isaac GR00T (general‑purpose robotics), NVIDIA Alpaymayo (autonomous driving), NVIDIA BioNeMo (biology and chemistry) and NVIDIA Earth‑2 (weather and climate).

Physical AI - AI that can navigate the real world - is also evolving. Huang said NVIDIA’s robotaxi‑ready platform is drawing new automaker partners, including BYD, Hyundai, Nissan and Geely. He also highlighted a partnership with Uber to deploy these vehicles into its ride‑hailing network.

Beyond automakers, NVIDIA is working with industrial software giants and robotics leaders such as ABB, Universal Robots and KUKA to integrate its physical AI models and simulation tools, enabling deployment of smarter robots on manufacturing lines, and with telecom providers like T‑Mobile as base stations evolve into edge AI platforms.

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Watch the keynote at https://youtu.be/1eCAXNgw2Wg

Hashtags: #GTC, #GTC2026