In today’s market, organizations that fail to invest in forward-looking AI infrastructure risk being left behind as the race to support more complex workflows accelerates.

But as demand for real-time data processing and super-intelligence hits a fever pitch, the next generation of applied AI applications, from advanced robotics to large-scale autonomous agents, requires a total paradigm shift. That pressure is prompting organizations to rethink how they build and scale their underlying systems, according to Sam Khosroshahi (pictured), vice president of strategy at Lambda Inc., an Nvidia Corp.-powered AI infrastructure company.

“Lambda obsesses over this because we have a research organization that works to test out and benchmark a variety of things running on our infrastructure that’s powered by Nvidia,” Khosroshahi said. “It’s not just about deploying the infrastructure … It’s about tuning it so that it’s driving the performance.”

Khosroshahi spoke with theCUBE’s John Furrier at the Nvidia GTC AI Conference & Expo, for an exclusive interview on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the evolution of the AI factory and strategic investments in the supply chain. (* Disclosure below.)

Scaling AI infrastructure with liquid cooling and photonics

As businesses transition from traditional setups to high-density AI factories, the technical requirements are becoming significantly more demanding. One major shift is in networking, where the move toward the Nvidia Vera Rubin architecture is eliminating dependencies on traditional copper connections, Khosroshahi explained.

“We are talking about taking co-packaged optical and photonics on the backend to accelerate the network and not have the dependency on copper,” Khosroshahi said. “You’re starting to see the speed of light is coming into fruition.”

To support these massive workloads, Lambda is helping customers deploy gigawatt-scale campuses. This scale is necessary because the agentic era requires instantaneous processing to be effective, Khosroshahi noted, adding that Lambda focuses on providing the machine learning engineering expertise needed to help customers accelerate their path to the other side of this technological transformation.

“These investments will pay off over the long term for organizations that really lean in,” Khosroshahi said. “We focus on deploying the best infrastructure and supporting that infrastructure and aiding customers through our applied AI teams, our machine learning engineers that are here and speaking with customers live, to get them to accelerate their path to agentic or a variety of other outcomes.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Nvidia GTC AI Conference & Expo:

(* Disclosure: TheCUBE is a paid media partner for the Nvidia GTC AI Conference & Expo. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE