The artificial intelligence pie is expanding, and niche offerings are emerging to serve particular enterprise pain points. Broadcom Inc. has made private AI its cornerstone initiative in the space, having fleshed out the platform over the past year, according to Chris Wolf (pictured), global head of AI and advanced services, VMware Cloud Foundation Division, at Broadcom.

Broadcom’s Chris Wolf unpacks private AI.

“What we were betting on was that privacy and control of data mattered to customers,” he said. “The ability to bring the AI model to wherever their data resides would matter to customers. Even last summer, we had some real insights about operating AI services in an enterprise data center because we were doing that ourselves. We saw that some of our internal services were roughly one-third the cost of comparable public cloud services.”

Wolf spoke with theCUBE Research Executuve Analyst John Furrier at the VMware Cloud Foundation Transformed event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed private AI as a leap forward in integrating AI into enterprise environments, with a focus on privacy, cost efficiency and flexibility. (* Disclosure below.)

Private AI: A functioning ecosystem to address enterprise needs

Broadcom outlined three main problem areas it set out to solve with private AI: reducing costs, strengthening privacy/data control and enabling flexibility. It teamed up with Nvidia Corp., enabling the integration of Nvidia’s powerful inference microservices with Broadcom’s infrastructure. This collaboration has spawned the Private AI Foundation, which has now become generally available and garnered traction among customers, according to Wolf.

“We said we need to take a platform approach, bet on an AI infrastructure platform that’s going to give you some optionality so that as something changes, you can quickly adopt it,” he said. “[On] one of our top internal AI services, we’ve changed the foundation model three times in the last nine months just because we keep getting better results. The platform approach is what gives you that agility, and that’s a key reason why folks are betting on us.”

Privacy and data control concerns have been key to the enterprise’s reluctance to adopt AI. By allowing AI models to operate adjacent to customer data, Broadcom addressed these concerns head-on. This approach ensures data privacy and aligns with regulatory compliance and legal requirements, making it a preferred choice for many organizations, Wolf added.

“It’s easy to say, ‘Run an AI app.’ [But] how do you automate the deployment? How do you automate beyond day two? How do you secure it? How do you add governance and controls?” he asked. “These are the real challenges that folks face. Then the other issue is, I can’t just go out and buy all this AI infrastructure. I have to figure out how to effectively use it.”

While most AI-related discourse focuses on training models, the vast majority of AI compute cycles are dedicated to inference — running already trained models. Broadcom’s platform is optimized for this, balancing resource efficiency and reliability, according to Wolf. Coupled with the ability to manage and maximize GPU infrastructure, this focus provides substantial cost savings and efficiency gains for enterprises.

“I’ll use the cloud services for training models where I need that bursty capacity,” Wolf said. “When I want to do inference workloads and just apply the AI model to an application, the cost savings are significant.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the VMware Cloud Foundation Transformed event: 

(* Disclosure: TheCUBE is a paid media partner for the VMware Cloud Foundation Transformed event. Neither VMware by Broadcom, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE