Private AI is the fastest growing new product with which I have been associated in my career, remarked Chris Wolf, Global Head of AI and Advanced Services, VMware Cloud Foundation Division, Broadcom, while addressing a briefing at Explore’24 in Las Vegas on Tuesday.
He noted that the company is seeing tremendous customer adoption, particularly in financial services and public sector verticals.
“We are really seeing good traction in retail, oil and gas and manufacturing as well,” he said. However, he expressed concerns regarding the healthcare sector’s adoption, which has been slower due to regulatory matters.
In the briefing, Wolf touched upon the use cases of Private AI with particular emphasis on contact centre resolution and noted its effectiveness in handling private customer support data.
“Economically, we found customers see a lot of cost savings running these inference-type workloads compared to a public cloud service,” he said. He also pointed out the benefit of quicker access to information and the resultant efficiency gains. He attributed the efficiency improvement to using an open-source model as the foundation.’
Wolf also stressed the unique advantage of resource sharing and distributed resource scheduling, which he claimed is unmatched in the industry. He also shared his experience meeting with AI leaders at major banks and retailers, where their resource management capabilities were highly appreciated.
Wolf appreciated the Indian engineers and said they are “actively driving” the company’s AI agenda.
“A significant proportion of the features in the keynote today have been developed by on of my engineering teams in India and they have been doing it quite well,” he said.
He added that the team is also partnering with their field teams to help the first customers in India see value from the platform.
The company's approach to private AI was first unveiled at Explore’23 in Vegas. It was described as a powerful architectural approach that could provide customers with the benefits of AI without compromising data control, privacy, and compliance.
In his note, earlier in the day, Wolf mentioned that the starting costs for AI turned out to be far less than they thought.
“When we started moving services to production, we found that we had a far lower cost running AI inferencing services in our data centres. This, in turn, had a direct impact on our AI product strategy and roadmap,” he noted.
