Nvidia and VMware Join Forces on AI Hybrid Cloud Platform

By AI Business

Nvidia is expanding its collaboration with VMware to enable faster deployments of AI solutions in the latter’s hybrid cloud platform.

Nvidia’s AI Enterprise Suite has now been integrated into the VMware Cloud Foundation (VCF) 4.4 platform. The pair have been actively collaborating for the past two years, unveiling an AI Enterprise software suite last March.

The inclusion of the AI Enterprise Suite enables IT professionals to use the same tools for AI as the ones they use to manage data centers and hybrid cloud environments. Nvidia has said that AI Enterprise cuts down the AI development time by 90 percent — from 80 weeks to eight weeks.

This latest collaboration for VMware Cloud Foundation (VCF) 4.4 supports “flexible and easily scalable AI-ready infrastructure.”

“Performance gains are realized through the raw power of Nvidia Ampere architecture GPUs while providing a platform that scales to meet the demands of development and production workloads,” Rick Walsworth, director of product marketing at VMware wrote in a blog post.

“This enables data scientists and researchers to build AI-ready infrastructure as it’s needed.”

The Cloud Foundation (VCF) 4.4 platform contains pre-trained models and pre-built sets of AI software enabling data scientists to develop and deploy apps.

VMware suggests that the Nvidia integration makes it possible to deliver Kubernetes clusters to AI developer teams at a rapid pace. This addition removes friction between IT operations and lines of business when implementing AI and ML infrastructure, Walsworth wrote.

“VMware brings deep knowledge of infrastructure, operations and management, and Nvidia delivers accelerated computing expertise, GPU virtualization technology, and prebuilt sets of AI software, pre-trained models, and other tools that data scientists can use to create applications and quickly deploy them,” he said.

The collaboration news comes after Nvidia’s attempts to purchase Arm collapsed over “significant” regulatory challenges.

This article first appeared in IoT World Today’s sister publication AI Business.