Introduction to VMware Private AI

VMware Private AI brings compute capacity and AI models to where enterprise data is created, processed, and consumed, whether that is in a public cloud, enterprise data center, or at the edge. VMware Private AI consists of both product offerings (VMware Private AI Foundation with NVIDIA) and a VMware Private AI Reference Architecture for Open Source to help customers achieve their desired AI outcomes by supporting best-in-class open source software (OSS) technologies today and in the future. VMware’s interconnected and open ecosystem supports flexibility and choice in customers’ AI strategies.

Chris Wolf, the Global Head of AI and Advanced Services at VMware by Broadcom, discusses VMware’s Private AI initiative, which was announced in August 2023. The goal of Private AI is to democratize general AI and ignite business innovation across all enterprises while addressing privacy and control concerns. VMware focuses on providing AI infrastructure, optimizations, security, data privacy, and data serving, leaving higher-level AI services to AI ISVs (Independent Software Vendors). This non-competitive approach makes it easier for VMware to partner with ISVs since VMware does not directly compete with them in offering top-level AI services, unlike public clouds.

Wolf shares an example of VMware’s code generation use case with a 92% acceptance rate by software engineers using an internal solution based on an open-source model for the ESXi kernel. He discusses the importance of governance and compliance, particularly in AI-generated code, and mentions VMware’s AI council and governance practices.

He highlights use cases such as call center resolution and advanced information retrieval across various industries. VMware’s solution emphasizes flexibility, choice of hardware and software, simplifying deployment, and mitigating risks. Wolf also notes VMware’s capability to stand up an AI cluster with preloaded models in about three seconds, which is not possible in public clouds or on bare metal.

The discussion covers the advantages of VMware Private AI in managing multiple AI projects within large enterprises, including efficient resource utilization and integration with existing operational tools, leading to lower total cost of ownership.

Wolf touches on the trend of AI adoption at the edge, the importance of security features within VMware’s stack, and the curated ecosystem of partners that VMware is building. He points out that VMware’s Private AI solution can leverage existing IT investments by bringing AI models to where the data already resides, such as on VMware Cloud Foundation (VCF).

Finally, Wolf previews upcoming Tech Field Day sessions that will go into detail about VMware’s collaborations with NVIDIA, Intel, and IBM, showcasing solutions like Private AI Foundation with NVIDIA and WatsonX SaaS service deployment on-premises. He encourages attendees to participate in these sessions to learn more about VMware’s AI offerings.