VMware Private AI Foundation with NVIDIA is an AI-focused stack built on VMware Cloud Foundation that helps you run and manage GPU-enabled infrastructure in your own environment. Instead of manually piecing together hardware, drivers, and software for machine learning (ML) and AI workloads, you use VMware Cloud Foundation’s Private AI Automation Services to: - Stand up GPU-enabled machines for ML and AI workloads - Manage those resources consistently across your private cloud - Integrate with Kubernetes for AI-enabled application deployments In practice, it lets your teams treat AI infrastructure more like a standardized service inside your VMware Cloud Foundation environment, rather than a set of one-off, custom builds.

Private AI Automation Services in VMware Cloud Foundation are designed to streamline how you request and manage GPU capacity for AI and ML. Key ways it helps: - **Automated provisioning**: Instead of opening tickets and waiting for manual configuration, you can automatically provision GPU-enabled machines that are preconfigured for ML workloads. - **Catalog-based access**: Your teams can select dedicated catalog items specifically created for GPU-enabled AI workloads, so they don’t have to guess which configuration to use. - **Consistent operations**: Because everything runs on VMware Cloud Foundation, you get a consistent operational model for both traditional and AI workloads—same tools, same governance, same policies. The result is faster access to GPU resources and less time spent on low-level infrastructure tasks, so your data science and platform teams can focus more on models and applications.

VMware Private AI Foundation with NVIDIA is built to help you move faster from idea to running AI workloads in production. It supports faster AI model development and Kubernetes changes by: - **Reducing the need for retraining**: The platform is designed to help you accelerate AI model development without always having to retrain models from scratch, which can save both time and compute resources. - **Enabling rapid iteration on infrastructure**: You can more easily iterate on AI-enabled Kubernetes infrastructure changes—such as scaling GPU-backed nodes or adjusting configurations—because these capabilities are integrated into VMware Cloud Foundation’s automation services. - **Providing ready-to-use AI infrastructure**: With GPU-enabled catalog items and automated provisioning, your teams can quickly spin up the right environment for experimentation, testing, and deployment. Together, these capabilities help your organization reimagine how AI infrastructure is delivered, so your teams can iterate more frequently and bring AI-enabled features to market more efficiently.