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This article was written by Krish Prasad, Senior Vice President and General Manager of VMware's Cloud Infrastructure Business Group. 

In 2023, after several decades of niche growth and development, Generative AI and AI/ML adoption have achieved mainstream status.

As AI drives tremendous productivity gains and enables new experiences, many core functions within a typical business will be transformed, including sales, marketing, software development, customer operations, and document processing.

In fact, McKinsey projects that Generative AI's impact on productivity could add the equivalent of $4.4 Trillion annually to the global economy.

But at the core of this remains the privacy of enterprises' data. Hence, in August 2023, at VMware Explore in Las Vegas, we announced VMware Private AI and VMware Private AI Foundation with NVIDIA.

Today, we are excited to announce further expansions to the VMware Private AI ecosystem with two key partners.

VMware Private AI with Intel unlocks AI for all organizations

VMware and Intel have partnered for over 20 years to enable next-generation, datacenter-to-cloud capabilities with the broadest portfolio of trusted enterprise solutions, enabling businesses to move faster, innovate more, and operate efficiently.

Today, we are extending this partnership with Intel to unlock AI everywhere for all organizations.

With this partnership, enterprises can get AI models everywhere by harnessing Intel's AI software suite validated on VMware Cloud Foundation.

VMware and Intel will help enterprises build and deploy private and secure AI models running on VMware Cloud Foundation and boost AI performance by harnessing Intel's AI software suite, 4th Generation Intel® Xeon® Scalable Processors with built-in accelerators, and Intel® Max Series GPUs.

Let's delve into the value enterprises can expect from this partnership.

  1. Enable privacy and security for AI models: VMware Private AI's architectural approach for AI services enables privacy and control of corporate data and integrated security and management. This partnership will help enterprises build and deploy private and secure AI models with integrated security capabilities in VCF and its components.
  2. Boost AI Performance– Achieve excellent AI and LLM model performance using the integrated capabilities built into VCF and Intel processors, hardware accelerators, and optimized software. For example, vSphere, one of the core components of VCF, includes Distributed Resources Scheduler, which improves AI workload management by grouping hosts into resource clusters for different applications and ensuring that VMs have access to the right amount of computing resources, preventing resource bottlenecks, and optimizing resource utilization.
  3. Get AI Everywhere – VMware and Intel are providing enterprises with a fully validated AI stack on already deployed clusters. This stack enables enterprises to do data prep, machine learning, fine-tuning, and inference optimization using Intel processors, hardware accelerators, Intel's AI software suite, and VCF across your on-premises environment.


VMware Private AI with Intel enables both Gen AI and classical AI/ML use cases. It harnesses the power of VMware Cloud Foundation and Intel's AI software suite, processors, and hardware accelerators. This architectural ecosystem brings together VMware, Intel, ML Ops providers (, Domino Data Labs, DKube, Kubeflow, etc.), major OEM server providers (such as Dell Technologies, Hewlett Packard Enterprise, and Lenovo), and Global System integrators like HCL, Kyndryl, and Wipro.

Use Cases

VMware Private AI and the collaboration with Intel enable several use cases for enterprises by securely enabling classical AI/ML and large language models, fine-tuning, and deployment (inference) within their private corporate environment. Here is a description of the top use cases.

  1. Code Generation: Enterprises can use their models without the risk of losing their IP or data and can accelerate developer velocity by enabling code generation.
  2. Contact centers resolution experience: Enterprises can fine-tune models against their internal documentation and knowledge base articles, including private support data, and, in turn, realize more efficient customer service and support with meaningful reductions in human interactions in support/service incidents.
  3. Classical Machine Learning: Classical ML models are used for a variety of real-world applications across the financial services, health and life sciences, retail, research, and manufacturing industries. Popular ML use cases include customized marketing, visual quality control in manufacturing, personalized medicine, and retail demand forecasting.
  4. Recommendation Engines: Enterprises can enhance experiences by suggesting or recommending additional products to consumers. These can be based on various criteria, including past purchases, search history, demographic information, and other factors.

VMware Private AI with IBM brings watsonx to on-premises environments

IBM and VMware are building on VMware Private AI to enable enterprises to access IBM watsonx in private, on-premises environments and hybrid cloud for the secure training and fine-tuning their models with the watsonx platform. The strategic partnership between IBM and VMware aims to enable mutual clients to easily embrace the hybrid cloud and modernize their mission-critical workloads. Now, by having the choice of when, where, and how to integrate GenAI technologies with VMware Cloud Foundation, enterprises will be empowered to quickly train and deploy custom AI capabilities across their enterprise while retaining full control and compliance over their data. With this partnership on AI technologies between VMware and IBM, enterprises benefit from a powerful solution leveraging the best innovations from VMware's on-premises offerings in a unified stack to deliver a consistent environment integrated with the data and AI capabilities brought by IBM Cloud partner technology.

  1. Get private and secure AI models with VMware Private AI: Privacy and security are paramount to enterprises. Enterprises can now build their private and secure AI models with VMware Private AI with IBM using the several integrated privacy, security, and micro-segmentation capabilities in VCF.
  2. Deploy AI/ML models on-premises and in the cloud: This partnership enables enterprises to train, validate, tune, and deploy private and secure AI/ML models on-premises and on the IBM Cloud.
  3. Select your option of open-source or IBM proprietary models: This partnership allows enterprises to choose LLMs by providing access to IBM-selected open-source models from Hugging Face, third-party models, and a family of IBM-trained foundation models. Here are a few examples of the supported models available with
    • Open-source models: Llama 2 (70b)
    • 3rd party models: StarCoder (15.5b)
    • Proprietary IBM models: Granite (13b)


This full-stack architecture built on VMware Cloud Foundation runs Red Hat OpenShift and pairs the capabilities of the IBM watsonx platform for Gen AI and classical AI/ML-based workloads and enterprise-grade security. With this architecture, enterprises can use for accessing IBM-selected open-source models from Hugging Face, as well as other third-party models and a family of IBM-trained foundation models to support GenAI use cases and for classical AI/ML model training, validation, tuning, and deployment.

Use Cases

VMware Private AI with IBM can enable several use cases for enterprises by securely enabling large language models' customization, fine-tuning, and deployment (inference) within their private corporate environment. In the domain of code generation, the focus is on accelerating developer productivity while addressing critical concerns surrounding privacy and intellectual property. Moreover, VMware Private AI, in collaboration with IBM, presents a significant opportunity to enhance contact center interactions. This partnership promises improved content and feedback quality for customers, resulting in more accurate responses and an overall enhanced customer experience. This partnership can significantly streamline IT operations by automating tasks like incident management, reporting, ticketing, and monitoring, ultimately saving time and effort for IT operations agents. Finally, advanced information retrieval capabilities brought about by this collaboration can elevate employee productivity by streamlining document search and policy research, fostering a more productive work environment.

IBM Consulting Provides Clients with Expertise in VMware-specific solutions and Generative AI

Earlier this year, IBM Consulting established a Center of Excellence for generative AI and now has more than 1,000 consultants with specialized generative AI expertise who are engaging with a global set of clients to drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models.

This, combined with IBM's VMware-specific expertise and service capabilities, will help accelerate our client's business transformations with enterprise-grade AI on the VMware Private AI reference architecture.

Additionally, for clients looking to modernize & transform their workloads, IBM Consulting plans to integrate IBM watsonx and VMware Private AI services into its proprietary IBM Consulting Cloud Accelerator to help accelerate the cloud transformation process. Once released, this integration helps with reverse engineering, code generation, and conversion while helping manage the day two operations and beyond for seamless Hybrid Cloud management services from IBM Consulting.

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