VMware Private AI with Intel will deliver the transformative power of Artificial Intelligence through superior privacy, security, performance, scale and TCO
More than 300,000 customers deploy VMware Cloud globally, and VMware virtualization software is deployed nearly everywhere in the enterprise where data is created, processed, or consumed. This makes VMware Cloud a fast means to bring AI-accelerated compute and models to wherever business gets done. Similarly, Intel offers open, scalable and trusted solutions to hundreds of thousands of customers. The ubiquity of VMware and Intel products in the enterprise is a powerful combination which will increase the accessibility of data science, and enable organizations globally to adopt Private AI, an architectural approach that aims to balance the business gains from AI with the practical privacy and compliance needs.
“When it comes to AI, there is no longer any reason to debate trade-offs in choice, privacy, and control. Private AI empowers customers with all three, enabling them to accelerate AI adoption while future-proofing their AI infrastructure,” said Chris Wolf, vice president of VMware AI Labs. “VMware Private AI with Intel will help our mutual customers dramatically increase worker productivity, ignite transformation across major business functions, and drive economic impact.”
“For decades, Intel and VMware have delivered next-generation data center-to-cloud capabilities that enable customers to move faster, innovate more, and operate efficiently,” said Sandra Rivera, executive vice president and general manager of the Data Center and AI Group (DCAI) at Intel. “With the potential of artificial intelligence to unlock powerful new possibilities and improve the life of every person on the planet, Intel and VMware are well equipped to lead enterprises into this new era of AI, powered by silicon and software.”
Boost AI Performance and get a More Secure AI Infrastructure with Lower TCO
VMware Private AI brings compute capacity and AI models to where enterprise data is created, processed, and consumed, whether in a public cloud, enterprise data center, or at the edge, in support of traditional AI/ML workloads and generative AI. VMware and Intel are enabling the fine-tuning of task specific models in minutes to hours and the inferencing of large language models at faster than human communication using the customer’s private corporate data. VMware and Intel now make it possible to fine-tune smaller, economical state of the art models which are easier to update and maintain on shared virtual systems, which can then be delivered back to the IT resource pool when the batch AI jobs are complete. Use cases such as AI-assisted code generation, experiential customer service centers recommendation systems, and classical machine statistical analytics can now be co-located on the same general purpose servers running the application.
VMware and Intel are designing a reference architecture that combines Intel’s AI software suite, Intel® Xeon® processors, and Data Center GPUs with VMware Cloud Foundation to enable customers to build and deploy private AI models on the infrastructure they have, thereby reducing total cost of ownership and addressing concerns of environmental sustainability. This VMware Private AI reference architecture with Intel AI will include:
- 4th Gen Intel® Xeon® processors with Intel® Advanced Matrix Extensions (Intel® AMX) deliver up to 10x significant out-of-box performance improvements using standard industry frameworks and libraries, end-to-end data science productivity tools, and optimized AI models.
- Intel® Data Center GPU Max contains up to 128 Xe cores and is Intel’s foundational GPU compute building block targeted at the most demanding AI workloads. Intel Max Series GPUs will be available in several form factors to address different customer needs.
- Intel’s AI software suite is packaged with end-to-end open source software and optional licensing components to enable developers to run full AI pipeline workflows from data preparation to fine-tuning to inference, accelerate building multi-node scaling and deploying AI on enterprise IT infrastructure. The open oneAPI framework enables processors and hardware accelerator-agnostic software development, allowing developers to write code once and run it across different architectures, eliminating the need for multiple code bases and specialized languages. Intel’s Transformer Extensions and PyTorch Extension’s deep integration with developer favorite open source Hugging Face libraries provide automated optimization recipes for fine-tuning and compressing models for efficient inference.
SOURCE: BusinessWire
