Launching a strategic AI program can be a daunting prospect, but companies like DDN and NVIDIA are working together to solve the problem and help organizations create an AI Center of Excellence. In a recent interview with Tony Paikeday, NVIDIA’s Senior Director of Product Marketing, AI Systems, we discussed how virtually all industries are now using AI to optimize supply chains, reduce cost, and deliver better business outcomes.

The biggest challenge for forward-looking enterprises is that AI can be a challenge to deploy at scale without the right tools, skills and infrastructure. This is why DDN and NVIDIA have been working together to help businesses put together the right AI infrastructure and platform to get AI models into production faster.

We understand the problems that organizations often encounter when talking about AI infrastructure, such as eliminating the complexity of design, making deployment simpler, and integrating with other key business systems. We have created joint reference architectures and fully baked turnkey solutions, which eliminate the guesswork and complexity of architecting an AI storage fabric, compute backplanes, application scheduling and resource management.

NVIDIA builds and consumes AI infrastructure to support its own internal business and product teams – thousands of developers around the world use NVIDIA’s AI infrastructure every day, and the NVIDIA DGX SuperPOD™ architecture with DDN storage is the direct result of what NVIDIA and DDN have learned from building and using AI infrastructure together.

As Tony says, DGX SuperPOD was born out of NVIDIA’s own journey when they first started putting together infrastructure to support their own research and development, and today it has become NVIDIA’s flagship platform for AI and HPC workloads. NVIDIA’s own experience of cluster design, fabric interconnect, integrated software, and their AI vision were built into a turnkey solution, with an architecture which is proven in production.

DDN’s optimized AI storage is a key component of DGX SuperPOD, as it provides the high-performance storage necessary for AI workloads. With DDN’s storage technology, NVIDIA can achieve the extreme levels of performance required for the largest AI workloads, while also ensuring data reliability and availability.

For enterprises to succeed with their AI strategy, there are three key things to focus on:

  1. First, they need tools that can give their developers a jump start on model development, including pre-trained models that can be fine-tuned to fit the specific problem or business vocabulary.
  2. Second, enterprises need a scalable and energy-efficient platform that can handle complex AI models, particularly large language models, recommender systems and graph computation.
  3. Finally, enterprises should consider building an AI Center of Excellence to centralize and consolidate their resources and expertise, and to encourage cross-functional collaboration. Such a shared AI platform can provide much greater investment return, and accelerate the adoption of AI across the organization.

The collaboration between NVIDIA and DDN has been crucial in enabling organizations to build and deploy high-performance AI infrastructure. With DGX SuperPOD, NVIDIA and DDN are making it easier for organizations to access the technology necessary to drive their AI initiatives forward.

Ready to take your enterprise’s AI infrastructure to the next level? Contact NVIDIA and DDN today to learn more about how NVIDIA DGX SuperPOD with DDN A³I storage can help accelerate your AI projects and drive business success. Watch the full conversation here.

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