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What Is AI Infrastructure?

What Is AI Infrastructure?

AI infrastructure refers to the technology stack (both hardware and software) needed to build, test, train, and deploy AI-powered apps. From GPUs to scale-out flash to data fabrics, competing in the ever-evolving world of AI requires a continuous investment in the latest data technologies.

Anatomy of an AI Technology Stack

When developing AI-powered applications at the enterprise level, it’s important to have a clear understanding of all the layers that make up your AI infrastructure. Here’s an example of what an AI technology stack might look like:

  • Scale-out file and object protocols (e.g., Pure Storage® Purity//FB)
  • Scale-out flash storage (e.g., Pure Storage FlashBlade®)
  • Deep learning frameworks like TensorFlow
  • Containers (e.g., GPU-optimised Docker)
  • Scale-out GPU compute hardware (e.g., NVIDIA DGX A100 with Tensor Core GPUs

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Why Use AIRI for Your AI Infrastructure?

The process of scaling your AI infrastructure from pilot lab to production can easily turn into a costly and time-consuming exercise in DIY-engineering. You might spend months building racks of GPUs, troubleshooting the bottlenecks of legacy storage systems, and finessing open-source software into commodity hardware.

Pure Storage teamed up with NVIDIA to create AIRI®, the world’s first full-stack AI-ready infrastructure. By combining NVIDIA’s DGX A100 servers with Pure’s FlashBlade arrays, AIRI provides a scalable AI solution that’s big, fast, and efficient.

Core benefits of AIRI include:

  • A single integrated platform for all AI workloads
  • Massively parallel scale-out processing power with flash storage to match
  • Remote direct memory access (RDMA) fabric for moving big data fast
  • Scalable AI infrastructure that’s easy to set up, upgrade, and manage 

With AIRI, you get an enterprise-ready AI technology stack upon which you can host machine learning algorithms and AI-powered applications.

11/2025
Scale AI from Pilot to Production Guide
Learn how to overcome AI scaling challenges. Get practical strategies for data readiness, infrastructure modernization, and building your AI factory.
Ebook
12 pages

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