Infrastructure requirements for AI adoption at scale

Artificial Intelligence Series

Session 1 of 4

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As enterprises increase their use of AI, they face many challenges, including workload scalability and data availability. Now you can fully realize the promise of ML and DL by simplifying, accelerating, and integrating your data pipeline with NetApp and NVIDIA. Learn how the NetApp Data Science toolkit enables data scientists and data engineers to provision, destroy, clone, and snapshot data volumes in seconds. Hear how the NetApp AI portfolio delivers efficient and scalable performance for the most demanding ML/DL workloads.

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Key takeaways

  • Improve your models—we help you create an end-to-end pipeline with 6-9x faster model training
  • Enable seamless hybrid cloud AI training and inferencing
  • Bring your data where your data scientist resides and let them seamlessly collaborate
  • Get a faster ROI from your AI investments
  • Faster results by eliminating days and months of configuration, support and other non-data science essential tasks
  • Future proof—protect your investment, start small with a POC and scale efficiently and limitless
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Speaker bio by region

Meet the specialists ready to help simplify your data challenges. Expect to dive into real-world, industry-specific questions—they’re experts who love to talk shop.


Ray White

Pursuit Business Development Manager

Ray's LinkedIn

Dan Holmay

Global AI Pursuit Business Development Manager

Dan's LinkedIn

Tony Paikeday

NVIDIA l Sr Director Product Marketing l AI Systems

Tony's LinkedIn

EBC Solution Series

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