52:06 Webinar

Take AI/ML models to production faster by bringing performance & productivity to your MLOps

According to industry analysts, more than 85% of artificial intelligence (AI) deployments never make it into production. Moving from research (using small data sets) to robust online production environments is far from trivial.
This webinar first aired on 21 April 2022
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Miroslav Klivansky

Principal Data Architect — AI & Analytics, Pure Storage

Gilad Shaham

Director of Product Management, Iguazio

According to industry analysts, more than 85% of artificial intelligence (AI) deployments never make it into production. Moving from research (using small data sets) to robust online production environments is far from trivial. Production environments need to process large amounts of real-world data and meet application performance and SLA goals. To bring AI projects from the lab to production, organisations need a production-first mindset. They also need underlying infrastructure built for scale and high performance.

In this webinar, learn how the Pure Storage and Iguazio solution can help

  • Adopt a production-first mindset and the tools to support it
  • Use scalable enterprise-grade infrastructure to host data and compute across development and production environments.
  • Implement an automated, scalable, and performant enterprise-grade MLOps platform.
  • Foster collaboration across data science, engineering, and DevOps teams by adopting the same practices and the same toolset across these teams.


We look forward to having you join Pure Storage and Iguazio for this exciting webinar!

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