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The Future of Enterprise AI? AI in Production!

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Manage episode 469758867 series 3279398
Content provided by Domino Data Lab. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Lab or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
What does the near term future of Enterprise AI look like? A scramble to get valuable, cost-effective, enterprise-grade AI solutions into production, with rigorous governance at scale. If that sounds like a tall order - that’s because it is! However, large advanced organizations (yes, even outside of the tech sector) are already seeing success deploying AI solutions and we can expect the pace to accelerate rapidly in the next 1-2 years.
To find out how enterprises are gearing up for this challenge we speak with Richard Swakla, AI and ML Specialist at NetApp and get the inside scoop on the trends that are underway and the strategies organizations are putting in place to operationalize meaningful AI outcomes.
Join us as we discuss:
  • The pressure to shift from experimentation to production
  • Breaking down the data, infrastructure and organizational silos
  • Best practices for tackling governance, security and cost challenges
  • Examples of AI efficiency gains in healthcare, pharma, and beyond

  continue reading

96 episodes

Artwork
iconShare
 
Manage episode 469758867 series 3279398
Content provided by Domino Data Lab. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Lab or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
What does the near term future of Enterprise AI look like? A scramble to get valuable, cost-effective, enterprise-grade AI solutions into production, with rigorous governance at scale. If that sounds like a tall order - that’s because it is! However, large advanced organizations (yes, even outside of the tech sector) are already seeing success deploying AI solutions and we can expect the pace to accelerate rapidly in the next 1-2 years.
To find out how enterprises are gearing up for this challenge we speak with Richard Swakla, AI and ML Specialist at NetApp and get the inside scoop on the trends that are underway and the strategies organizations are putting in place to operationalize meaningful AI outcomes.
Join us as we discuss:
  • The pressure to shift from experimentation to production
  • Breaking down the data, infrastructure and organizational silos
  • Best practices for tackling governance, security and cost challenges
  • Examples of AI efficiency gains in healthcare, pharma, and beyond

  continue reading

96 episodes

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