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Iguazio, McKinsey, and the Future of MLOps

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Manage episode 405906770 series 2548283
Content provided by EM360. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by EM360 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://player.fm/legal.

From the rise of generative AI to the EU AI Act, it’s been a particularly explosive year in the AI and ML space.

With most industry surveys pointing to bringing in some form of AI as the biggest priority for companies looking to level up their tech stack in 2024 - what challenges and trends need to be addressed before creating and honing that MLOps strategy?

In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Yaron Haviv, Founder and CTO at Iguazio (recently acquired by McKinsey) as they discuss:

  • The current AI landscape
  • Implementing AI and ML - in the right way
  • How scalable is MLOps?

  continue reading

211 episodes

Artwork
iconShare
 
Manage episode 405906770 series 2548283
Content provided by EM360. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by EM360 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://player.fm/legal.

From the rise of generative AI to the EU AI Act, it’s been a particularly explosive year in the AI and ML space.

With most industry surveys pointing to bringing in some form of AI as the biggest priority for companies looking to level up their tech stack in 2024 - what challenges and trends need to be addressed before creating and honing that MLOps strategy?

In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Yaron Haviv, Founder and CTO at Iguazio (recently acquired by McKinsey) as they discuss:

  • The current AI landscape
  • Implementing AI and ML - in the right way
  • How scalable is MLOps?

  continue reading

211 episodes

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