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SPOTLIGHT. Moving Enterprise AI Applications From Experiments to Production with NetApp

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Manage episode 509310797 series 1204875
Content provided by Tech Field Day. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tech Field Day 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.

More information on NetApp Insight

Running enterprise applications in production is a lot different from the AI experiments many of us have been involved with so far. This episode of the Tech Field Day podcast, recorded prior to NetApp Insight 2025, features Ingo Fuchs from NetApp along with Gina Rosenthal, Glenn Dekhayser, and Stephen Foskett. AI applications often start as experiments with a limited data set, but once these are moved to production there are many critical decisions to be made. Data must be classified and cleaned, removing personal and financial data and proprietary information before it even reaches an LLM. Data also must be structured for embedding and vectorization prior to use by an LLM. And we have to ensure that data is up to date or the application will not serve the customer properly. Finally we have to consider whether it is proper and ethical to share and act on this data. Many of the challenges facing modern AI applications are similar to the historic issues faced by enterprise storage, and this is an area in which NetApp and their customers have decades of experience.

NetApp Representative: Ingo Fuchs, Chief Technologist of AI at NetApp

Host:

Stephen Foskett, President and Organizer of Tech Field Day

Gina Rosenthal, Principal Product Marketing Manager, Digital Sunshine Solutions

Glenn Dekhayser, Global Principal Technologist at Equinix

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Follow ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more information on upcoming and current event coverage ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠visit our website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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329 episodes

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Manage episode 509310797 series 1204875
Content provided by Tech Field Day. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tech Field Day 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.

More information on NetApp Insight

Running enterprise applications in production is a lot different from the AI experiments many of us have been involved with so far. This episode of the Tech Field Day podcast, recorded prior to NetApp Insight 2025, features Ingo Fuchs from NetApp along with Gina Rosenthal, Glenn Dekhayser, and Stephen Foskett. AI applications often start as experiments with a limited data set, but once these are moved to production there are many critical decisions to be made. Data must be classified and cleaned, removing personal and financial data and proprietary information before it even reaches an LLM. Data also must be structured for embedding and vectorization prior to use by an LLM. And we have to ensure that data is up to date or the application will not serve the customer properly. Finally we have to consider whether it is proper and ethical to share and act on this data. Many of the challenges facing modern AI applications are similar to the historic issues faced by enterprise storage, and this is an area in which NetApp and their customers have decades of experience.

NetApp Representative: Ingo Fuchs, Chief Technologist of AI at NetApp

Host:

Stephen Foskett, President and Organizer of Tech Field Day

Gina Rosenthal, Principal Product Marketing Manager, Digital Sunshine Solutions

Glenn Dekhayser, Global Principal Technologist at Equinix

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Follow ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more information on upcoming and current event coverage ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠visit our website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

  continue reading

329 episodes

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