Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by data.world. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by data.world 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.
Player FM - Podcast App
Go offline with the Player FM app!

TAKEAWAYS - How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson

5:14
 
Share
 

Archived series ("Inactive feed" status)

When? This feed was archived on September 12, 2025 05:12 (4M ago). Last successful fetch was on May 29, 2025 15:47 (7M ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 476141982 series 3585221
Content provided by data.world. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by data.world 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.

Hugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyond the initial excitement.

  continue reading

317 episodes

Artwork
iconShare
 

Archived series ("Inactive feed" status)

When? This feed was archived on September 12, 2025 05:12 (4M ago). Last successful fetch was on May 29, 2025 15:47 (7M ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 476141982 series 3585221
Content provided by data.world. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by data.world 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.

Hugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyond the initial excitement.

  continue reading

317 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Copyright 2026 | Privacy Policy | Terms of Service | | Copyright
Listen to this show while you explore
Play