Feature Platforms for Data-Centric AI with Mike Del Balso - #577

2022-06-06 · 46 min · episode 577 · 13 entities

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→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast

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Feature Platforms for Data-Centric AI with Mike Del Balso - #577
→ hosted by Sam Charrington person

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→ discusses Science concept

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→ discusses Technology company

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Feed category: Tech News
→ hosted by TWIML company

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Feed author/publisher: TWIML

Entities found in this episode

concepts 5

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mentioned Tech News concept

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Feed category: Tech News
discusses Science concept

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Feed category: Science
discusses News concept

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Feed category: News
discusses Tech News concept

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Feed category: Tech News

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mentioned TWIML company

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Feed author/publisher: TWIML
mentioned Technology company

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discusses Technology company

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hosted by TWIML company

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Feed author/publisher: TWIML

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mentioned Mike De person

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Feature Platforms for Data-Centric AI with Mike Del Balso - #577
mentioned Sam Charrington person

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evidence rules-v4
Feed author/publisher: Sam Charrington
hosted by Sam Charrington person

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evidence rules-v4
Feed author/publisher: Sam Charrington

podcasts 1

appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast

0.68 · ×2

evidence rules-v4
Feature Platforms for Data-Centric AI with Mike Del Balso - #577

Episode description as stored

In the latest installment of our Data-Centric AI series, we’re joined by a friend of the show Mike Del Balso, Co-founder and CEO of Tecton. If you’ve heard any of our other conversations with Mike, you know we spend a lot of time discussing feature stores, or as he now refers to them, feature platforms. We explore the current complexity of data infrastructure broadly and how that has changed over the last five years, as well as the maturation of streaming data platforms. We discuss the wide vs deep paradox that exists around ML tooling, and the idea around the “ML Flywheel”, a strategy that leverages data to accelerate machine learning. Finally, we spend time discussing internal ML team construction, some of the challenges that organizations face when building their ML platforms teams, and how they can avoid the pitfalls as they arise. The complete show notes for this episode can be found at twimlai.com/go/577