Feature Stores for MLOps with Mike del Balso - #420

Feature Stores for MLOps with Mike del Balso - #420

Today we’re joined by Mike del Balso, co-Founder and CEO of Tecton. Mike, who you might remember from our last conversation on the podcast, was a foundational member of the Uber team that created their ML platform, Michelangelo. Since his departure from the company in 2018, he has been busy building up Tecton, and their enterprise feature store. In our conversation, Mike walks us through why he chose to focus on the feature store aspects of the machine learning platform, the journey, personal and otherwise, to operationalizing machine learning, and the capabilities that more mature platforms teams tend to look for or need to build. We also explore the differences between standalone components and feature stores, if organizations are taking their existing databases and building feature stores with them, and what a dynamic, always available feature store looks like in deployment. Finally, we explore what sets Tecton apart from other vendors in this space, including enterprise cloud providers who are throwing their hat in the ring. The complete show notes for this episode can be found at twimlai.com/go/420. Thanks to our friends at Tecton for sponsoring this episode of the podcast! Find out more about what they're up to at tecton.ai.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(798)

Your Ranking Model Is Optimizing the Wrong Thing with Zoe Weil - #780

Your Ranking Model Is Optimizing the Wrong Thing with Zoe Weil - #780

In this episode, Zoe Weil, co-founder and CEO of Sequen, joins us to discuss how ranking systems can use live behavioral signals to optimize for purchases rather than clicks or search relevance alone....

15 Okt 52min

Why Jev Is Changing How We Build With AI with Diogo Almeida - #779

Why Jev Is Changing How We Build With AI with Diogo Almeida - #779

In this episode, Diogo Almeida, co-founder and CEO of TypeSafe, joins us to discuss Jev, TypeSafe’s recently released model for bringing fast, reliable intelligence directly into software. We explore ...

6 Okt 1h 30min

From Math Olympiads to Navier-Stokes: How Fast Is AI Progressing? with Greg Burnham - #778

From Math Olympiads to Navier-Stokes: How Fast Is AI Progressing? with Greg Burnham - #778

AI systems have gone from struggling with grade-school math to helping solve research problems that have resisted mathematicians for decades, including Navier-Stokes. In this episode, Greg Burnham, w...

29 Sep 1h 7min

From Voice Agents to AI Avatars with Alexander Smola - #777

From Voice Agents to AI Avatars with Alexander Smola - #777

Voice AI has gotten remarkably good, but natural conversation remains a high bar. Small delays, awkward interruptions, or the wrong tone can quickly break the illusion—and adding vision and visual pre...

17 Sep 1h 4min

Do AI Tokenomics Matter More Than Model Benchmarks? with Chris Potts - #776

Do AI Tokenomics Matter More Than Model Benchmarks? with Chris Potts - #776

As reasoning models consume more tokens and AI systems become more expensive to run, understanding what those tokens actually buy is becoming increasingly important. In this episode, Stanford professo...

9 Sep 59min

World Models and the Future of Spatial AI with Justin Johnson - #775

World Models and the Future of Spatial AI with Justin Johnson - #775

In this episode, Justin Johnson, co-founder of World Labs, joins us to discuss world models and the emerging field of spatial AI. We explore why many researchers see capabilities beyond language as an...

1 Sep 1h 6min

Why the Next AI Breakthrough May Come from Physics with Max Welling - #774

Why the Next AI Breakthrough May Come from Physics with Max Welling - #774

The conventional wisdom in AI is that the next breakthrough will come from more compute, more data, and larger models. But what if the next leap comes from somewhere else? In this episode, Max Wellin...

26 Aug 58min

Why Image Generation Needs More Than Bigger Models with Fatih Porikli - #773

Why Image Generation Needs More Than Bigger Models with Fatih Porikli - #773

Text-to-image models have become remarkably good at producing realistic images. But realism isn’t the same as correctness. Ask for several distinct people, a specific composition, or a high-resolution...

12 Aug 56min

Populært innen Politikk og nyheter

giver-og-gjengen-vg
aftenpodden
aftenpodden-usa
popradet
forklart
stopp-verden
fotballpodden-2
det-store-bildet
rss-gukild-johaug
rss-espen-lee-usensurert
hanna-de-heldige
dine-penger-pengeradet
rss-ness
nokon-ma-ga
aftenbla-bla
e24-podden
bt-dokumentar-2
ta-dokumentar
rss-utenrikskomiteen-med-bogen-og-grasvik
frokostshowet-pa-p5