Artwork

Indhold leveret af Kostas Pardalis, Nitay Joffe. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kostas Pardalis, Nitay Joffe eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Player FM - Podcast-app
Gå offline med appen Player FM !

Optimizing SQL with LLMs: Building Verified AI Systems at Espresso AI with Ben Lerner

1:06:04
 
Del
 

Manage episode 459126947 series 3594857
Indhold leveret af Kostas Pardalis, Nitay Joffe. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kostas Pardalis, Nitay Joffe eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

In this episode, we chat with Ben, founder of Espresso AI, about his journey from building Excel Python integrations to optimizing data warehouse compute costs.

We explore his experience at companies like Uber and Google, where he worked on everything from distributed systems to ML and storage infrastructure.

We learn about the evolution of his latest venture, which started as a C++ compiler optimization project and transformed into a system for optimizing Snowflake workloads using ML.

Ben shares insights about applying LLMs to SQL optimization, the challenges of verified code transformation, and the importance of formal verification in ML systems. Finally, we discuss his practical approach to choosing ML models and the critical lesson he learned about talking to users before building products.

Chapters

00:00 Ben's Journey: From Startups to Big Tech
13:00 The Importance of Timing in Entrepreneurship
19:22 Consulting Insights: Learning from Clients
23:32 Transitioning to Big Tech: Experiences at Uber and Google
30:58 The Future of AI: End-to-End Systems and Data Utilization
35:53 Transitioning Between Domains: From ML to Distributed Systems
44:24 Espresso's Mission: Optimizing SQL with ML
51:26 The Future of Code Optimization and AI

Click here to view the episode transcript.

  continue reading

16 episoder

Artwork
iconDel
 
Manage episode 459126947 series 3594857
Indhold leveret af Kostas Pardalis, Nitay Joffe. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Kostas Pardalis, Nitay Joffe eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

In this episode, we chat with Ben, founder of Espresso AI, about his journey from building Excel Python integrations to optimizing data warehouse compute costs.

We explore his experience at companies like Uber and Google, where he worked on everything from distributed systems to ML and storage infrastructure.

We learn about the evolution of his latest venture, which started as a C++ compiler optimization project and transformed into a system for optimizing Snowflake workloads using ML.

Ben shares insights about applying LLMs to SQL optimization, the challenges of verified code transformation, and the importance of formal verification in ML systems. Finally, we discuss his practical approach to choosing ML models and the critical lesson he learned about talking to users before building products.

Chapters

00:00 Ben's Journey: From Startups to Big Tech
13:00 The Importance of Timing in Entrepreneurship
19:22 Consulting Insights: Learning from Clients
23:32 Transitioning to Big Tech: Experiences at Uber and Google
30:58 The Future of AI: End-to-End Systems and Data Utilization
35:53 Transitioning Between Domains: From ML to Distributed Systems
44:24 Espresso's Mission: Optimizing SQL with ML
51:26 The Future of Code Optimization and AI

Click here to view the episode transcript.

  continue reading

16 episoder

Alle episoder

×
 
Loading …

Velkommen til 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.

 

Hurtig referencevejledning

Lyt til dette show, mens du udforsker
Afspil