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Optimizing SQL with LLMs: Building Verified AI Systems at Espresso AI with Ben Lerner
Manage episode 459126947 series 3594857
Kostas Pardalis, Nitay Joffe에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Kostas Pardalis, Nitay Joffe 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.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
22 에피소드
공유
