{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Tech on the Rocks","title":"Optimizing SQL with LLMs: Building Verified AI Systems at Espresso AI with Ben Lerner","html":"","width":"100%","height":180,"duration":3964,"description":"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. \nWe explore his experience at companies like Uber and Google, where he worked on everything from distributed systems to ML and storage infrastructure. \nWe 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. \nBen 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.\nChapters\n00:00 Ben's Journey: From Startups to Big Tech\n13:00 The Importance of Timing in Entrepreneurship\n19:22 Consulting Insights: Learning from Clients\n23:32 Transitioning to Big Tech: Experiences at Uber and Google\n30:58 The Future of AI: End-to-End Systems and Data Utilization\n35:53 Transitioning Between Domains: From ML to Distributed Systems\n44:24 Espresso's Mission: Optimizing SQL with ML\n51:26 The Future of Code Optimization and AI","thumbnail_url":"https://img.transistorcdn.com/UA-KG4zXoEeEh4XuiVMdD9yAhMnDJ2YVfAhHWI5inpc/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80ZWI0/YjY4MDc1YmU2MDI0/MTNkNjYwZWYwYzky/ZGEyNi5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}