Mar 10 • 38M

From Astrophysics to AI: Building the future AI Data Stack — with Sarah Nagy of

Latent Space Podcast Ep. 3: Why AI automating your job is Good Actually

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The podcast by and for AI Engineers! We are the first place over 50k developers hear news and interviews about Software 3.0 - Foundation Models changing every domain in Code Generation, Computer Vision, Data Science, and more, directly from the founders, builders, and thinkers involved in pushing the cutting edge. Striving to give you both the definitive take on the Current Thing down to the first introduction to the tech you'll be using in the next 3 months! Guests from Databricks, Glean, Replit, Roboflow, MosaicML, UC Berkeley, OpenAI, and more.
Episode details

If Text is the Universal Interface, then Text to SQL is perhaps the killer B2B business usecase for Generative AI. You may have seen incredible demos from Perplexity AI, OSS Insights, and CensusGPT where the barrier of learning SQL and schemas goes away and you can intuitively converse with your data in natural language.

But in the multi-billion dollar data engineering industry, has emerged as the forerunner in building a conversational engine and knowledge base that truly democratizes data insights.

We’re proud to present our first remote interview with Sarah Nagy to learn how AI can help you “seek what matters”!


  • 00:00: Intro to Sarah

  • 03:40: origin

  • 05:45: Data driven vs Data backfit

  • 09:15: How Enterprises adopt AI

  • 12:55: Patents and IP Law

  • 14:05: The Semantic Layer

  • 16:35: Interfaces - Dashboards vs Chat?

  • 21:05: LLM performance and selection

  • 26:05: LLMOps and LangChain

  • 30:55: Lightning round

Show notes

Lightning Rounds

  • Favorite AI Product: Stable Diffusion

  • Favorite AI Community: Eleuther

  • One year prediction: Things will move fast!

  • Request for Startup: Scheduling/Emails (shoutout from our hackathon!)

  • Takeaway: Automate everything!