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

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, Seek.ai 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”!Timestamps* 00:00: Intro to Sarah* 03:40: Seek.ai 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 roundShow notes* Sarah Nagy Linkedin* Seek.ai* Sarah on the dbt podcastLightning Rounds* Favorite AI Product: Stable Diffusion* Favorite AI Community: Eleuther* One year prediction: Things will move fast!* Request for Startup: Scheduling/Emails (shoutout Ipso.ai from our hackathon!)* Takeaway: Automate everything! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe