In this episode, we sat down with Bob van Luijt (https://twitter.com/bobvanluijt), the CEO of Weaviate, diving into the cutting-edge world of vector databases and their role in the AI revolution. Weaviate is an open source, AI-native vector database that helps developers create intuitive and reliable AI-powered applications. Weaviate sets itself apart with its vector search engine that integrates machine learning directly into its core, enabling more nuanced and context-aware search capabilities for AI-driven applications. This conversation explores vector databases (the core infrastructure behind generative models), the role of Retrieval-Augmented Generation (RAG), and how open source is driving commercial use cases. WEAVIATE Website - https://weaviate.io Twitter - https://twitter.com/weaviate_io Bob van Luijt (Co-Founder & Co-CEO): LinkedIn - https://www.linkedin.com/in/bobvanluijt Twitter - https://twitter.com/bobvanluijt Matt Turck: LinkedIn - https://www.linkedin.com/in/turck/ Twitter - https://twitter.com/mattturck DATA DRIVEN NYC This episode of the MAD Podcast was recorded live at Data Driven NYC, an event series organized by FirstMark Capital. The events are free and held monthly in New York, currently with the support of Foursquare. If you wish to attend and be notified of future events, please follow FirstMark on Eventbrite at https://www.eventbrite.com/o/firstmark-capital-2215570183 01:00 What is RAG? 06:20 Why is embedding models is such a hot topic right now? 08:06 What is your assessment of RAG? 09:53 Generative feedback loops 11:46 What is Hybrid Search? 15:15 What makes Weaviate special? 16:53 What about security? 17:45 Does RAG accelerated the need for real-time data? 19:27 How to define good vector database? 22:11 What do you think about general purpose databases entering the field of vector-based databases? 23:47 Interesting use cases of Weaviate 25:27 What’s your sense of the current state of the market? 26:53 Open source vs commercial product on Weaviate 29:23 How did it all get started?