This week on High Agency, Raza Habib is joined by Chroma founder Jeff Huber. They cover the evolution of vector databases in AI engineering, challenge common assumptions about RAG and share insights from Chroma's journey. Jeff shares insights from Chroma's development, including their focus on developer experience and observations about real-world usage patterns. They also get into whether or not we can expect a super AI any time soon and what is over and under hyped in the industry today.
00:00 - Introduction02:30 - Why vector databases matter for AI06:00 - Understanding embeddings and similarity search12:00 - Chroma early days15:45 - Problems with existing vector database solutions19:30 - Workload patterns in AI applications23:40 - Real-world use cases and search applications27:15 - The problem with RAG terminology31:45 - Dynamic retrieval and model interactions35:30 - Email processing and instruction management39:15 - Context windows vs vector databases42:30 - Enterprise adoption and production systems45:45 - The journey from GPT-3 to production AI48:15 - Internal vs customer-facing applications51:00 - Advice for AI engineers
--------------------------------------------------------------------------------------------------------------------------------------------------Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com
