How to Look at Your Data - Clustering Techniques and Data Analysis for AI Applications

Learn to apply clustering techniques and data analysis to understand the valuable work your AI application performs by analyzing conversation histories and creating generative evaluations to benchmark discovered capabilities. This 19-minute conference talk from the AI Engineer World's Fair demonstrates practical approaches to examining AI application data, with insights from Jeff Huber, CEO and cofounder of Chroma (an open-source vector database), and Jason Liu, a machine learning engineer and consultant. Discover methods for extracting meaningful patterns from conversational data, implementing clustering algorithms to identify key functionalities, and developing evaluation frameworks to measure your AI system's newly identified strengths and capabilities.