Data Engine Insights

Kate discusses the parallels between data engines for NLP and vision, emphasizing the importance of user feedback in identifying failure modes. By comparing systems like Tesla's autopilot and chat models, she highlights the need for consistent performance and automated curation methods to enhance model reliability. Variability in responses can signal weaknesses, guiding further improvements.