Reliable LLM Products Fueled by Feedback - MLOps Podcast #251

Dive into a comprehensive podcast episode exploring the critical aspects of developing reliable LLM products through user feedback. Learn from Chinar Movsisyan, CEO of Feedback Intelligence, as she shares insights on automating evaluation processes, enhancing user experience, and optimizing AI products for real-world deployment. Discover innovative approaches to measuring and improving LLM performance, particularly in highly regulated industries. Explore topics ranging from object detection in drones and street surveillance to challenges in plastic surgery projects and the rising popularity of diffusion models. Gain valuable knowledge on effective data analysis strategies, identifying key metrics, and bridging the gap between subject matter experts and engineers in AI development. Uncover the shifting role of AI metrics and the importance of balancing engineering with evaluation in creating successful LLM-based products.