AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Optimizing AI Performance: Cost and Accuracy Trade-offs
This chapter explores the intricate relationship between cost and performance in compound AI systems, highlighting the benefits of smaller models and optimized sampling. It introduces the DSPY framework for balancing accuracy and costs while emphasizing the importance of dynamic cost evaluations in real-world AI deployments. The discussion culminates in a focus on innovative strategies for agent optimization, including the potential for agents to create other agents and the evolving role of database management in this context.