
Optimizing Retrieval Agents with Shirley Wu - Weaviate Podcast #115!
Weaviate Podcast
Optimizing Retrieval Agents through Prompt Strategies
This chapter examines the intricacies of causal inference in the development of retrieval agents, particularly under the Stark benchmark. The discussion covers the integration of diverse data sources and the concept of contrastive prompt optimization to enhance language models' performance in responding to queries. Additionally, it highlights the evolutionary processes in prompt development, emphasizing the analysis of action sequences and the application of advanced methodologies for improving agent reasoning.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.