How AI Is Built cover image

#023 The Power of Rerankers in Modern Search

How AI Is Built

00:00

Understanding Re-Rankers in AI Search Systems

This chapter explores the role of re-rankers and cross encoders in AI applications, specifically their function in classifying duplicate documents and optimizing search outputs. It highlights the advantages and limitations of late interaction models, discusses advancements in modern search technologies, and emphasizes the importance of query understanding for effective information retrieval. The chapter also delves into the challenges of aligning training data with user queries, especially in dynamic fields, while advocating for the significance of re-rankers in maintaining search performance.

Transcript
Play full episode

The AI-powered Podcast Player

Save insights by tapping your headphones, chat with episodes, discover the best highlights - and more!
App store bannerPlay store banner
Get the app