Databricks unveils adaptive AI retrieval model to cut search costs and latency

Databricks on Wednesday introduced Adaptive Instructed-Retriever, a new retrieval model designed to improve enterprise AI search by taking additional steps for complex queries while stopping early on simpler ones in order to help its customers balance answer quality, latency, and cost. The new model builds on research behind Databricks’ earlier Instructed-Retriever-1 but takes a different approach to handling complex queries. While Instructed-Retriever-1 uses parallel, single-step search and inc