Advances in Vespa features and performance include rank-phase statistics, detailed rank performance analysis, new query- and trace-applications and a new training video!
This blog post describes how your organization can unlock the full potential of multimodal AI-powered vector representations using Vespa -- the industry-leading open-source big data serving engine.
Advances in Vespa features and performance include ANN with configurable filtering, fuzzy matching, and native embedding support. Also see pyvespa’s new experimental ranking module!
Find videos and links from four Vespa-related talks at Berlin Buzzwords 2022, Germany’s most exciting conference on storing, processing, streaming and searching large amounts of digital data.
This blog post describes Vespa's industry leading support for combining approximate nearest neighbor search, or vector search, with query constraints to solve real-world search and recommendation problems at scale.
Advances in Vespa features and performance include tensor and ranking configuration improvements, pyvespa usability features and grouping configuration. Also find new guides for performance and ANN. And a podcast!