The April 2020 update includes Top-K hits, smarter data migration and CloudWatch integration. Contributing to Vespa is now easier with the release of a CentOS 7 dev environment.
The Vespa team has been working non-stop to put together the cord19.vespa.ai search app based on the COVID-19 Open Research Dataset (CORD-19) released by the Allen Institute for AI.
Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library
In the November Vespa product update, we mentioned Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance and...
Vespa.ai have just published two tutorials to help people to get started with text search applications by building scalable solutions with Vespa. The tutorials were based on the full document...
Holiday shopping season is upon us and it’s time for a blog post on E-commerce search and recommendation using Vespa.ai. Vespa.ai is used as the search and recommendation backend at...
In the September Vespa product update, we mentioned Tensor Float Support, Reduced Memory Use for Text Attributes, Prometheus Monitoring Support, and Query Dispatch Integrated in Container.
In the August Vespa product update, we mentioned BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export. Largely developed by Yahoo engineers, Vespa is an open source...
In the recent Vespa product update, we mentioned Large Machine Learning Models, Multithreaded Disk Index Fusion, Ideal State Optimizations, and Feeding Improvements. Largely developed by Yahoo engineers, Vespa is an...
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