In last month’s Vespa update, we mentioned ONNX integration, precise transaction log pruning, grouping on maps, and improvements to streaming search performance. Largely developed by Yahoo engineers, Vespa is an...
Vespa includes a relatively unknown mode which provides personal search at massive scale for a fraction of the cost of alternatives: streaming search. In this article we explain streaming search...
This blog post describes Zedge’s use of Vespa for search and recommender systems to support content discovery for personalization of mobile phones (Android, iOS and Web). Zedge is now using...
We recently introduced a new addition to the Search API - JSON queries. The search request can now be executed with a POST request, which includes the query-parameters within its...
ONNX (Open Neural Network eXchange) is an open format for the sharing of neural network and other machine learned models between various machine learning and deep learning frameworks. As the...
Parent-child relationships let you model hierarchical relations in your data. This blog post talks about why and how we added this feature to Vespa, and how you can use it...
In this blog post we’ll explain how to use Vespa to evaluate TensorFlow models over arbitrarily many data points while keeping total latency constant. We provide benchmark data from our...
In previous blog posts we have talked about Vespa’s tensor API which enables some advanced ranking capabilities. The primary use case is for machine learned ranking, where you train your...
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