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Building Billion-Scale Vector Search - part one

How fast is fast? Many consider the blink of an eye, around 100-250ms, to be plenty fast.

Pre-trained models on Vespa Cloud

Vespa Cloud now provides pre-trained ML models for your applications

Text embedding made simple

Vespa now lets you create a production quality semantic search application from scratch in minutes

Vespa Newsletter, September 2022

Advances in Vespa features and performance include rank-phase statistics, detailed rank performance analysis, new query- and trace-applications and a new training video!

Will new vector databases dislodge traditional search engines?

Doug Turnbull asks an interesting question on Linkedin; Will new vector databases dislodge traditional search engines?

IR evaluation metrics with uncertainty estimates

Compare different metrics and their uncertainty in the passage ranking dataset.

Summer internship at Vespa

After the summer internship of 2022 the intern has summarized what he has done and his experience at Vespa

Managed Vector Search using Vespa Cloud

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.

Vespa Newsletter, June 2022

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!

Vespa 8 is here

Announcing the release of Vespa 8 - the next major version of vespa.ai

Vespa at Berlin Buzzwords 2022

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.

Billion-scale vector search using hybrid HNSW-IF

This blog post describes HNSW-IF, a cost-efficient solution for high-accuracy vector search over billion scale vector datasets.