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Vespa Newsletter, November 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, November 2022

Vespa features and performance advances include ANN Pre-Filter Performance, Parent Field Hit-Estimates, Model Training Notebooks, and GCP Support.

Improving Product Search with Learning to Rank - part two

This is the second blog post on applying learning to rank to enhance E-commerce search.

Vespa Cloud on Google Cloud Platform

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Vespa Cloud on Google Cloud Platform

Vespa Cloud is now available on Google Cloud Platform

Improving Product Search with Learning to Rank - part one

This is the first blog post on applying learning to rank to enhance E-commerce search.

Vespa Newsletter, October 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, October 2022

Advances in Vespa features and performance include a BertBase Embedder / model hub, improved query performance, paged attributes, ARM64 support and term bolding in string arrays.

Building Billion-Scale Vector Search - part two

Searching billion-scale datasets without breaking the bank.

Vespa on ARM64

Foto de Niek Doup en Unsplash

Vespa on ARM64

Vespa is now released as a multiplatform container image, supporting both x86_64 and ARM64.

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

Photo by Ilya Pavlov on Unsplash

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?