Tag vespaengine

Vespa Meetup in Sunnyvale

WHAT: Vespa meetup with various presentations from the Vespa team.

Tag database

Vespa Newsletter, December 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, December 2023

Advances in Vespa features and performance include rank score normalization in the global ranking phase, improved feeding using PyVespa, token authentication, and query match debugging!

Vespa Newsletter, October 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, October 2023

Advances in Vespa features and performance include Vespa Cloud Enclave, Lucene Linguistics integration, much faster fuzzy query term matching, and performance and usability improvements.

Vespa Newsletter, August 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, August 2023

Advances in Vespa features and performance include multilingual models, more control over ANN queries, mapped tensors in queries, and multiple new features in pyvespa and the Vespa CLI.

Vespa Newsletter, July 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, July 2023

Advances in Vespa features and performance include Vector Streaming Search, GPU accelerated embeddings, Huggingface models and a solution to MIPS using a nearest neighbor search.

Vespa Newsletter, May 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, May 2023

Advances in Vespa features and performance include multi-vector HNSW Indexing, global-phase re-ranking, LangChain support, improved bfloat16 throughput, and new document feed/export features in the Vespa CLI.

Vespa Newsletter, March 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, March 2023

Advances in Vespa features and performance include GPU support, advanced BCP autoscaling, GCP Private Service Connect, and a great update to the e-commerce sample app.

Vespa Newsletter, January 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2023

Advances in Vespa features and performance include Better Tensor formats, AWS PrivateLink, Autoscaling, Data Plane Access Control and Container and Content Node Performance.

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.

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.

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!

Vespa Newsletter, June 2022

Photo by Scott Graham on Unsplash

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 Newsletter, April 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, April 2022

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!

Vespa Newsletter, January 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2022

Advances in Vespa features, performance and operability improvements include: Improved synonym support, faster node recovery, re-balancing and re-indexing, WeakAnd query type and new pyvespa features and sample applications.

Vespa Newsletter, December 2021

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, December 2021

Advances in Vespa features and performance include tensor performance improvements, match-features and a Vespa IntelliJ plugin.

Vespa Newsletter, November 2021

Photo by Scott Graham on Unsplash

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa Product Updates, September 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Vespa Product Updates, July 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Vespa Product Updates, May 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, May 2021

Advances in features and performance include new int8 and bfloat16 tensor cell types, compact tensor feed format, Approximate Nearest Neighbor using Hamming distance, hash-based attribute dictionaries and case-sensitive attribute search...

Vespa Product Updates, March 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, March 2021

Advances in Vespa features and performance last month include mass update/delete in /document/v1/, improved memory usage, OR-to-WeakAnd and better full node protection.

Vespa Product Updates, January 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, January 2021

Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.

Vespa Product Updates, December 2020

Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.

Vespa Product Updates, October 2020

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, October 2020

Improvement to Vespa feeding APIs

Vespa Product Updates, September 2020

Introducing ONNX-Runtime, Hamming Distance Metric, Conditional Update Performance Improvements and Compressed Transaction Log with Synced Ack

Vespa Product Updates, August 2020

Introducing NLP with Transformers, Grafana how-to, Improved GEO Search Support, Query Profile Variants Optimizations, & Build on Debian 10

Vespa Product Updates, June 2020

Announcing support for approximate nearest neighbor vector search which can be combined with filters and text search with state-of-the art performance

Vespa Product Updates, May 2020

The May 2020 update includes Improved Slow Node Tolerance, Multi-Threaded Rank Profile Compilation, Reduced Peak Memory at Startup, Feed Performance Improvements, & Increased Tensor Performance.

Vespa Product Updates, April 2020

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.

Vespa Product Updates, February 2020

Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library

Vespa Product Updates, January 2020

The January 2020 update includes information about new tensor functions, updated sizing guides and various performance improvements.

Vespa Product Updates, December 2019: Improved ONNX support, New rank feature attributeMatch().maxWeight, Free lists for attribute multivalue mapping, faster updates for out-of-sync documents, Zookeeper 3.5.6

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 Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

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.

Vespa Product Updates, September 2019: 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...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

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...

Vespa Product Updates, March 2019: Tensor updates, Query tracing and coverage

In last month’s Vespa update, we mentioned Boolean Field Type, Environment Variables, and Advanced Search Core Tuning. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, February 2019: Boolean Field Type, Environment Variables, and Advanced Search Core Tuning

In last month’s Vespa update, we mentioned Parent/Child, Large File Config Download, and a Simplified Feeding Interface. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, January 2019: Parent/Child, Large File Config Download, and a Simplified Feeding Interface

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...

Efficient personal search at large scale

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...

Migrating to the Vespa Search Engine

In this post, I will detail the journey at Stanby of how we have addressed the challenges faced by our existing search system through migrating to Vespa.

When you're using vectors you're doing search

Photo by NEOM on Unsplash

When you're using vectors you're doing search

Combining scale and quality takes more than vector similarity search

Vespa Newsletter, December 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, December 2023

Advances in Vespa features and performance include rank score normalization in the global ranking phase, improved feeding using PyVespa, token authentication, and query match debugging!

Vespa Newsletter, October 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, October 2023

Advances in Vespa features and performance include Vespa Cloud Enclave, Lucene Linguistics integration, much faster fuzzy query term matching, and performance and usability improvements.

Vespa Newsletter, August 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, August 2023

Advances in Vespa features and performance include multilingual models, more control over ANN queries, mapped tensors in queries, and multiple new features in pyvespa and the Vespa CLI.

Vespa Newsletter, July 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, July 2023

Advances in Vespa features and performance include Vector Streaming Search, GPU accelerated embeddings, Huggingface models and a solution to MIPS using a nearest neighbor search.

Vespa Newsletter, May 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, May 2023

Advances in Vespa features and performance include multi-vector HNSW Indexing, global-phase re-ranking, LangChain support, improved bfloat16 throughput, and new document feed/export features in the Vespa CLI.

Vespa Newsletter, March 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, March 2023

Advances in Vespa features and performance include GPU support, advanced BCP autoscaling, GCP Private Service Connect, and a great update to the e-commerce sample app.

Vespa Newsletter, January 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2023

Advances in Vespa features and performance include Better Tensor formats, AWS PrivateLink, Autoscaling, Data Plane Access Control and Container and Content Node Performance.

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.

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.

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!

Vespa Newsletter, June 2022

Photo by Scott Graham on Unsplash

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 Newsletter, April 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, April 2022

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!

Vespa Newsletter, January 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2022

Advances in Vespa features, performance and operability improvements include: Improved synonym support, faster node recovery, re-balancing and re-indexing, WeakAnd query type and new pyvespa features and sample applications.

Vespa Newsletter, December 2021

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, December 2021

Advances in Vespa features and performance include tensor performance improvements, match-features and a Vespa IntelliJ plugin.

Vespa Newsletter, November 2021

Photo by Scott Graham on Unsplash

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa Product Updates, September 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Vespa Product Updates, July 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Vespa Product Updates, May 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, May 2021

Advances in features and performance include new int8 and bfloat16 tensor cell types, compact tensor feed format, Approximate Nearest Neighbor using Hamming distance, hash-based attribute dictionaries and case-sensitive attribute search...

Vespa Product Updates, March 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, March 2021

Advances in Vespa features and performance last month include mass update/delete in /document/v1/, improved memory usage, OR-to-WeakAnd and better full node protection.

Vespa Product Updates, January 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, January 2021

Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.

Vespa Product Updates, December 2020

Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.

Vespa Product Updates, October 2020

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, October 2020

Improvement to Vespa feeding APIs

Vespa Product Updates, September 2020

Introducing ONNX-Runtime, Hamming Distance Metric, Conditional Update Performance Improvements and Compressed Transaction Log with Synced Ack

Vespa Product Updates, August 2020

Introducing NLP with Transformers, Grafana how-to, Improved GEO Search Support, Query Profile Variants Optimizations, & Build on Debian 10

Vespa Product Updates, June 2020

Announcing support for approximate nearest neighbor vector search which can be combined with filters and text search with state-of-the art performance

Vespa Product Updates, May 2020

The May 2020 update includes Improved Slow Node Tolerance, Multi-Threaded Rank Profile Compilation, Reduced Peak Memory at Startup, Feed Performance Improvements, & Increased Tensor Performance.

Vespa Product Updates, April 2020

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.

Vespa Product Updates, February 2020

Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library

Vespa Product Updates, January 2020

The January 2020 update includes information about new tensor functions, updated sizing guides and various performance improvements.

Vespa Product Updates, December 2019: Improved ONNX support, New rank feature attributeMatch().maxWeight, Free lists for attribute multivalue mapping, faster updates for out-of-sync documents, Zookeeper 3.5.6

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...

Learning to Rank with Vespa – Getting started with Text Search

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...

E-commerce search and recommendation with Vespa.ai

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...

Vespa Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

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.

Vespa Product Updates, September 2019: 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...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

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...

Vespa Product Updates, March 2019: Tensor updates, Query tracing and coverage

In last month’s Vespa update, we mentioned Boolean Field Type, Environment Variables, and Advanced Search Core Tuning. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, February 2019: Boolean Field Type, Environment Variables, and Advanced Search Core Tuning

In last month’s Vespa update, we mentioned Parent/Child, Large File Config Download, and a Simplified Feeding Interface. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, January 2019: Parent/Child, Large File Config Download, and a Simplified Feeding Interface

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...

Efficient personal search at large scale

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...

Tag big data

Vespa Newsletter, December 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, December 2023

Advances in Vespa features and performance include rank score normalization in the global ranking phase, improved feeding using PyVespa, token authentication, and query match debugging!

Vespa Newsletter, October 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, October 2023

Advances in Vespa features and performance include Vespa Cloud Enclave, Lucene Linguistics integration, much faster fuzzy query term matching, and performance and usability improvements.

Vespa Newsletter, August 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, August 2023

Advances in Vespa features and performance include multilingual models, more control over ANN queries, mapped tensors in queries, and multiple new features in pyvespa and the Vespa CLI.

Vespa Newsletter, July 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, July 2023

Advances in Vespa features and performance include Vector Streaming Search, GPU accelerated embeddings, Huggingface models and a solution to MIPS using a nearest neighbor search.

Vespa Newsletter, May 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, May 2023

Advances in Vespa features and performance include multi-vector HNSW Indexing, global-phase re-ranking, LangChain support, improved bfloat16 throughput, and new document feed/export features in the Vespa CLI.

Vespa Newsletter, March 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, March 2023

Advances in Vespa features and performance include GPU support, advanced BCP autoscaling, GCP Private Service Connect, and a great update to the e-commerce sample app.

Vespa Newsletter, January 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2023

Advances in Vespa features and performance include Better Tensor formats, AWS PrivateLink, Autoscaling, Data Plane Access Control and Container and Content Node Performance.

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.

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.

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!

Vespa Newsletter, June 2022

Photo by Scott Graham on Unsplash

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 Newsletter, April 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, April 2022

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!

Vespa Newsletter, January 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2022

Advances in Vespa features, performance and operability improvements include: Improved synonym support, faster node recovery, re-balancing and re-indexing, WeakAnd query type and new pyvespa features and sample applications.

Vespa Newsletter, December 2021

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, December 2021

Advances in Vespa features and performance include tensor performance improvements, match-features and a Vespa IntelliJ plugin.

Vespa Newsletter, November 2021

Photo by Scott Graham on Unsplash

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa Product Updates, September 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Vespa Product Updates, July 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Vespa Product Updates, May 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, May 2021

Advances in features and performance include new int8 and bfloat16 tensor cell types, compact tensor feed format, Approximate Nearest Neighbor using Hamming distance, hash-based attribute dictionaries and case-sensitive attribute search...

Vespa Product Updates, March 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, March 2021

Advances in Vespa features and performance last month include mass update/delete in /document/v1/, improved memory usage, OR-to-WeakAnd and better full node protection.

Vespa Product Updates, January 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, January 2021

Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.

Vespa Product Updates, December 2020

Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.

Vespa Product Updates, October 2020

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, October 2020

Improvement to Vespa feeding APIs

Vespa Product Updates, September 2020

Introducing ONNX-Runtime, Hamming Distance Metric, Conditional Update Performance Improvements and Compressed Transaction Log with Synced Ack

Vespa Product Updates, August 2020

Introducing NLP with Transformers, Grafana how-to, Improved GEO Search Support, Query Profile Variants Optimizations, & Build on Debian 10

Vespa Product Updates, June 2020

Announcing support for approximate nearest neighbor vector search which can be combined with filters and text search with state-of-the art performance

Vespa Product Updates, May 2020

The May 2020 update includes Improved Slow Node Tolerance, Multi-Threaded Rank Profile Compilation, Reduced Peak Memory at Startup, Feed Performance Improvements, & Increased Tensor Performance.

Vespa Product Updates, April 2020

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.

Vespa Product Updates, February 2020

Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library

Vespa Product Updates, January 2020

The January 2020 update includes information about new tensor functions, updated sizing guides and various performance improvements.

Vespa Product Updates, December 2019: Improved ONNX support, New rank feature attributeMatch().maxWeight, Free lists for attribute multivalue mapping, faster updates for out-of-sync documents, Zookeeper 3.5.6

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 Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

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.

Vespa Product Updates, September 2019: 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...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

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...

Vespa Product Updates, March 2019: Tensor updates, Query tracing and coverage

In last month’s Vespa update, we mentioned Boolean Field Type, Environment Variables, and Advanced Search Core Tuning. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, February 2019: Boolean Field Type, Environment Variables, and Advanced Search Core Tuning

In last month’s Vespa update, we mentioned Parent/Child, Large File Config Download, and a Simplified Feeding Interface. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Serving article comments using reinforcement learning of a neural net

Don’t look at the comments. When you allow users to make comments on your content pages you face the problem that not all of them are worth showing — a difficult problem...

Vespa Product Updates, January 2019: Parent/Child, Large File Config Download, and a Simplified Feeding Interface

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...

Efficient personal search at large scale

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...

Tag search engines

Vespa Newsletter, December 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, December 2023

Advances in Vespa features and performance include rank score normalization in the global ranking phase, improved feeding using PyVespa, token authentication, and query match debugging!

Vespa Newsletter, October 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, October 2023

Advances in Vespa features and performance include Vespa Cloud Enclave, Lucene Linguistics integration, much faster fuzzy query term matching, and performance and usability improvements.

Vespa Newsletter, August 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, August 2023

Advances in Vespa features and performance include multilingual models, more control over ANN queries, mapped tensors in queries, and multiple new features in pyvespa and the Vespa CLI.

Vespa Newsletter, July 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, July 2023

Advances in Vespa features and performance include Vector Streaming Search, GPU accelerated embeddings, Huggingface models and a solution to MIPS using a nearest neighbor search.

Vespa Newsletter, May 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, May 2023

Advances in Vespa features and performance include multi-vector HNSW Indexing, global-phase re-ranking, LangChain support, improved bfloat16 throughput, and new document feed/export features in the Vespa CLI.

Vespa Newsletter, March 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, March 2023

Advances in Vespa features and performance include GPU support, advanced BCP autoscaling, GCP Private Service Connect, and a great update to the e-commerce sample app.

Vespa Newsletter, January 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2023

Advances in Vespa features and performance include Better Tensor formats, AWS PrivateLink, Autoscaling, Data Plane Access Control and Container and Content Node Performance.

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.

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.

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!

Vespa Newsletter, June 2022

Photo by Scott Graham on Unsplash

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 Newsletter, April 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, April 2022

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!

Vespa Newsletter, January 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2022

Advances in Vespa features, performance and operability improvements include: Improved synonym support, faster node recovery, re-balancing and re-indexing, WeakAnd query type and new pyvespa features and sample applications.

Vespa Newsletter, December 2021

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, December 2021

Advances in Vespa features and performance include tensor performance improvements, match-features and a Vespa IntelliJ plugin.

Vespa Newsletter, November 2021

Photo by Scott Graham on Unsplash

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa Product Updates, September 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Vespa Product Updates, July 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Vespa Product Updates, May 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, May 2021

Advances in features and performance include new int8 and bfloat16 tensor cell types, compact tensor feed format, Approximate Nearest Neighbor using Hamming distance, hash-based attribute dictionaries and case-sensitive attribute search...

Vespa Product Updates, March 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, March 2021

Advances in Vespa features and performance last month include mass update/delete in /document/v1/, improved memory usage, OR-to-WeakAnd and better full node protection.

Vespa Product Updates, January 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, January 2021

Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.

Vespa Product Updates, December 2020

Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.

Vespa Product Updates, October 2020

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, October 2020

Improvement to Vespa feeding APIs

Vespa Product Updates, September 2020

Introducing ONNX-Runtime, Hamming Distance Metric, Conditional Update Performance Improvements and Compressed Transaction Log with Synced Ack

Vespa Product Updates, August 2020

Introducing NLP with Transformers, Grafana how-to, Improved GEO Search Support, Query Profile Variants Optimizations, & Build on Debian 10

Vespa Product Updates, June 2020

Announcing support for approximate nearest neighbor vector search which can be combined with filters and text search with state-of-the art performance

Vespa Product Updates, May 2020

The May 2020 update includes Improved Slow Node Tolerance, Multi-Threaded Rank Profile Compilation, Reduced Peak Memory at Startup, Feed Performance Improvements, & Increased Tensor Performance.

Vespa Product Updates, April 2020

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.

Vespa Product Updates, February 2020

Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library

Vespa Product Updates, January 2020

The January 2020 update includes information about new tensor functions, updated sizing guides and various performance improvements.

Vespa Product Updates, December 2019: Improved ONNX support, New rank feature attributeMatch().maxWeight, Free lists for attribute multivalue mapping, faster updates for out-of-sync documents, Zookeeper 3.5.6

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 Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

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.

Vespa Product Updates, September 2019: 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...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

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...

Vespa Product Updates, March 2019: Tensor updates, Query tracing and coverage

In last month’s Vespa update, we mentioned Boolean Field Type, Environment Variables, and Advanced Search Core Tuning. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, February 2019: Boolean Field Type, Environment Variables, and Advanced Search Core Tuning

In last month’s Vespa update, we mentioned Parent/Child, Large File Config Download, and a Simplified Feeding Interface. Largely developed by Yahoo engineers, Vespa is an open source big data processing...

Vespa Product Updates, January 2019: Parent/Child, Large File Config Download, and a Simplified Feeding Interface

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...

Efficient personal search at large scale

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...

Tag vespa vespa7

Vespa 7 is released!

This week we rolled the major version of Vespa over from 6 to 7.

Tag machine learning

Learning to Rank with Vespa – Getting started with Text Search

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...

Serving article comments using reinforcement learning of a neural net

Don’t look at the comments. When you allow users to make comments on your content pages you face the problem that not all of them are worth showing — a difficult problem...

Tag recommendation systems

Serving article comments using reinforcement learning of a neural net

Don’t look at the comments. When you allow users to make comments on your content pages you face the problem that not all of them are worth showing — a difficult problem...

Tag reinforcement learning

Serving article comments using reinforcement learning of a neural net

Don’t look at the comments. When you allow users to make comments on your content pages you face the problem that not all of them are worth showing — a difficult problem...

Tag neural networks

Serving article comments using reinforcement learning of a neural net

Don’t look at the comments. When you allow users to make comments on your content pages you face the problem that not all of them are worth showing — a difficult problem...

Tag big data serving

Vespa Newsletter, December 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, December 2023

Advances in Vespa features and performance include rank score normalization in the global ranking phase, improved feeding using PyVespa, token authentication, and query match debugging!

Vespa Newsletter, October 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, October 2023

Advances in Vespa features and performance include Vespa Cloud Enclave, Lucene Linguistics integration, much faster fuzzy query term matching, and performance and usability improvements.

Vespa Newsletter, August 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, August 2023

Advances in Vespa features and performance include multilingual models, more control over ANN queries, mapped tensors in queries, and multiple new features in pyvespa and the Vespa CLI.

Vespa Newsletter, July 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, July 2023

Advances in Vespa features and performance include Vector Streaming Search, GPU accelerated embeddings, Huggingface models and a solution to MIPS using a nearest neighbor search.

Vespa Newsletter, May 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, May 2023

Advances in Vespa features and performance include multi-vector HNSW Indexing, global-phase re-ranking, LangChain support, improved bfloat16 throughput, and new document feed/export features in the Vespa CLI.

Vespa Newsletter, March 2023

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, March 2023

Advances in Vespa features and performance include GPU support, advanced BCP autoscaling, GCP Private Service Connect, and a great update to the e-commerce sample app.

Vespa Newsletter, January 2023

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2023

Advances in Vespa features and performance include Better Tensor formats, AWS PrivateLink, Autoscaling, Data Plane Access Control and Container and Content Node Performance.

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.

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.

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!

Vespa Newsletter, June 2022

Photo by Scott Graham on Unsplash

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 Newsletter, April 2022

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, April 2022

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!

Vespa Newsletter, January 2022

Photo by Scott Graham on Unsplash

Vespa Newsletter, January 2022

Advances in Vespa features, performance and operability improvements include: Improved synonym support, faster node recovery, re-balancing and re-indexing, WeakAnd query type and new pyvespa features and sample applications.

Vespa Newsletter, December 2021

Photo by Ilya Pavlov on Unsplash

Vespa Newsletter, December 2021

Advances in Vespa features and performance include tensor performance improvements, match-features and a Vespa IntelliJ plugin.

Vespa Newsletter, November 2021

Photo by Scott Graham on Unsplash

Vespa Newsletter, November 2021

Advances in Vespa features and performance include improved schema inheritance, Intellij plugin for schemas, Hamming distance in ranking, and performance gains in data dump and application deployment.

Vespa Product Updates, September 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, September 2021

Advances in Vespa features and performance include Vespa CLI, nearest neighbor performance improvements, mTLS security, improved write throughput and Sentencepiece Encoder.

Vespa Product Updates, July 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, July 2021

Advances in Vespa features and performance include HTTP/2 feed and query endpoints, ONNX Runtime integration for stateless model inference, and the new open Vespa Factory build and test system.

Vespa Product Updates, May 2021

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, May 2021

Advances in features and performance include new int8 and bfloat16 tensor cell types, compact tensor feed format, Approximate Nearest Neighbor using Hamming distance, hash-based attribute dictionaries and case-sensitive attribute search...

Vespa Product Updates, March 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, March 2021

Advances in Vespa features and performance last month include mass update/delete in /document/v1/, improved memory usage, OR-to-WeakAnd and better full node protection.

Vespa Product Updates, January 2021

Photo by Scott Graham on Unsplash

Vespa Product Updates, January 2021

Advances in Vespa features and performance last month include Automatic Reindexing, Tensor Optimizations and Explainlevel Query Parameter for easier query blueprint tracing.

Vespa Product Updates, December 2020

Advances in Vespa features and performance include improved tensor ranking performance, Apache ZooKeeper integration, Vespa Python API for researchers and ONNX integration.

Vespa Product Updates, October 2020

Photo by Ilya Pavlov on Unsplash

Vespa Product Updates, October 2020

Improvement to Vespa feeding APIs

Vespa Product Updates, September 2020

Introducing ONNX-Runtime, Hamming Distance Metric, Conditional Update Performance Improvements and Compressed Transaction Log with Synced Ack

Vespa Product Updates, August 2020

Introducing NLP with Transformers, Grafana how-to, Improved GEO Search Support, Query Profile Variants Optimizations, & Build on Debian 10

Vespa Product Updates, June 2020

Announcing support for approximate nearest neighbor vector search which can be combined with filters and text search with state-of-the art performance

Vespa Product Updates, May 2020

The May 2020 update includes Improved Slow Node Tolerance, Multi-Threaded Rank Profile Compilation, Reduced Peak Memory at Startup, Feed Performance Improvements, & Increased Tensor Performance.

Vespa Product Updates, April 2020

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.

Vespa Product Updates, February 2020

Advances in Vespa features and performance in February include LightGBM support, improved tensor performance, benchmarking guide and query builder library

Vespa Product Updates, January 2020

The January 2020 update includes information about new tensor functions, updated sizing guides and various performance improvements.

Vespa Product Updates, December 2019: Improved ONNX support, New rank feature attributeMatch().maxWeight, Free lists for attribute multivalue mapping, faster updates for out-of-sync documents, Zookeeper 3.5.6

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 Product Updates, October/November 2019: Nearest Neighbor and Tensor Ranking, Optimized JSON Tensor Feed Format, Matched Elements in Complex Multi-value Fields, Large Weighted Set Update Performance, and Datadog Monitoring Support

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.

Vespa Product Updates, September 2019: 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...

Vespa Product Updates, August 2019: BM25 Rank Feature, Searchable Parent References, Tensor Summary Features, and Metrics Export

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...

Tag vespa

Learning to Rank with Vespa – Getting started with Text Search

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...

E-commerce search and recommendation with Vespa.ai

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...

Tag information retrieval

E-commerce search and recommendation with Vespa.ai

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...

Tag e commerce business

E-commerce search and recommendation with Vespa.ai

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...

Tag holiday shopping online

E-commerce search and recommendation with Vespa.ai

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...

Tag tensorflow

Learning to Rank with Vespa – Getting started with Text Search

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...

Tag learning to rank

Learning to Rank with Vespa – Getting started with Text Search

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...

Tag Search Engines

Vespa.ai and the CORD-19 public API

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.

Tag Covid 19

Vespa.ai and the CORD-19 public API

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.

Tag Artificial Intelligence

Vespa.ai and the CORD-19 public API

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.

Tag Machine Learning

Vespa.ai and the CORD-19 public API

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.

Tag NLP

Vespa.ai and the CORD-19 public API

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.

Tag parent child

Parent-child joins and tensors for content recommendation

A real-world application of parent-child joins and tensor functions to model topic popularity for content recommendation.

Tag tensor

Parent-child joins and tensors for content recommendation

A real-world application of parent-child joins and tensor functions to model topic popularity for content recommendation.

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

The Singaporean government deploys state of the art semantic search

The Singapore Government Pair Search

The Singaporean government deploys state of the art semantic search

The Singaporean government leverages Vespa to do semantic search in every word ever said in Parliament

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

Tag embeddings

Matryoshka 🤝 Binary vectors: Slash vector search costs with Vespa

Announcing Matryoshka (dimension flexibility) and binary quantization in Vespa and how these features slashes costs.

Scaling vector search using Cohere binary embeddings and Vespa

Photo by Phil Botha on Unsplash

Scaling vector search using Cohere binary embeddings and Vespa

Three comprehensive guides to using the Cohere Embed v3 binary embeddings with Vespa.

Announcing Vespa Long-Context ColBERT

Announcing long-context ColBERT, giving it larger context for scoring and simplifying long-document RAG applications.

Embedding flexibility in Vespa

Why did Vespa score "Exceptional" on Embedding Flexibility in GigaOm's report on Vector Databases?

Announcing the Vespa ColBERT embedder

Announcing the native Vespa ColBERT embedder in Vespa, enabling explainable semantic search using token-level vector representations

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Photo by Simon Hurry on Unsplash

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Using the "shortening" properties of OpenAI v3 embedding models to greatly reduce latency/cost while retaining near-exact quality

Representing BGE embedding models in Vespa using bfloat16

This post demonstrates how to use recently announced BGE embedding models in Vespa. We evaluate the effectiveness of two BGE variants on the BEIR trec-covid dataset. Finally, we demonstrate how...

Accelerating Transformer-based Embedding Retrieval with Vespa

Photo by Appic on Unsplash

Accelerating Transformer-based Embedding Retrieval with Vespa

In this post, we’ll see how to accelerate embedding inference and retrieval with little impact on quality. We’ll take a holistic approach and deep-dive into both aspects of an embedding...

Simplify Search with Multilingual Embedding Models

This blog post presents and shows how to represent a robust multilingual embedding model of the E5 family in Vespa.

Leveraging frozen embeddings in Vespa with SentenceTransformers

How to implement frozen embeddings approach in Vespa using SentenceTransformers library and optimize your search application at the same time.

Customizing Reusable Frozen ML-Embeddings with Vespa

Photo by fabio on Unsplash

Customizing Reusable Frozen ML-Embeddings with Vespa

Deep-learned embeddings are popular for search and recommendation use cases. This post introduces the concept of using reusable frozen embeddings and tailoring them with Vespa.

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

Tag ANN

Text embedding made simple

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

Tag HNSW

Text embedding made simple

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

Tag ML

Pre-trained models on Vespa Cloud

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

Tag models

Pre-trained models on Vespa Cloud

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

Tag vespa cloud

Pre-trained models on Vespa Cloud

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

Tag ARM64

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.

Tag container image

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.

Tag GCP

Vespa Cloud on Google Cloud Platform

Photo by NASA on Unsplash

Vespa Cloud on Google Cloud Platform

Vespa Cloud is now available on Google Cloud Platform

Tag Google Cloud Platform

Vespa Cloud on Google Cloud Platform

Photo by NASA on Unsplash

Vespa Cloud on Google Cloud Platform

Vespa Cloud is now available on Google Cloud Platform

Tag rag

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Photo by Simon Hurry on Unsplash

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Using the "shortening" properties of OpenAI v3 embedding models to greatly reduce latency/cost while retaining near-exact quality

Turbocharge RAG with LangChain and Vespa Streaming Mode for Sharded Data

A hands-on guide to connect LangChain with Vespa streaming mode to build cost-efficient RAG applications over naturally sharded data.

Hands-On RAG guide for personal data with Vespa and LLamaIndex

Photo by Avi Richards on Unsplash

Hands-On RAG guide for personal data with Vespa and LLamaIndex

A hands-on guide to using Vespa streaming mode with PyVespa and LLamaIndex.

Yahoo Mail turns to Vespa to do RAG at scale

Vector search in trillions of personal documents can be done cost-effectively with vector streaming search.

Announcing vector streaming search: AI assistants at scale without breaking the bank

With personal data, you need complete results at low cost, something vector databases cannot provide. Vespa's new vector streaming search delivers complete results at a fraction of the cost.

Tag vectors

Farfetch: Scaling recommendations with Vespa

E-commerce platform Farfetch explains how they use Vespa to scale their online recommendation system

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Photo by Simon Hurry on Unsplash

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Using the "shortening" properties of OpenAI v3 embedding models to greatly reduce latency/cost while retaining near-exact quality

Turbocharge RAG with LangChain and Vespa Streaming Mode for Sharded Data

A hands-on guide to connect LangChain with Vespa streaming mode to build cost-efficient RAG applications over naturally sharded data.

Hands-On RAG guide for personal data with Vespa and LLamaIndex

Photo by Avi Richards on Unsplash

Hands-On RAG guide for personal data with Vespa and LLamaIndex

A hands-on guide to using Vespa streaming mode with PyVespa and LLamaIndex.

Yahoo Mail turns to Vespa to do RAG at scale

Vector search in trillions of personal documents can be done cost-effectively with vector streaming search.

Announcing vector streaming search: AI assistants at scale without breaking the bank

With personal data, you need complete results at low cost, something vector databases cannot provide. Vespa's new vector streaming search delivers complete results at a fraction of the cost.

Tag streaming

Turbocharge RAG with LangChain and Vespa Streaming Mode for Sharded Data

A hands-on guide to connect LangChain with Vespa streaming mode to build cost-efficient RAG applications over naturally sharded data.

Hands-On RAG guide for personal data with Vespa and LLamaIndex

Photo by Avi Richards on Unsplash

Hands-On RAG guide for personal data with Vespa and LLamaIndex

A hands-on guide to using Vespa streaming mode with PyVespa and LLamaIndex.

Yahoo Mail turns to Vespa to do RAG at scale

Vector search in trillions of personal documents can be done cost-effectively with vector streaming search.

Announcing vector streaming search: AI assistants at scale without breaking the bank

With personal data, you need complete results at low cost, something vector databases cannot provide. Vespa's new vector streaming search delivers complete results at a fraction of the cost.

Tag company

Announcing our series A funding

Adressa.no

Announcing our series A funding

Announcing a $31 million investment from Blossom Capital

Vespa is becoming a company

Vespa is becoming its own company!

Tag linguistics

Introducing Lucene Linguistics

This post is about an idea that was born at the Berlin Buzzwords 2023 conference and its journey towards the production-ready implementation of the new Apache Lucene-based Vespa Linguistics component....

Tag bm25

Introducing Lucene Linguistics

This post is about an idea that was born at the Berlin Buzzwords 2023 conference and its journey towards the production-ready implementation of the new Apache Lucene-based Vespa Linguistics component....

Tag stemming

Introducing Lucene Linguistics

This post is about an idea that was born at the Berlin Buzzwords 2023 conference and its journey towards the production-ready implementation of the new Apache Lucene-based Vespa Linguistics component....

Redefining Hybrid Search Possibilities with Vespa - part one

Photo by Trent Erwin on Unsplash

Redefining Hybrid Search Possibilities with Vespa - part one

This is the first blog post in a series on hybrid search. This first post focuses on efficient hybrid retrieval and representational approaches in IR

Tag mrl

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Photo by Simon Hurry on Unsplash

Exploring the potential of OpenAI Matryoshka 🪆 embeddings with Vespa

Using the "shortening" properties of OpenAI v3 embedding models to greatly reduce latency/cost while retaining near-exact quality

Tag vector

When you're using vectors you're doing search

Photo by NEOM on Unsplash

When you're using vectors you're doing search

Combining scale and quality takes more than vector similarity search

Tag RAG

The Singaporean government deploys state of the art semantic search

The Singapore Government Pair Search

The Singaporean government deploys state of the art semantic search

The Singaporean government leverages Vespa to do semantic search in every word ever said in Parliament

Tag solr

Migrating to the Vespa Search Engine

In this post, I will detail the journey at Stanby of how we have addressed the challenges faced by our existing search system through migrating to Vespa.

Tag elastic

Migrating to the Vespa Search Engine

In this post, I will detail the journey at Stanby of how we have addressed the challenges faced by our existing search system through migrating to Vespa.

Tag elasticsearch

Vinted moves from Elasticsearch to Vespa

With Vespa, Vinted managed to halve the number of servers, slash query latency by 2.5x, indexing latency by 3x, and increase ranking depth by more than 3x.

Migrating to the Vespa Search Engine

In this post, I will detail the journey at Stanby of how we have addressed the challenges faced by our existing search system through migrating to Vespa.

Tag milvus

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Tag opensearch

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Tag weaviate

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Tag redis

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Tag qdrant

Marqo chooses Vespa

Vector search experts Marqo choose Vespa as their vector database after benchmarking against Milvus, OpenSearch, Weaviate, Redis, and Qdrant.

Tag tensors

Farfetch: Scaling recommendations with Vespa

E-commerce platform Farfetch explains how they use Vespa to scale their online recommendation system

Tag recommendation

Farfetch: Scaling recommendations with Vespa

E-commerce platform Farfetch explains how they use Vespa to scale their online recommendation system

Tag e-commerce

Farfetch: Scaling recommendations with Vespa

E-commerce platform Farfetch explains how they use Vespa to scale their online recommendation system