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Archive of posts with
category 'newsletter'
Vespa Newsletter, December 2025
Advances in Vespa features and performance include automated ANN tuning, accelerated vector distance calculations with Google Highway, precise chunk-level matching with enhanced sameElement, and expressive proximity queries with nested NEAR...
Vespa Newsletter, September 2025
Advances in Vespa features and performance include new ANN tuning parameters, improvements to Geo filtering, filtering in grouping, and relevance score carry-over to global ranking.
Vespa Newsletter, June 2025
Advances in Vespa features and performance include layered ranking for RAG applications, chunking, and facet filtering.
Vespa Newsletter, April 2025
Advances in Vespa features and performance include Lexical Search Query Performance, Pyvespa Relevance Evaluator, Global-phase rank-score-drop-limit, and Compact tensor representation.
Vespa Newsletter, January 2025
Advances in Vespa features and performance include Pyvespa Querybuilder, Vespa input/output plugins for Logstash, ModernBERT models, and Vespa CLI multi-get.
Vespa Newsletter, December 2024
Advances in Vespa features and performance include Elasticsearch vs Vespa Performance Comparison, Vision RAG and Binarizing Vectors
Vespa Newsletter, October 2024
Advances in Vespa features and performance include Global significance models and Nearest Neighbor Search with multiple sparse tensor dimensions.
Vespa Newsletter, September 2024
Advances in Vespa features and performance include Optimized MaxSim with Hamming distance, IDE Support, Pyvespa features, and new notebooks with ColPali examples.
Vespa Newsletter, August 2024
Advances in Vespa features and performance include new pyvespa and Vespa CLI features for queries, feeding, and deployment, shared match-phase heap, Chinese tokenization with Jieba, and new ranking framework features....
Vespa Newsletter, May 2024
Advances in Vespa features and performance include improved vector search performance, fuzzy search with prefix match, RAG, and new Pyvespa and embedding features.
Photo by
Scott Graham
on
Unsplash
Vespa Newsletter, April 2024
Advances in Vespa features and performance include a new SPLADE embedder, float16 support for ONNX models, new Cohere guides, and support for using ColBERT with long texts.
Photo by
Ilya Pavlov
on
Unsplash
Vespa Newsletter, February 2024
Advances in Vespa features and performance include the YQL IN operator, new streaming search features, and embed using parameter substitution.
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!
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.
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.
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.
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.
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.
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.
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.
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.
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!
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Scott Graham
on
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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!
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!
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.
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.
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.
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