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Here’s what’s big in vector search!
November 23, 2022 – This blog post presents Ref2Vec, a new Weaviate module to use Cross-References for Recommendation!
November 15, 2022 – Learn how to quickly and easily back up and restore your Weaviate data with the native backup feature.
November 1, 2022 – Learn, what is new in Weaviate 1.16. New filter operators, distributed backups, centroid module, node status API, Azure-based OIDC, and more frequent stable releases.
October 25, 2022 – The Lock Striping pattern is a great way to solve race conditions - for example, when dealing with concurrent batch imports containing objects with the same UUID - without sacrificing performance.
October 18, 2022 – Learn how to use build an image search application using the Img2vec-neural module in Weaviate
October 11, 2022 – Vector search on disks: How does Vamana compare to HNSW?
October 4, 2022 – Learn about the various Sentence Transformers from Hugging Face!
September 27, 2022 – Running ML Model Inference in production is hard. You can use Weaviate – a vector search engine – with Hugging Face Inference module to delegate the heavy lifting.
September 21, 2022 – Two weeks after the 1.15 release, we have a patch (v1.15.1) release for you, which brings 15 bug fixes and 2 UX improvements.
September 21, 2022 – Learn about why you need distance metrics in vector search and the metrics implemented in Weaviate (Cosine, Dot Product, L2-Squared, Manhattan, and Hamming).
September 13, 2022 – Vector Search engines can run semantic queries on multi-million datasets in milliseconds. How is that possible?
September 7, 2022 – Learn, what is new in Weaviate 1.15. Cloud-native backups, memory optimizations, faster filtered aggregations and ordered imports, new distance metrics and Weaviate modules.
September 1, 2022 – Press Release: Pay-as-you-grow comes to vector search.
August 30, 2022 – A new algorithm presents evidence that Self-Supervised Retrieval can surpass BM25 and Supervised techniques. This technique also pairs very well alongside BM25 in Hybrid Retrieval.
August 15, 2022 – It can be very frustrating when Go applications use less memory than what is available to them, and yet they still manage to run out of memory and crash. Go 1.19 introduced GOMEMLIMIT, which completely changes how you can manage memory limits in Go.
August 9, 2022 – Learn about bi-encoder and cross-encoder machine learning models, and why combining them could improve the vector search experience.
July 6, 2022 – Learn, what is new in Weaviate 1.14, the most reliable and observable Weaviate release yet!
June 23, 2022 – This is the description, it describes what the post is about
November 25, 2021 – Semantic search through the complete Wikipedia with the Weaviate vector search engine
May 19, 2021 – What Weaviate users should know about Docker & Containers
March 30, 2021 – Weaviate v1.2 introduced support for transformers (DistilBERT, BERT, RoBERTa, Sentence-BERT, etc) to vectorize and semantically search through your data
February 15, 2021 – How the vector search engine Weaviate overcomes the limitations of popular Approximate Nearest Neighbor (ANN) libraries.
January 27, 2021 – Any kind of data storage architecture needs an API. You want your users, and their applications, to access and interact with their data. And no matter how complicated the database architecture itself is, you want this interaction to happen as intuitively as possible.
January 20, 2021 – Weaviate is an open-source search engine with a build-in NLP model called the Contextionary. What makes Weaviate unique, is that it stores data in a vector space rather than a traditional row-column or graph structure, allowing you to search through data based on its meaning rather than keywords alone.
January 20, 2021 – Learn how the AI-first search engine Weaviate unlocks the potential of unstructured data and why this is important.