In general, a K-nearest neighbor (KNN) algorithm is likely to give good answers to vector search problems. The major issue with KNN is that it’s computationally expensive, both in processor and ...

Google’s June 2025 Core Update just finished. What’s notable is that while some say it was a big update, it didn’t feel disruptive, indicating that the changes may have been more subtle than game ...

MongoDB Atlas then indexes the embeddings using the Hierarchical Navigable Small World, or HNSW, algorithm to provide an ANN vector search. With the introduction of Atlas Search Nodes, ...

Microsoft has made its Space Partition Tree And Graph (SPTAG) algorithm, used in its own Bing search engine, available to all as an open-source GitHub project. The algorithm uses vector search and ...

Vector database offers on-prem, cloud-native, or SaaS deployment, leading performance, a rich set of integrations and language drivers, and a dizzying array of optimization options.

Vector database provider Qdrant presents new algorithm for hybrid searches Qdrant introduces BM42, a new search algorithm tailored to Retrieval Augmented Generation that takes advantage of ...

Bing announced they have made their Space Partition Tree And Graph (SPTAG) vector search algorithm open source to help others who want to make it possible to search through billions of pieces of ...

The KNN algorithm was first developed in 1951, and KNN has been routinely used in Web applications for several decades. However, until recently, ... MongoDB vector search indexes provide a better ...

The BM42 search algorithm marks a significant step forward beyond traditional text-based search for RAG and AI applications. BM42 provides enterprises another choice – not just traditional text ...

Vector databases are a critical component of the emerging GenAI stack because they store the vector embeddings generated ahead of time by LLMs, such as those offered in Amazon Bedrock. At runtime, the ...