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 ...

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.

The vector search approach encapsulated in an algorithm called Space Partition Tree and Graph attempts to address the reality that growing data volumes have made keyword search “brittle.” The ...

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 ...

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, ...

Keyword search, often implemented using algorithms like BM25, remains a cornerstone of search technology. ... Vector Search: Ideal for semantic understanding, multilingual datasets, ...

Even a couple seconds for a search can make an app unusable,” said Bing group program manager Rangan Majumder. “We’ve only started to explore what’s really possible around vector search at ...