Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable.
Vector search, sometimes referred to as vector similarity search, is a technique that uses vectors -- numerical representations of data -- as the basis to conduct searches and identify relevance. A vector, in the context of a vector search, is defined as a set of numbers mathematically compute...
Postgres does not have native vector capabilities as of Postgres 16, and pgvector is designed to fill this gap. You can store your vector data with the rest of your data in Postgres, do a vector similarity search, and still utilize all of Postgres’ great features. Who Needs Vector Simila...
Vector search is a search technique used to find similar items or data points, typically represented as vectors, in large collections.
Needless to say, the complexity of this can become quite daunting to try and comprehend. However, at the core of vector search is the ability to mathematically calculate the distance or similarity between vectors, and this is done with a number of mathematical formulas like cosine similarity or...
A vector database is an organized collection of vector embeddings that can be created, read, updated, and deleted at any point in time.
Vector search challenges Vector embeddings help us to find similarity between documents. When it comes to relevance, vector search is superior to keyword search for many types of queries. If they’re so great, why don’t we use vector search for everything? In fact, for many query types, ...
What is similarity search? If we think of vector embeddings as stars in vast cosmic constellations, similarity search, or vector search, would be like trying to find the nearest stars to your current position in space. In practical terms, this means finding the most relevant documents, images,...
In simpler terms, a vector database is like a library for high-dimensional data points, where each data point is represented as a vector of numbers, and the database is optimized to quickly find other vectors that are similar to a specified vector. This similarity search process is crucial ...
What is vector search?Completed 100 XP 4 minutes Vector search is a new capability available in AI Search used to index, store and retrieve vector embedding from a search index. You can use it to power applications implementing the Retrieval Augmented Generation (RAG) architecture, similarity and...