# Vector embeddings explained: from theory to real-world use

DevFeed: [Vector embeddings explained: from theory to real-world use](<https://devfeed.tech/articles/vector-embeddings-explained-from-theory-to-real-world-use-4859.md>)

Original publisher: [Read original article](<https://redis.io/blog/vector-embeddings-explained/>)

Author: Jeff Mills

Published: 2026-07-13T00:00:00Z

Content type: article

Language: en

Sources: [Redis Blog](<https://devfeed.tech/sources/redis-blog.md>)

Topics: [AI search](<https://devfeed.tech/topics/ai-search.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>)

Tags: [embedding](<https://devfeed.tech/tags/embedding.md>), [embeddings](<https://devfeed.tech/tags/embeddings.md>), [rag](<https://devfeed.tech/tags/rag.md>), [search](<https://devfeed.tech/tags/search.md>), [tech-de](<https://devfeed.tech/tags/tech-de.md>), [vector](<https://devfeed.tech/tags/vector.md>)

## AI overview

A guide to vector embeddings: dense numerical representations that capture semantic similarity and support semantic search, recommendations, RAG pipelines, and large-scale vector querying.

## Source excerpt

Type "songs for a rainy Sunday morning" into a music app and you'll get results that match the mood, even though none of those words appear in the track titles. That kind of result is often powered by vector embeddings, numerical representations of me...