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# The Rise of Vector Databases: Understanding Vector Search and RAG Pipeline

**[Towards AI](https://daily.dev/sources/tai)** · 7 min read · 21 upvotes · 0 comments

## Summary

This post explains the fundamentals of vectors and vector databases, as well as the implementation of vector searches and Retrieval-Augmented Generation (RAG) using Qdrant Vector Database. It covers the applications of vector databases in NLP, recommendation engines, and image/video searches. The post also provides a step-by-step guide on how to perform vector searches using Qdrant database and how RAG can be used to improve the accuracy of language models.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pub.towardsai.net/the-rise-of-vector-databases-640f7db2dca0>

---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#nlp](https://daily.dev/tags/nlp), [#vector-search](https://daily.dev/tags/vector-search)

[View this post on daily.dev](https://daily.dev/posts/the-rise-of-vector-databases-understanding-vector-search-and-rag-pipeline-50e9ihqdy)

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