There are a wide variety of different use cases for information retrieval and vector-powered retrieval systems.

In the blog section, we collate examples of these use cases and case studies from our contributors discussing how they use and improve information retrieval systems to solve real-world problems.

We are always looking to expand our Use Cases and share the latest thinking. So if you've been working on something and would like to share your experiences with the community, you 

Learn how information retrieval and vector powered retrieval systems can enhance your products with this comprehensive document. Featuring real-life case studies and in-depth analysis of the ML pipeline, it offers valuable insights for practitioners. Join

3.3 Conclusion

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Personalized Search: Harnessing the Power of Vector Embeddings

VectorHub

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Manifesto

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1.1 Data Velocity

1.2 Data Modality

1.3 Conclusion

1.0 Data Sources

2.1 Embedding Models

2.2 Pre-Trained vs Custom Models

2.3 Applications of Vector Compute

2.0 Vector Compute

3.1 Nearest Neighbor Search Algorithms

3.2 Key Access Patterns

3.0 Vector Search & Management

Building Blocks

A Recommender System: Collaborative Filtering with Sparse Metadata

Retrieval Augmented Generation

Enhancing RAG with a Multi-Agent System

Vector Embeddings in the browser

Toolbox

Markdown Formatting

Style Guide

Contributing

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Contents