1 min read
Azure AI Search: Implementing Hybrid Search with Vectors and Keywords
Hybrid search significantly improves retrieval quality for RAG applications by leveraging both semantic understanding and exact keyword matching.
Semantic Search
9 articles
1 min read
Building AI-Powered Search with Azure AI Search and Semantic Ranker
Monitor reranker scores and caption extraction quality. A/B test semantic ranking against pure vector or keyword search to quantify improvements for your…
7 min read
Azure AI Search Semantic Ranker: Configuration, Thresholds and Cost
How to design semantic configurations, use reranker scores as a RAG cut-off, and decide when Azure AI Search's semantic ranker is worth paying for.
7 min read
Azure AI Search After Ignite 2023: What's GA and What's Still Preview
A January 2024 stock-take of Azure AI Search for RAG: which features are GA, which are preview, and which SDK and REST versions to build on.
1 min read
Azure Cognitive Search Vector Search: Building Semantic Search Applications
Vector search enables powerful semantic search capabilities. Tomorrow, I will cover hybrid retrieval patterns in more detail.
1 min read
Semantic Search for Enterprise: Beyond Keyword Matching
Enterprise semantic search transforms how organizations find and use knowledge. By understanding meaning rather than just matching keywords, these systems…
1 min read
Building Semantic Search with Azure OpenAI Embeddings
Embeddings are numerical representations of text that capture semantic meaning. Similar concepts have similar vectors. Azure OpenAI provides the…
8 min read
Semantic Search Prototype: Azure OpenAI Embeddings and NumPy
Build a small semantic search prototype on Azure OpenAI embeddings and NumPy, measure it with hit rate@k, add BM25, and know when to move to a real index.
1 min read
Semantic Search in Azure Cognitive Search
Semantic search dramatically improves search relevance by understanding user intent rather than just matching keywords.