Introduction SQL Server 2025 introduced new features, including vectors. The main purpose of vectors is to create a new semantic search with the help of AI. Modern AI models represent text as vectors (embeddings) that capture semantic meaning. Similar meanings produce vectors that are close to each other in this vector space, allowing AI systems to […]
2026-03-23
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Searching for relevant information in vast repositories of unstructured text can be a challenge. This article explains a Python-based approach to implementing an efficient document search system using FAISS (Facebook AI Similarity Search) for Vector DB and sentence embeddings, which can be useful in applications like chatbots, document retrieval, and natural language understanding. In this […]
2025-01-17
3,480 reads
By HeyMo0sh
DevOps is about shortening the system development lifecycle. Plan faster, build faster, test faster,...
A short blog post about an issue with Fabric Mirroring (with Azure SQL DB...
By Steve Jones
I wrote an article recently on the JSON_OBJECTAGG function, but neglected to include an...
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When thinking about the identity property and sequence objects, which of these can generate values before an insert statement is executed?
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