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
7,469 reads
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
3,441 reads
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