Tag: vector-database
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RAG — Retrieval-Augmented Generation
An LLM architecture that fetches relevant documents from an external knowledge base before generating a response, grounding answers in retrieved facts rather than training data alone.
2mo ago
ai_ml intermediate
Semantic Search
Search that matches by meaning and intent rather than exact keywords — a query for 'how to prevent database attacks' finds SQL injection documentation even if those exact words never appear.
2mo ago
ai_ml intermediate
Vector Database
A database optimised for storing and querying high-dimensional vector embeddings, enabling similarity search — finding items semantically close to a query rather than exact-match lookups.
2mo ago
ai_ml intermediate
Embeddings Dense numerical vector representations of text, images, or other data — capturing semantic meaning so that similar items have similar vectors and can be found via distance search.
2mo ago
ai_ml intermediate
Retrieval-Augmented Generation (RAG)
A pattern that combines document retrieval with LLM generation — relevant documents are fetched and injected into the prompt context, grounding responses in current, specific data.
2mo ago
ai_ml advanced
Vector Databases
Databases specialised for storing and querying high-dimensional vectors — enabling fast approximate nearest-neighbour search across millions of embeddings.
2mo ago
ai_ml intermediate