Building
Vector database
A special store that finds information by meaning rather than exact words.
A vector database keeps those meaning-based number lists called embeddings and is very fast at finding the ones most similar to a given query. Unlike a regular search that matches exact keywords, it can surface content that is related in meaning even if the wording is different. It is the workhorse behind letting AI find relevant material quickly.
For example
Search your notes for 'money worries' and a vector database also finds entries about 'financial stress.'
Related
RAG (retrieval-augmented generation)Letting an AI look up real documents before it answers.AI agentAn AI that can take actions and complete multi-step tasks on its own.Tool useAn AI reaching outside itself to use calculators, search, or other software.MCP (Model Context Protocol)A common standard that lets AI plug into apps and data sources.