Company
Date Published
Jan. 9, 2024
Author
Matt Webb
Word count
1886
Language
English
Hacker News points
None

Summary

The text discusses the implementation of semantic search using AI and embedding models. It explains how to convert any string of text into a vector and store it in a vector database, where nearby vectors mean approximately the same thing. The author demonstrates building a search engine for their side project website Braggoscope, which uses an unofficial directory of BBC Radio 4's show In Our Time. They walk through setting up a vector database, embedding model, and creating a minimal PartyKit server to manage indexing and querying. The text also touches upon the use of vector databases in retrieval-augmented generation (RAG) for AI chatbots and copilot experiences.