Vector Embeddings — Topic Summaries
AI-powered summaries of 6 videos about Vector Embeddings.
6 summaries
How I Set Up My AI-Powered Second Brain in Obsidian (ChatGPT, Search, Assistant, Plugins, Tools)
A practical setup for an “AI-powered second brain” in Obsidian centers on embedding ChatGPT directly inside the workspace and then using a paid...
I Built My Second Brain with AI (GPT-3)
A “second brain” built from personal notes can be made searchable by converting text into vector embeddings and then using semantic search to answer...
RAG vs Context Window - Gemini 1.5 Pro Changes Everything?
The central shift driving the hype is simple: very large context windows—paired with faster hardware—are making “put everything in the prompt”...
Easy RAG Setup - Load Anything into Context - Mistral 7B / ChromaDB / LangChain
A practical RAG (retrieval-augmented generation) pipeline can be built in roughly 90 lines of code by pairing LangChain with ChromaDB for vector...
OpenAI DevDay 2024 | Community Spotlight | Supabase
Supabase is pitching an AI-powered PostgreSQL playground that lets a model run real database operations end-to-end inside the browser—turning “code...
How to Integrate RAG - Retrieval Augmented Generation into a LLM? (Practical Demo)
Retrieval-Augmented Generation (RAG) is presented as a practical way to make a language model answer questions using external, user-provided sources...