Resources:
Neon Vector Database:  https://fyi.neon.tech/gs1
AWS Transcribe: https://aws.amazon.com/pm/transcribe

This is how I built an AI teaching assistant with vector databases and ChatGPT. The bot uses the RAG model to answer user questions in real-time.

This project took some time to create, and you can see it in action below:
https://interviewready.io/learn/system-design-course

00:00 Agenda
00:16 Problem Statement
01:15 Vanilla ChatGPT
03:22 Vector Databases
06:49 Implementation
07:42 Internal Algorithms
09:30 Demo
11:17 RAG Model 
12:03 Hmm...

#AI #VectorDatabase #RAG

YouTube

Learn how to build an AI teacher using vector databases and ChatGPT. The process involves using OpenAI's APIs and vector databases to store and retrieve relevant data from video and PDF transcripts. Neon vector database, integrated with PostgreSQL, offers efficient handling of similar content for AI-driven responses. Tools such as AWS Transcribe aid in converting video content to text. This setup aims to provide quick, contextually accurate responses to user queries.

How I built an AI Teacher with Vector Databases and ChatGPT

<p>Great article! For those exploring vector DB options, you might also want to check out Astra DB - it handles vector embeddings really well and scales automatically. Love how you’ve broken down the AI teacher implementation process - very clear and practical approach.</p>
