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How I built an AI Teacher with Vector Databases and ChatGPT



Gaurav Sen

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

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23 thoughts on “How I built an AI Teacher with Vector Databases and ChatGPT
  1. I wonder how useful this will be whilst replying to question specific or detailed doubts (such as while walking through the solution of a difficult math question a student might have a doubt about how did we go from one equation to the other). This would however obviously depend on the capabilities of ChatGPT and if it is not able to answer, what better could have been done?

  2. Hi Gaurav, Thanks for the video. I want to try with simple small book transcript in to vector db, augmented and use free model. Is there any free vector DB and LLM model which I can play with ??

  3. Great video! I may have missed it, but did you talk about vector embedding and embedding models that turn this data into vectors to make a similarity search. Also wanted to know if neon automatically did that that.

  4. Hey Gaurav, good video. Not as good as your newer ones though.
    07:00 minutes into your video and you have not mentioned RAG even once, not said why you are using a vector, not mentioned vectorization process. This was way too focused on vector DB of your experience w/o enough context.

    Fan of your videos, btw.

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