AI for Beginners - Using FAISS with GPT API (vector DB example)

In this video, I explain what vector databases are and how they can be used instead of traditional cosine similarity functions for scalable and efficient searching in AI and machine learning applications. I introduce FAISs, Facebook's AI similarity search, as a powerful tool for storing and retrieving vector embeddings. I walk through the process of embedding documents, creating an index, and querying it to find similar documents based on a given input. I demonstrate how to normalize vectors and retrieve the top three similar documents, highlighting their similarity scores. Viewers are encouraged to follow along and implement the code changes to see how vector databases can enhance their projects.

Timestamps
0:00 Different Types of DB
2:17 Code example of FAISS
3:52 Storing Documents in DB
5:02 Query Embedding
5:32 Final Results

GIT Repo - https://github.com/stocke777/AI_Tutorials

SETUP Video (Conda + GPT) - https://www.youtube.com/watch?v=Oqe5V8bwAo8

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Видео AI for Beginners - Using FAISS with GPT API (vector DB example) канала Jaivardhan_Deshwal