Cohere vs. OpenAI embeddings — multilingual search
In this video, we're going to work through a multilingual semantic search example using Cohere's new multilingual model. I also expect many of you will be curious about how it stacks up against OpenAI's GPT 3.5 text-embedding-ada-002 model, so we cover that too. Big thanks to @NilsReimersTalks — he basically wrote all of the code here and explained a ton of things to me. You should go look at his channel. He has a ton of useful content on semantic search. 📌 Notebook: https://github.com/pinecone-io/examples/blob/master/learn/search/multilingual/cohere-multilingual/cohere-multilingual-search.ipynb 🎙️ AI Dev Studio: https://aurelio.ai/ 👾 Discord: https://discord.gg/c5QtDB9RAP 🤖 70% Discount on the NLP With Transformers in Python course: https://bit.ly/3DFvvY5 🎉 Subscribe for Article and Video Updates! https://jamescalam.medium.com/subscribe https://medium.com/@jamescalam/membership 00:00 What are Cohere embeddings 00:46 Cohere v OpenAI on cost 04:37 Cohere v OpenAI on performance 06:37 Implementing Cohere multilingual model 07:55 Data prep and embedding 10:45 Creating a vector index with Pinecone 14:07 Embedding and indexing everything 17:24 Making multilingual queries 21:55 Final throughts on Cohere and OpenAI
