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Vector Embeddings for Developers: The Basics | Pinecone
Vector Embeddings for Developers: The Basics | Pinecone
You might not know it yet, but vector embeddings are everywhere. They are the building blocks of many machine learning and deep learning algorithms used by applications ranging from search to AI assistants. If you’re considering building your own application in this space, you will likely run into vector embeddings at some point. In this post, we’ll try to get a basic intuition for what vector embeddings are and how they can be used.
·pinecone.io·
Vector Embeddings for Developers: The Basics | Pinecone
What is a Vector Database & How Does it Work? Use Cases + Examples | Pinecone
What is a Vector Database & How Does it Work? Use Cases + Examples | Pinecone
Discover Vector Databases: How They Work, Examples, Use Cases, Pros & Cons, Selection and Implementation. They have combined capabilities of traditional databases and standalone vector indexes while specializing for vector embeddings.
semantic information retrieval
·pinecone.io·
What is a Vector Database & How Does it Work? Use Cases + Examples | Pinecone
Shelf space strategy for marketing developer tools
Shelf space strategy for marketing developer tools
When you build a new developer tool (a database, an AI/ML framework, a devops tool, etc...), you have to figure out how to make developers aware of it and start using it in their project. Traditional marketing techniques don’t really help. Literally zero developers saw your billboard on 101 during their commute or your keynote talk at Oracle open world and thought “I’ll use that distributed database in my thing at work”. But developers aren’t going to find your great new Thing on their own. You
·blog.jsr.wtf·
Shelf space strategy for marketing developer tools