Embeddings — Vector Embeddings
Definition: Numerical vector representations of text, images, or other data that capture semantic meaning. Embeddings power similarity search, recommendation, and the retrieval half of RAG systems.
Example
In AI strategy reviews, you'll often hear something like: "Let's pull the latest Embeddings numbers before we make a call" — shorthand for vector embeddings.
When you'll hear it
Embeddings shows up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. When someone uses it, they're usually referring to vector embeddings — and they expect the room to already know what that means.
FAQs
What does Embeddings stand for?
Embeddings stands for Vector Embeddings.
What does Embeddings mean in AI and machine-learning?
Numerical vector representations of text, images, or other data that capture semantic meaning. Embeddings power similarity search, recommendation, and the retrieval half of RAG systems.
Where will I hear Embeddings used at work?
Embeddings comes up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. It's used as shorthand for vector embeddings, so people assume you already know the term.
Related terms
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