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AI Glossary

What is Embeddings?

Numerical representations of text that capture semantic meaning for AI processing.

By Council Research TeamUpdated: Jan 27, 2026

Definition

Embeddings convert text into vectors (lists of numbers) that capture semantic meaning. Similar concepts have similar embeddings, enabling semantic search, clustering, and RAG systems. They're fundamental to how AI understands and compares text.

Examples

1Finding similar documents
2Semantic search (meaning, not keywords)
3Clustering customer feedback

Why It Matters

Embeddings power semantic search and RAG, enabling AI to find relevant information based on meaning.

Related Terms

RAG (Retrieval-Augmented Generation)

Combining AI with real-time information retrieval from external knowledge bases.

Common Questions

What does Embeddings mean in simple terms?

Numerical representations of text that capture semantic meaning for AI processing.

Why is Embeddings important for AI users?

Embeddings power semantic search and RAG, enabling AI to find relevant information based on meaning.

How does Embeddings relate to AI chatbots like ChatGPT?

Embeddings is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Finding similar documents Understanding this helps you use AI tools more effectively.

Related Use Cases

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AI Models Using This Concept

ClaudeClaudeChatGPTChatGPTGeminiGemini

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