# Embedding

Concept · [Building with AI](https://ecosystem.samcarlton.com/ai)

Also called: embeddings, text embedding, semantic meaning

A way of turning a piece of text into a [list of numbers](https://ecosystem.samcarlton.com/vector) that captures its meaning, so software can tell which pieces of text are about similar things.

**For example:** The sentences 'How do I get my money back?' and 'What is your refund policy?' share few words, but their embeddings are close because they mean nearly the same thing.

## Connects to (14)

- [Vector database](https://ecosystem.samcarlton.com/vector-database): A database built to store embeddings and quickly find the items closest in meaning to a question, not just the ones that share its exact…
- [RAG](https://ecosystem.samcarlton.com/rag): Retrieval-augmented generation.
- [LLM](https://ecosystem.samcarlton.com/llm): Large language model.
- [Vector](https://ecosystem.samcarlton.com/vector): An ordered list of numbers.
- [Dimension](https://ecosystem.samcarlton.com/dimension): One number position in a vector, like one axis on a map.
- [Similarity search](https://ecosystem.samcarlton.com/similarity-search): Finding the stored items whose vectors are closest to a query's vector, so results match by meaning rather than exact words.
- [Chunking](https://ecosystem.samcarlton.com/chunking): Splitting long documents into smaller passages before creating embeddings, so a search can return just the relevant part instead of a…
- [Attention](https://ecosystem.samcarlton.com/attention): The part of a language model that decides, for each token, how much every other token in the input should shape its meaning.
- [Latent space](https://ecosystem.samcarlton.com/latent-space): The internal map of numbers where a model places the things it reads.
- [Knowledge graph](https://ecosystem.samcarlton.com/knowledge-graph): A way of storing information as things and the named connections between them, such as 'course A teaches skill B'.
- [Recommendation engine](https://ecosystem.samcarlton.com/recommendation-engine): Software that suggests items a person is likely to want, based on what they and similar people have done before.
- [Cosine similarity](https://ecosystem.samcarlton.com/cosine-similarity): A common way to measure how alike two vectors are by the angle between them.
- [Tokenizer](https://ecosystem.samcarlton.com/tokenizer): The step that splits text into tokens, the small pieces a model actually reads, and turns each one into a number.
- [ONNX](https://ecosystem.samcarlton.com/onnx): An open file format for AI models, so a model trained with one tool can run with another, on servers, phones or in a browser.

Map view: https://ecosystem.samcarlton.com/embedding