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Intermediate

Embedding Dimensionality

The fixed number of scalar values in a vector that represent the semantic features of a data point. In RAG architectures, it defines the size of the latent space where text chunks are mapped, directly impacting the granularity of semantic search and the memory requirements of the vector store.

Definition

The fixed number of scalar values in a vector that represent the semantic features of a data point. In RAG architectures, it defines the size of the latent space where text chunks are mapped, directly impacting the granularity of semantic search and the memory requirements of the vector store.

Disambiguation

Not the total count of vectors in a database, but the numerical length of a single vector.

Visual Metaphor

"The number of 'GPS coordinates' required to find a specific thought in a high-dimensional library; more coordinates provide a more precise location but require a larger map."

Key Tools
OpenAI text-embedding-3-largeHugging Face Sentence TransformersCohere EmbedPineconeMilvusFaiss
Related Connections

Conceptual Overview

The fixed number of scalar values in a vector that represent the semantic features of a data point. In RAG architectures, it defines the size of the latent space where text chunks are mapped, directly impacting the granularity of semantic search and the memory requirements of the vector store.

Disambiguation

Not the total count of vectors in a database, but the numerical length of a single vector.

Visual Analog

The number of 'GPS coordinates' required to find a specific thought in a high-dimensional library; more coordinates provide a more precise location but require a larger map.

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