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PQ

Product Quantization (PQ) is a lossy compression technique for high-dimensional vector embeddings that decomposes a vector space into a Cartesian product of smaller subspaces, quantizing each independently to drastically reduce memory footprint and accelerate Approximate Nearest Neighbor (ANN) searches.

Definition

Product Quantization (PQ) is a lossy compression technique for high-dimensional vector embeddings that decomposes a vector space into a Cartesian product of smaller subspaces, quantizing each independently to drastically reduce memory footprint and accelerate Approximate Nearest Neighbor (ANN) searches.

Disambiguation

Not to be confused with Scalar Quantization; PQ compresses groups of dimensions (sub-vectors) rather than individual values.

Visual Metaphor

"A LEGO mosaic: instead of storing the exact position and color of every atom, you approximate sections of the image using a limited set of pre-defined plastic bricks from a kit."

Key Tools
FAISSMilvusWeaviateScaNNPinecone
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Conceptual Overview

Product Quantization (PQ) is a lossy compression technique for high-dimensional vector embeddings that decomposes a vector space into a Cartesian product of smaller subspaces, quantizing each independently to drastically reduce memory footprint and accelerate Approximate Nearest Neighbor (ANN) searches.

Disambiguation

Not to be confused with Scalar Quantization; PQ compresses groups of dimensions (sub-vectors) rather than individual values.

Visual Analog

A LEGO mosaic: instead of storing the exact position and color of every atom, you approximate sections of the image using a limited set of pre-defined plastic bricks from a kit.

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