🌱Terminology Guide

Guide to the terminology used in Vector AI

An example of a document in Vector AI:

document_example = {
    "car": {
        "wheels":
            {
                "number": 4
            }
        }
    }
}

Terminology	Definition
Vectors	AKA embeddings, 1D arrays, latent space vectors
Models/Encoders	Turns data into vectors (e.g. Word2Vec turns words into vectors)
Vector Similarity Search	Nearest neighbor search, distance search
Collection	Index, Table (a collection is made up of multiple documents)
Documents	(AKA JSON, item, dictionary, row) - a document can contain vector and other important information.
Field	A field is the key to a Python dictionary.
Value	A value is the value of a Python dictionary