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May 16, 2026 · 1 min read

How do embeddings work in vector databases, and what are some of the common algorithms used for creating them?

Embeddings in vector databases represent high-dimensional data points in a lower-dimensional space. Common algorithms for creating embeddings include Word2Vec, GloVe, and more recent approaches like BERT and sentence transformers, which…

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📅 May 16, 2026 ⏱ 1 min read

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How do embeddings work in vector databases, and what are some of the common algorithms used for creating them?

COVER // HOW DO EMBEDDINGS WORK IN VECTOR DATABASES, AND WHAT ARE SOME OF THE COMMON ALGORITHMS USED FOR CREATING THEM?

Embeddings in vector databases represent high-dimensional data points in a lower-dimensional space. Common algorithms for creating embeddings include Word2Vec, GloVe, and more recent approaches like BERT and sentence transformers, which leverage deep learning techniques to capture semantic meaning.

embeddings machine learning natural-language-processing vector-databases

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