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@@ -26,7 +26,7 @@ Let's look at the central concept of vector databases — [**vectors**](/documen
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Vectors (also known as embeddings) are high-dimensional representations of various data points — texts, images, videos, etc. Many state-of-the-art (SOTA) embedding models generate representations of over 1,500 dimensions. When it comes to state-of-the-art PDF retrieval, the representations can reach [**over 100,000 dimensions per page**](/documentation/advanced-tutorials/pdf-retrieval-at-scale/).
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This brings us to the first challenge of vector search — **vectors are heavy**.
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This brings us to the first challenge of vector search — vectors are heavy.
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### Vectors are Heavy
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