Vector databases have one thing in common — they support similarity searches. Similarity searches identify the “closest” record in the database to a vector. This is important for operations such as recommendation engines and personalization tools. Unlike keywords and SQL searches, similarity search ...
Cosine Similarity. Note that other comparison techniques exist. alwaysreturns a vector with 1536 dimensions, no matter what you try to get the embeddings for. Given that behavior, it is obvious that the larger the input text is, the more...
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