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MongoDB Atlas Vector Search uses a technique called k-nearestneighbors (k-NN) to search for similar vectors. k-NN works by finding the k most similar vectors to a given vector. Vector data is a type of data that represents a point in a high-dimensional space.
We perform a k-nearestneighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. The summary describes an image related to the progression of naturallanguageprocessing and generative AI technologies, but it does not mention anything about particle physics or the concept of quarks.
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