Vectors are used in science to describe anything that has both a direction and a magnitude. They are usually drawn as pointed arrows, the length of which represents the vector's magnitude. A quarterback's pass is a good example, because it has a direction (usually somewhere downfield) and a...
we are querying for rows that match our query. However, vector databases work with vectors rather than strings, etc. Vector databases also apply a similarity metric which is used to help find a vector most similar to the query.
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Vector embeddings are the core component of enabling machine learning and AI. Once data is turned into vectors we need to store all the vectors in a highly scalable, highly performant repository called avector database. Once data has been transformed and stored as vectors that data can now pow...
What are vectors give one example? A vector in mathematics is a quantity that has both magnitude and direction but not position. In other words, the vector is the movement of particles from one place to another where the magnitude is the distance traveled by those objects and direction is th...
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Storage Options: There are two primary storage options. The in-memory storage option keeps all vectors in RAM, which allows for the highest speed in data access since disk access is only required for persistence. Alternatively, the Memmap storage option creates a virtual address space linked with...
The index is built using a hashing function. Vector embeddings that are nearby each other are hashed to the same bucket. We can then store all these similar vectors in a single table or bucket. When a query vector is provided, its nearest neighbors can be found by hashing the query vector...
Embedding models are used for ingesting data and understanding user prompts. Upon receiving a query from the user, chatbot, or AI application, the system parses it and uses an embedding model to get vector embeddings representing parts of the prompt. The prompt’s vectors are then used to do...
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