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Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor (ANN) algorithms, [1] [2] so that one can search the database with a query vector to retrieve the closest matching ...
Vector space model or term vector model is an algebraic model for representing text documents (or more generally, items) as vectors such that the distance between vectors represents the relevance between the documents.
The Vector Institute is a private, non-profit artificial intelligence research institute in Toronto focusing primarily on machine learning and deep learning research.
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Other reports have indicated that registration for the bare term "GPT" seems unlikely to be granted, [73] [83] as it is used frequently as a common term to refer simply to AI systems that involve generative pre-trained transformers.
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In natural language processing (NLP), a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1] Word embeddings can be obtained using language modeling and feature ...