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AI Vector Search allows you to conduct searches on both structured and unstructured data by understanding its semantics or meaning, as well as its values. Combining relational data, JSON documents, graphs, geospatial data, text, and vectors in a single database enables you to rapidly build new ...
vb (mainly tr) , means, meaning or meant 1. (may take a clause as object or an infinitive) to intend to convey or express 2. (may take a clause as object or an infinitive) intend: she didn't mean to hurt it. 3. (may take a clause as object) to say or do in all seriousn...
At its core, the FM infers the next token based on a set of input tokens. Atokenin this case refers to any element with semantic meaning, like a word or phrase in text generation. The more contextually relevant input tokens you provide, the higher the likelihood that the next tok...
use of color does more than just look good—color breathes life into art and creates the mood and vibe of an image. Colors evoke emotions and help communicate meaning. Read this chapter for tips on using color in your art and details about working with colors in common graphic design ...
a combination of business and semantic data can be faster and more precise if both data types are available in a single database. This approach also avoids the data consistency problems introduced when using a separate, specialized vector database in addition to the business’s primary database....
Semantic search:Perform searches based on the meaning or context of a query, enabling more precise and relevant results. Because both words and phrases can be represented as vectors, semantic vector search functions understand user intent better than general keywords. ...
In a well-configured word embedding scheme, subtracting the vector for “man” from the vector for “king” and adding the vector for “woman” should essentially yield the vector for “queen.” Sentence embeddings Sentence embeddings embed the semantic meaning of entire phrases or sentences, ...
In this post, we explore how to use MemoryDB for performing a vector search in an e-commerce use case to create a real-time semantic search engine. Vector search for MemoryDB Vectors are numerical representations of data and its meaning, created using machine learning (ML), ca...
Convert Query to Vector:Weaviate vectorizes the text query using a vectorization module (OpenAI, Sentence Transformers). This vector encodes the query’s semantic meaning, enabling the system to search based on context instead of purely exact keyword matches. ...