Subscribe • Previous Issues The Vector Database Index If you work with text or images, chances are embeddings are already a key part of your machine learning and analytic pipelines. Embeddings are low-dimensional spaces into which higher-dimensional vectors can be mapped into. They can represent many kinds of data, whether a piece of text, an image or audio snippet, or a logged event. Embeddings capture some of the semantics of the inputs and place inputs that are semantically similar near each other in the embedding space. Thus, embeddings make AI applications much faster and cheaper without sacrificing quality.
Embed Retrieve Win
Embed Retrieve Win
Embed Retrieve Win
Subscribe • Previous Issues The Vector Database Index If you work with text or images, chances are embeddings are already a key part of your machine learning and analytic pipelines. Embeddings are low-dimensional spaces into which higher-dimensional vectors can be mapped into. They can represent many kinds of data, whether a piece of text, an image or audio snippet, or a logged event. Embeddings capture some of the semantics of the inputs and place inputs that are semantically similar near each other in the embedding space. Thus, embeddings make AI applications much faster and cheaper without sacrificing quality.