Embedding Space

The d-dimensional vector space that features from a higher-dimensional vector space are mapped to. Embedding space is trained to capture structure that is meaningful for the intended application. The dot product of two embeddings is a measure of their similarity.

In Generative AI, embedding space refers to a numerical representation of text, images, or videos that captures relationships between inputs. Machine learning models, particularly generative AI models, are adept at creating these embeddings by identifying patterns within large datasets. Applications can utilize embeddings to process and generate language, recognizing complex meanings and semantic relationships specific to the content.