Embeddings

Embeddings are vectors in multidimensional space (the latent space) that can capture the meaning of words, phrases, or other data. Embedding also describes the process itself, i.e. the step of translating inputs into this numerical format.

Neural networks can use embeddings to understand context, identify patterns, and perform tasks like translation, sentiment analysis, and generating text.

Embeddings can also provide useful applications outside of neural networks, as similar concepts are positioned closer together in the numerical space, embeddings allow for similarity comparisons of complex information.