Inner Product (IP)

The IP distance between two embeddings is defined as follows:

πŸ“˜

Kindly note

  1. IP is more useful if users would like to measure the orientation but not the magnitude of the vectors.
  2. If users use IP to calculate embeddings similarities, they must normalize the embeddings. After normalization, the inner product equals cosine similarity.