bedding for male give us a word embedding very close to the word embedding for King so you can actually do algebra in latent space and have it correspond to semantics the authors of the DC GaN paper showed that generative adversarial networks provide a similar property for images in particular if we take the word or the image embedding for images of a man with glasses and subtract the embedding for images of a man and add the embedding for images of a woman we obtained the embedding that corresponds to images of women with