Methods and systems for identifying and generating images of faces attractive to many people

A computer-implemented method of identifying faces attractive to many people, comprising steps of

• A. for each of multiple individuals, training for that respective individual a respective model that models the attractiveness preferences of that respective individual based on (i) embeddings of a plurality of images of faces rated for attractiveness by that respective individual and (ii) respective ratings given by that respective individual to those respective images of faces, where the training of each model includes applying said embeddings and said respective ratings to an artificial intelligence engine,
• B. applying to the artificial intelligence engine and to each of multiple said models trained in step (A) an embedding of an image of a face of a candidate to predict how attractive that image is likely to be to a group represented by the multiple respective individuals for which the respective models were trained in step (A),
• C. generating a digital image based on the prediction in step (B).

A computer-implemented method of identifying faces attractive to many people, comprising the steps of:

• A. for each of multiple individuals, training for that respective individual a respective model that models the attractiveness preferences of that respective individual based on (i) embeddings of a plurality of images of faces rated for attractiveness by that respective individual and (ii) respective ratings given by that respective individual to those respective images of faces, where the training of each model includes applying said embeddings and said respective ratings to an artificial intelligence engine,
• B. applying to the artificial intelligence engine and to each of multiple models trained in step (A) respective embeddings of multiple images of faces to predict how relatively attractive those respective images are likely to be to a group represented by the multiple respective individuals for which the respective models were trained in step (A),
• C. generating a digital image of one of the multiple candidates selected on a basis of the predictions in step (B).