Transitive and commutative multimodal models and uses

A computer-implemented method comprising:

• obtaining an input data set comprising data from one or more modalities selected from a set of at least three modalities;
• and
• generating an output data set by processing the input data set using a machine learning model comprising a transitive and commutative machine-learning model,
• wherein a transitive and commutative machine-learning model is a machine learning model that has been trained to transform input data sets corresponding to any and each of the modalities of the set of least three modalities to output data sets of any and each other of the modalities of the set of at least three modalities, wherein the machine learning model has been trained to transform data between two modalities by using training data that includes data pairs corresponding to a first of the two modalities and another modality and other data pairs corresponding to the other modality and a second of the two modalities, and the machine learning model has been trained to perform a corresponding reverse type of modality transformation for any forward type of modality transformation that the model has been trained to perform.