The advent of machine learning and artificial intelligence has opened diverse possibilities, not least in the form of extracting greater interpretability from extant and interpretable biophysical data. This event aims to trigger crosstalk between biophysicists, theoreticians and data scientists to see how seemingly different groups can mutually benefit from each other. It is hoped that that the exercise will facilitate novel collaborative ventures.