Machine learning in claims reserving is an exciting area of actuarial research, with the promise of higher accuracy or greater insight and moving beyond limitations of traditional methods. Jacky Poon makes the case for ML in claims reserving, demystify the key concepts, and then provide an update of the recent progress and future goals of the Machine Learning in Reserving Working Party. We aim to leave attendees with a clear understanding of the current state and future direction of ML in claims reserving.