Aging is the principal risk factor in many chronic diseases such as cancer, cardiovascular, and metabolic & neurological diseases. There is therefore great interest in the development of accurate age biomarkers that can be targeted and measured to track the effectiveness of therapeutic interventions and other lifestyle adjustments. In this recent paper, Alex Zhavoronkov et al. show how deep learning algorithms can help advance aging research.