Charles Roques-Carmes, a Science Fellow at Stanford University, is interviewed by Yuval Boger. They discuss his work on using optical parametric oscillators as a form of random number generator with controllable bias. He elaborates on the potential applications of this technology in trainable randomness for Bayesian neural networks and logistics planning, previews the next steps for this research, and much more.