Mark discusses the concept of sparse upcycling, a technique used in training mixture of experts models. This method allows for the combination of smaller models into a larger architecture, optimizing efficiency by activating only a subset of parameters during queries. The distinction between dense and sparse models is crucial, as it highlights the computational advantages of utilizing a mixture of experts approach.
