One could envision a model-sharing and transfer-learning community similar to those found today in the fields of computer vision and language modeling. Furthermore, the performance metrics explored here raise the tantalizing prospect of further improving model quality via a federated learning approach. This could enable researchers from diverse backgrounds and institutions to pool their data and expertise, leading to more powerful models.