The FAIR Principles have two aspects: They were written specifically for research data and they also claim to be general for all research objects. In practice, this means that while the high-level concepts (findable, accessible, interoperable, and reusable) are generally applicable, the details of the wording, their context, and how they are applied is not. Different groups have been studying how the FAIR principles could be applied to other types of research objects, such as research software, machine learning models, and workflows, and this session will include talks on these three efforts and their status, followed by questions from the audience to the speakers and moderator.