  The development and adoption of artificial intelligence (AI) technologies in
space applications is growing quickly as the consensus increases on the
potential benefits introduced. As more and more aerospace engineers are
becoming aware of new trends in AI, traditional approaches are revisited to
consider the applications of emerging AI technologies. Already at the time of
writing, the scope of AI-related activities across academia, the aerospace
industry and space agencies is so wide that an in-depth review would not fit in
these pages. In this chapter we focus instead on two main emerging trends we
believe capture the most relevant and exciting activities in the field:
differentiable intelligence and on-board machine learning. Differentiable
intelligence, in a nutshell, refers to works making extensive use of automatic
differentiation frameworks to learn the parameters of machine learning or
related models. Onboard machine learning considers the problem of moving
inference, as well as learning, onboard. Within these fields, we discuss a few
selected projects originating from the European Space Agency's (ESA) Advanced
Concepts Team (ACT), giving priority to advanced topics going beyond the
transposition of established AI techniques and practices to the space domain.
