标题： 选自：空间应用中的人工智能趋势 显示英文标题

标题： Selected Trends in Artificial Intelligence for Space Applications

摘要： 随着人们对人工智能（AI）技术带来的潜在好处达成共识，其在航天应用中的发展和采用正在迅速增长。越来越多的航空航天工程师开始意识到人工智能领域的新趋势，传统方法也得以重新审视，以考虑新兴人工智能技术的应用。 截至撰写本文时，学术界、航空航天工业以及航天机构中与人工智能相关的活动范围如此广泛，以至于一篇深入的综述无法在此处涵盖所有内容。 在本章中，我们关注我们认为最相关且令人兴奋的两大新兴趋势：可微智能和机载机器学习。 简而言之，可微智能是指广泛使用自动微分框架来学习机器学习模型或其他相关模型参数的工作。 机载机器学习则涉及将推理和学习任务转移到航天器上的问题。 在这些领域内，我们将重点讨论欧洲航天局（ESA）先进概念团队（ACT）发起的一些精选项目，优先介绍超越将已建立的人工智能技术和实践简单移植到航天领域的高级主题。 显示英文摘要

摘要： 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.