Neuromorphic ionic computing, which uses principles similar to a human brain, represents a groundbreaking direction in computational technology, promising substantially improved energy efficiency compared with traditional silicon-based platforms. In a Review, Aluru et al. highlight essential gaps in knowledge spanning multiple domains such as materials science, device design, system integration, chemical compatibility, and biocompatibility that must be addressed. The authors emphasize the critical role of interdisciplinary collaboration in realizing the full promise of this emerging field. By advancing these areas, neuromorphic ionic systems could provide new possibilities for energy-efficient computing, with applications ranging from artificial intelligence to robotics and beyond. —Yury Suleymanov