👉 Gaps computing refers to the emerging paradigm that addresses the limitations of traditional computing by focusing on the dynamic and unpredictable nature of real-world data and problems. It acknowledges that many challenges, especially in areas like climate modeling, healthcare, and social sciences, involve complex, interconnected systems with inherent uncertainties. Gaps computing aims to bridge these gaps by integrating diverse data sources, leveraging machine learning and AI, and fostering interdisciplinary collaboration to provide more adaptive, context-aware, and holistic solutions. Unlike conventional computing, which often relies on static models and assumptions, gaps computing embraces fluidity, continuously learning from new data to improve predictions and decision-making in the face of incomplete or evolving information.
