Core Insights - The third Marine Intelligent Computing Conference was held in Guiyang from November 5 to 7, focusing on the integration of high-performance computing and artificial intelligence in marine science [1][3] - The conference aimed to create a global and open platform for technology and academic exchange, gathering experts and leaders in the field [1][3] Group 1: Importance of Marine Intelligent Computing - The ocean is a critical strategic space for national development, covering 71% of the Earth's surface, and marine intelligent computing is essential for understanding and managing marine resources [3] - High-performance computing and AI are transforming marine research paradigms, shifting from "observation-driven" to "computation-driven" and "intelligence-driven" approaches, enhancing capabilities in disaster warning, resource development, and environmental management [3][5] Group 2: Innovations and Applications - The integration of high-performance computing and AI with marine science has led to groundbreaking innovations, such as AI-driven storm surge disaster risk warning systems and high-resolution marine forecasting models [5][6] - The conference featured discussions on marine big data, intelligent forecasting, and new domestic software and hardware technologies, promoting key technological innovations and applications [5][6] Group 3: Expert Contributions and Research - Experts presented cutting-edge research, including advancements in storm surge disaster studies, marine satellite technology, and four-dimensional marine monitoring techniques [6] - The development of large models for marine forecasting is highlighted, showcasing their importance in various applications, including marine environment analysis and ice prediction [6] Group 4: Future Directions and Infrastructure - The demand for computational power in the marine sector is increasing, prompting the need for a robust ecological architecture for new computational bases to support marine model development [8] - The concept of Model as a Service (MaaS) is introduced, allowing users to access AI models as standardized cloud services, significantly lowering the barriers to AI adoption in marine applications [6][8]