Core Viewpoint - The article discusses the impact of Typhoon "Hagupit" on coastal cities in Guangdong, emphasizing the need for improved disaster preparedness and response strategies in the context of climate change and increasing extreme weather events [2][12]. Group 1: Typhoon Impact and Response - Typhoon "Hagupit" made landfall in Guangdong, classified as a strong typhoon with wind speeds reaching up to 17 levels, causing significant disruptions including the cancellation of flights and train services [1][6]. - The official designation of the typhoon as a "major disaster" highlights its severity, drawing comparisons to Typhoon "Mangkhut" in 2018, which affected nearly 3 million people across five provinces [2]. - The Guangdong government implemented emergency measures, including the "Five Stops" protocol (stopping work, business, markets, transport, and classes), and successfully evacuated over 2.22 million people in preparation for the storm [7][12]. Group 2: Climate Change and Disaster Preparedness - Experts indicate that while the number of typhoons may not significantly change, their intensity is likely to increase due to rising ocean and atmospheric temperatures, necessitating enhanced disaster preparedness [2][8]. - The article emphasizes the importance of upgrading infrastructure and improving meteorological forecasting capabilities to better handle extreme weather events [4][11]. Group 3: Technological Integration in Disaster Management - The use of artificial intelligence and big data analytics is becoming crucial in predicting typhoon paths and intensities, enhancing the accuracy of forecasts and allowing for timely evacuations [10][11]. - Cities like Guangzhou and Shenzhen are implementing smart water management systems and digital platforms to monitor and respond to flooding and other disaster-related challenges [14][15]. Group 4: Community Involvement and Resilience - Community engagement is highlighted as a vital component of disaster response, with local volunteers and grid workers playing key roles in ensuring safety and effective communication during typhoons [16]. - The article showcases successful local initiatives, such as the proactive evacuation measures taken in Dongguan, which ensured minimal disruption to daily life post-typhoon [16].

Core Insights - The 2025 World Artificial Intelligence Conference showcased the rapid acceleration of AI applications across various sectors, highlighting its transformative potential in industries and scientific research [1][10]. Weather Forecasting and Disaster Warning - AI models in meteorology, such as "Rain Master" and "Fuyou," can advance disaster warnings by 15 to 45 minutes, enhancing urban disaster preparedness [2][3]. - The "Rain Master" model provides detailed insights into severe convective weather, while "Fuyou" focuses on short-term heavy rainfall and thunderstorms, improving forecast updates from hourly to every 10 minutes [3]. - The "MAZU" early warning system integrates AI technology with advanced algorithms and multi-source data for comprehensive disaster alerts [3][4]. Industrial Empowerment - AI is increasingly integrated into various industries, enhancing efficiency and quality, with examples including Siemens' industrial AI system that autonomously executes production tasks [7][8]. - Over 200 companies and 150,000 workers are collaborating with Siemens' AI system, which is expected to be implemented in China within the year [8]. - Tencent's "Magical Digital Human" improves content production efficiency by 50% and reduces live-streaming costs by up to 90%, applicable in e-commerce, education, and finance [8]. Scientific Discovery and Innovation - The term "AI4S" (Artificial Intelligence for Science) signifies the use of AI in scientific discovery, marking a shift from traditional research paradigms to innovative solutions in complex systems [11]. - AI4S has achieved breakthroughs in various fields, including quantum computing and life sciences, with significant advancements such as defect-free arrangement of quantum bits and new cancer treatment targets [11][13]. - The integration of AI into the entire research lifecycle is propelling scientific discovery towards large-scale innovation [13].