Core Insights - Jinqiu Fund is dedicated to supporting innovative founders in the AI sector and engaging with leading AI pioneers to navigate industry transformations [2][3] - The first "AI Pioneers" list was recently announced, highlighting key figures in the AI field who are shaping the future [3][14] Group 1: Evaluation Process - The evaluation panel for the "AI Pioneers" list included industry experts from investment and media, as well as innovative developers and prominent figures from the Zhihu community [4][6] - The selection criteria focused on five dimensions: innovation, critical thinking, influence, ecological value, and development potential [12][13] Group 2: Notable Figures - The list features prominent individuals such as Wang Xingxing, CEO of Yushu Technology, and other leaders from institutions like Carnegie Mellon University and the Chinese Academy of Sciences [3][24][26] - These individuals are recognized for their contributions to AI technology, including advancements in deep learning frameworks and AI applications across various industries [19][21][23] Group 3: Future Outlook - The "AI Pioneers" list serves not only as a recognition of current leaders but also as a record of those exploring new boundaries and developing innovative tools in the AI landscape [28][29] - The ongoing nomination process for the next list encourages broader participation from the community to identify emerging talents in the AI sector [29]

Core Insights - The East China Air Traffic Management Bureau has successfully launched an intelligent system for air traffic control, marking a significant step in the transformation and upgrade of air traffic control services [1][5] - The intelligent system integrates professional knowledge and business processes in air traffic control, enabling intelligent data analysis, fault simulation, and operational decision support [1][2] Group 1: System Features - The intelligent system is built on advanced large language models and reasoning technologies, allowing it to deeply understand air traffic control knowledge and processes, thereby enhancing operational efficiency [2][5] - It serves as a "multi-faceted expert," breaking down information barriers and converting complex business processes into efficient digital solutions [2][5] Group 2: Application Scenarios - Four major intelligent application scenarios have been customized to enhance operational efficiency, including a qualification inspection application that significantly improves employee learning efficiency by reducing information retrieval time from over 10 minutes to around 1 minute, achieving a 90% efficiency increase [3] - Other applications include automated log analysis for quick historical record retrieval, a rapid Q&A function for technical documents, and an emergency troubleshooting assistant that provides decision-making references based on historical fault cases [3] Group 3: Technical Infrastructure - The system development utilized the Dify platform, which supports low-code development and allows for flexible integration of various models, significantly simplifying the AI application construction process [4] - The vLLM framework was employed for virtualization deployment, achieving high concurrency and low latency, which is crucial for the real-time and safety-critical nature of air traffic control [4] Group 4: Future Directions - The launch of the intelligent system demonstrates the feasibility of large model technology in high-safety industries, with plans for further integration of multimodal capabilities, including voice, image, and video recognition [5] - The technical team aims to enhance the intelligent system's multi-source perception capabilities and promote the comprehensive implementation of various AI application scenarios [5]