重磅资管会议，众多大咖发声

Core Insights - The conference focused on the integration of artificial intelligence (AI) in asset management, highlighting the historical opportunities presented by "AI + Asset Management" [2][3] - The event gathered over 300 participants from various sectors, including government, finance, and technology, to discuss the application and development trends of AI in asset management [1] Group 1: AI Integration in Asset Management - The Shanghai Lingang New Area aims to become a benchmark financial technology hub by leveraging its unique advantages in financial openness and innovation [2] - The Intelligent Investment Research Technology Alliance (ITL) has grown from 72 to 333 member institutions over five years, indicating a significant expansion in the sector [2] - AI technologies, particularly large models, are transforming asset management processes such as research, advisory, trading, and risk control [3] Group 2: Challenges and Solutions in AI Development - Key challenges in AI model development include the misalignment of AI expansion laws with hardware capabilities, error accumulation in multi-agent collaboration, and ensuring AI safety and value alignment [4] - Solutions proposed include the "Federated Teacher-Student Model" for collaborative learning between general and specialized models [4] - The need for high-quality vertical data, foundational technology platforms, and enhanced AI safety and ethical governance was emphasized as critical for AI's successful implementation in finance [4] Group 3: Practical Applications of AI - AI is being applied in various industries, including satellite design, new materials development, and semiconductor manufacturing, presenting investment opportunities [6][7] - The integration of AI in semiconductor manufacturing is particularly highlighted, with a focus on improving operational efficiency and increasing domestic production rates [6][7] - The financial sector is seeing a shift from "information disparity" to "model disparity," necessitating improvements in data governance and organizational structures to fully leverage AI capabilities [8] Group 4: Future Directions and Ecosystem Development - The establishment of a trusted data space in the securities industry aims to reduce the complexity and cost of applying large models, fostering AI innovation [8] - The importance of a multi-disciplinary team with a blend of curiosity and cross-functional skills was identified as essential for overcoming challenges in AI integration [8][9] - The Shanghai Asset Management Association is focusing on enhancing the global competitiveness of Shanghai as an asset management center through digitalization and AI integration [10]