Core Viewpoint - The article emphasizes the importance of integrating intelligent algorithms and data-driven approaches to enhance the efficiency and effectiveness of prosecutorial work, addressing existing mismatches in supply and demand, current practices and future trends, as well as capabilities and requirements [2][3][4]. Group 1: Intelligent Empowerment in Legal Supervision - The core of intelligent empowerment lies in the deep integration of algorithm capabilities with business scenarios, transitioning from data screening to intelligent generation [2]. - The use of prompt engineering is highlighted as a method to improve interaction between prosecutors and AI systems, enabling more precise and effective communication [2]. - Current supervisory models focus on data mining, while intelligent models can produce creative outputs, enhancing the analysis of vast electronic data in prosecutorial investigations [3]. Group 2: Data and Computing Power - A new foundational platform for the AI era is proposed, combining vast data, powerful computing capabilities, and a specialized knowledge base [4]. - Data aggregation is essential, with examples of successful data governance platforms that have created substantial data resource pools for legal supervision [4]. - The establishment of a shared computing power platform is necessary to address challenges in processing large volumes of information and running complex algorithms [4]. Group 3: Knowledge Base Development - A professional and precise knowledge base is crucial for connecting computing power with prosecutorial tasks, aiding AI in targeting and streamlining processes [5]. - The development of a multi-dimensional, high-quality knowledge system is suggested, incorporating legal regulations and case studies to enhance the efficiency of prosecutorial work [5]. Group 4: New Work Models - The establishment of intelligent prosecutorial teams that integrate technology with legal expertise is essential for effective case handling [6]. - Enhancing the application of AI through training and practical exercises is necessary to improve the skills of prosecutors in utilizing intelligent systems [6]. - A shift towards a human-machine collaborative model is advocated, ensuring that AI applications are closely aligned with prosecutorial practices [6].