Group 1 - The emergence of large language models (LLMs) has prompted various industries to explore their potential for business transformation, leading to the development of numerous AI-enhancing technologies [1] - AI systems require access to company data, which has led to the creation of Retrieval-Augmented Generation (RAG) architecture, essential for enhancing AI capabilities in specific use cases [2][5] - A well-structured knowledge base is crucial for effective AI responses, as poor quality or irrelevant documents can significantly hinder performance [5][6] Group 2 - Data governance roles are evolving to support AI system governance and the management of unstructured data, ensuring the protection and accuracy of company data [6] - Traditional data governance has focused on structured data, but the rise of Generative AI (GenAI) is expanding this focus to include unstructured data, which is vital for building scalable AI systems [6] - Collaboration between business leaders, AI technology teams, and data teams is essential for creating secure and effective AI systems that can transform business operations [6]
数据治理对人工智能的成功至关重要
3 6 Ke·2025-07-21 03:09