Core Insights - The most critical aspect of artificial intelligence development is data quality, as emphasized by the Director of the Information Hub at Hong Kong University of Science and Technology (Guangzhou) [2][10] - The establishment of a collaborative laboratory in the Guangdong-Hong Kong-Macao Greater Bay Area aims to integrate research capabilities from various universities to enhance the safe development of generative AI [2][4][10] Data Quality - Data quality is essential for effective AI applications, and the laboratory aims to create a big data platform for testing large models and improving their performance [4][10] - The laboratory will explore new methods to ensure data quality, including collaboration with industry to accumulate high-quality data for practical applications [4][9] Data Security - Data security poses significant challenges, requiring a balance between data integration and safety, with suggestions for using techniques like homomorphic encryption and privacy computing [5][9] - The laboratory is expected to establish a data security governance framework that includes both technical solutions and policy guidance to ensure proper data usage [5][8] AI Model Development - The successful application of large models in industries depends on their practical use, with examples provided from the insurance sector where large models can streamline claims processing [6][10] - The laboratory is tasked with addressing the security of AI models, particularly concerning the protection of sensitive information and the prevention of data poisoning attacks [9][10] Collaborative Efforts - The laboratory aims to form alliances through agreements that promote data security and encourage participants to prioritize data safety and privacy [8] - By fostering collaboration among universities and industries, the laboratory seeks to create a virtuous cycle of data sharing and usage, positioning the Greater Bay Area as a model for data security practices [8][9]