Group 1 - The integration of AI in the financial industry is evolving through three levels: data governance and knowledge, vertical model development and risk control, and security systems with full-stack AI collaboration [2][3] - In the first level, data governance is crucial, with the People's Bank of China promoting layered and classified data management, distinguishing between public market data and customer privacy data [2] - The second level focuses on the development of vertical models in areas like credit and wealth management, emphasizing the need for careful model training to mitigate risks associated with new data and algorithms [3] Group 2 - The third level highlights the importance of security mechanisms for large models, with financial institutions implementing technologies like safety barriers to ensure secure user interactions and data supply [3] - There is a need for financial institutions to optimize computing power while maintaining model accuracy, as quantization can save resources but may lead to precision loss [3] - Future developments in the financial sector will require clear definitions of AI and human responsibility boundaries, along with the establishment of relevant standards to address AI-related risks [3]