Core Insights - The rise of artificial intelligence (AI) is transforming various industries, including finance, with expectations for increased intelligence, efficiency, and customer-friendliness [1] - However, challenges such as the need for precision, transparency, and data quality in financial applications of AI are emerging [2][4] Application of AI in Finance - Financial institutions primarily use generative large models for basic functions like intelligent customer service, but broader applications face obstacles due to the models' lack of precision and logical reasoning required in finance [2] - AI can significantly impact technology finance by improving credit approval efficiency, risk management, and financial product innovation [3] Cost and Efficiency Challenges - The high cost of large models, particularly those based on the Transformer architecture, limits their application in finance [4] - Research is ongoing to explore alternative neural network structures that could reduce computational costs while maintaining effectiveness, suggesting that smaller models may be more suitable for specific financial tasks [4] Future Directions for AI in China - The future of AI applications should focus on diversification, balancing industrial and economic benefits with social science integration [5][6] - AI has the potential to enhance efficiency in high-investment, low-output industries, such as drug development, and improve accuracy in sectors like weather forecasting, which can have significant economic and social impacts [5][6]