工信部原副部长王江平：AI科学发现存在“堰塞湖”困境

Core Viewpoint - The former Vice Minister of the Ministry of Industry and Information Technology, Wang Jiangping, highlighted a "dam" dilemma in AI scientific discovery, where the exponential growth of AI predictions contrasts sharply with the linear growth of human verification and industrialization capabilities [1] Group 1: AI Prediction and Verification - AI predictions are experiencing exponential growth, while human verification capabilities are growing linearly, leading to a significant gap between the two [1] - The time required for humans to verify AI predictions can take 10 years or longer, creating a bottleneck in the application of scientific discoveries [1] Group 2: Resource Allocation - The mismatch between AI's rapid prediction capabilities and the slow verification process is likened to a "dam," obstructing the pathway for scientific discoveries to be transformed into practical applications [1] - This situation results in a backlog of numerous prediction outcomes that cannot be timely validated or industrialized, consuming substantial research and computational resources [1]