量子位·2025-09-15 05:57Core Viewpoint - The article discusses a new AI system developed by Google that assists scientists in creating expert-level empirical software, achieving state-of-the-art (SOTA) results across various scientific fields [10][12][30]. Group 1: AI System Development - The AI system utilizes a combination of Large Language Models (LLMs) and tree search algorithms to systematically improve software quality metrics [10][17]. - It addresses the slow and labor-intensive process of developing empirical software, which often takes years to complete [14][15]. - The system can automatically create empirical software for quantifiable tasks, significantly enhancing the efficiency of scientific research [17][24]. Group 2: Performance and Achievements - In bioinformatics, the system discovered 40 novel methods for single-cell data analysis, outperforming top human-developed methods on public leaderboards [25][30]. - In epidemiology, it generated 14 models that surpassed the CDC ensemble and all other individual models for forecasting COVID-19 hospitalizations [10][30]. - The system also produced state-of-the-art software for geospatial analysis, neural activity prediction in zebrafish, time series forecasting, and numerical solutions of integrals [10][30]. Group 3: Methodology and Innovation - The AI system enhances code mutation capabilities by injecting research ideas from highly cited papers, textbooks, and search engine results [21][24]. - It generates numerous candidate software solutions and employs tree search algorithms to filter and optimize these candidates [17][24]. - The integration of complex research ideas allows the system to explore a vast solution space, leading to the discovery of high-quality solutions [24][30]. Group 4: Community Response and Implications - The article notes that the introduction of AI in scientific research has sparked discussions about the appropriateness of delegating research authority to AI [32]. - There are concerns regarding the reliability of AI-generated results and the need for human oversight in the verification process [32][40].