分析
文章讨论了大型语言模型（LLM）在科学研究中的局限性，强调了对能够理解和处理超越语言限制的各种科学数据的科学基础模型的需求。文章重点介绍了之江实验室及其021科学基础模型的工作，强调了其在科学发现和问题解决中克服LLM局限性的能力。文章还提到了“AI曼哈顿计划”以及人工智能在科学进步中的重要性。
要点
引用 / 来源
查看原文"The article quotes Xue Guirong, the technical director of the scientific model overall team at Zhejiang Lab, who points out that LLMs are limited by the 'boundaries of language' and cannot truly understand high-dimensional, multi-type scientific data, nor can they independently complete verifiable scientific discoveries. The article also highlights the 'AI Manhattan Project' as a major initiative in the application of AI in science."