Large-language models: The game-changers for materials science research

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引用次数: 0

Abstract

Large Language Models (LLMs), such as GPT-4, are precipitating a new "industrial revolution" by significantly enhancing productivity across various domains. These models encode an extensive corpus of scientific knowledge from vast textual datasets, functioning as near-universal generalists with the ability to engage in natural language communication and exhibit advanced reasoning capabilities. Notably, agents derived from LLMs can comprehend user intent and autonomously design, plan, and utilize tools to execute intricate tasks. These attributes are particularly advantageous for materials science research, an interdisciplinary field characterized by numerous complex and time-intensive activities. The integration of LLMs into materials science research holds the potential to fundamentally transform the research paradigm in this field.

大型语言模型:改变材料科学研究的游戏规则
大型语言模型(LLM),如 GPT-4,通过显著提高各领域的生产力,正在催生一场新的 "工业革命"。这些模型从庞大的文本数据集中编码了大量科学知识,可作为近乎万能的通才发挥作用,能够进行自然语言交流并展现高级推理能力。值得注意的是,由 LLM 衍生出的代理可以理解用户意图,并自主设计、规划和使用工具来执行复杂的任务。这些特性对于材料科学研究尤为有利,因为材料科学研究是一个跨学科领域,涉及众多复杂且耗时的活动。将 LLM 融入材料科学研究,有可能从根本上改变该领域的研究模式。
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来源期刊
Artificial intelligence chemistry
Artificial intelligence chemistry Chemistry (General)
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