关于化学基础模型的一个视角
Junyoung Choi1, Gunwook Nam1, Jaesik Choi2
1Department of Chemical and Biological Engineering, and Institute of Chemical Processes, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea.
JACS Au
|May 2, 2025
概括
基础模型,在广泛的数据上训练的大型人工智能模型,正在彻底改变化学研究. 这些模型为数据稀缺和提高化学应用中的概括性等挑战提供了解决方案.
科学领域:
- 人工智能的人工智能
- 化学 化学 化学
- 机器学习 机器学习
背景情况:
- 基础模型是大规模的,预训练的AI模型,可以适应各种任务.
- 像ChatGPT这样的例子证明了它们在各种工作流程中的变革潜力.
- 他们的成功激发了对复杂化学挑战的开发.
研究的目的:
- 审查化学基础模型的最新进展.
- 探索它们在不同化学领域的应用.
- 讨论新出现的趋势和未来的方向.
主要方法:
- 对化学基础模型的现有文献进行审查.
- 分析材料发现和结构与属性关系等领域的应用.
- 讨论基础模型如何解决传统机器学习的局限性.
主要成果:
- 基础模型越来越多地应用于化学问题.
- 它们在克服化学机器学习中的数据稀缺性和泛化问题方面显示出前途.
- 进步涵盖了化学中的各种应用范围.
结论:
- 基础模型代表了化学人工智能的显著范式转变.
- 它们提供了强大的工具来应对现场持续存在的挑战.
- 预计持续的研发将进一步推进它们的功能和应用.
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