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在人工智能技术更广泛采用的情况下,思考化学研究的未来
Daniil A Boiko1, Mikhail V Polynski2
1Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Chemistry (Weinheim an der Bergstrasse, Germany)
|February 18, 2026
概括
人工智能 (AI) 和化学中的机器学习 (ML),加上学术压力,可能会重塑知识生产. 这可能会改变研究小组结构以及学术界,工业界和政府实验室之间的平衡.
科学领域:
- 化学 化学 化学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 学术研究面临着资金限制,人才竞争和不断变化的职业态度.
- 人工智能和机器学习在化学中的整合正在加速.
- 这些趋势给科学界带来了结构性压力.
研究的目的:
- 分析AI和ML的采用以及学术压力如何重塑化学知识生产.
- 讨论这些变化对研究人员,机构和资助者的影响.
- 培养一个更有弹性的研究生态系统.
主要方法:
- 对化学的AI/ML近期进展的回顾:自动化实验,自动驾驶实验室,基于ML的建模,数字双胞胎和大型语言模型.
- 分析目前对大学的财务和社会压力.
- 讨论研究小组组成的潜在变化以及学术界-工业界-政府之间的平衡.
主要成果:
- 人工智能和机器学习已经准备好将化学研究转变为不仅仅是生产力增长.
- 化学知识创造的格局可能会发生变化.
- 潜在的变化包括改变研究小组动态和跨部门合作.
结论:
- 人工智能/ML和学术压力的融合需要在化学研究中进行调整.
- 需要采取积极的措施,在研究生态系统中建立性.
- 化学知识生产的未来可能需要重新定义大学,工业和政府实验室的角色.
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