Real AI advances require collaboration

IF 51.7 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
N. M. Anoop Krishnan, Kevin Maik Jablonka
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引用次数: 0

Abstract

Standardized tasks and data sets have enabled machine learning experts to contribute to chemistry. However, current practices tend to reward incremental improvements in benchmark performance that do not necessarily translate into meaningful advances. We propose a framework for collaboration between artificial intelligence and domain experts to genuinely accelerate discovery.
真正的人工智能进步需要合作
标准化的任务和数据集使机器学习专家能够为化学做出贡献。然而,当前的实践倾向于奖励基准性能的增量改进,而不一定转化为有意义的进步。我们提出了一个人工智能和领域专家之间协作的框架,以真正加速发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature reviews. Chemistry
Nature reviews. Chemistry Chemical Engineering-General Chemical Engineering
CiteScore
52.80
自引率
0.80%
发文量
88
期刊介绍: Nature Reviews Chemistry is an online-only journal that publishes Reviews, Perspectives, and Comments on various disciplines within chemistry. The Reviews aim to offer balanced and objective analyses of selected topics, providing clear descriptions of relevant scientific literature. The content is designed to be accessible to recent graduates in any chemistry-related discipline while also offering insights for principal investigators and industry-based research scientists. Additionally, Reviews should provide the authors' perspectives on future directions and opinions regarding the major challenges faced by researchers in the field.
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