Accelerating Scientific Discovery With AI-Aided Automation

Creators: Schneider, Tapio¹; Altintas, Ilkay; Atkins, Daniel

1. California Institute of Technology

Abstract

AI-aided design of experiments and observations, together with robotic instrumentation and automated learning from data, has the potential to transform science and propel it forward with unprecedented speed.

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Acknowledgement

We thank the members of the National Academies study on Automated Research Workflows for their contributions to the report on which this perspective is based, Frances Arnold for her insights on directed evolution and its automation, and Sarah Reisman for helpful discussions on automated chemical synthesis. The National Academy of Science study on Automated Research Workflows was generously supported by Eric and Wendy Schmidt by recommendation of Schmidt Futures.

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Resource type: Journal Article
Publisher: IEEE
Published in: Computing in Science & Engineering, 25(5), 27-30, ISSN: 1521-9615.
Languages: English

Created:: May 6, 2024
Modified:: May 6, 2024