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- Naoya Ishizuki
- Tokyo Institute of Technology
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- Ryota Shimizu
- Tokyo Institute of Technology
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- Taro Hitosugi
- Tokyo Institute of Technology
説明
The emergence of autonomous experimental systems integrating machine learning and robots is ushering in a paradigm shift in materials science. Using computer algorithms and robots to decide and perform all experimental steps, these systems require no human intervention. A current direction focuses on discovering unexpected materials and theories with unconventional research approaches. This article reviews the latest achievements and discusses the impact of autonomous experimental systems, which will fundamentally change the way we understand research. Moreover, as autonomous experimental systems continue to develop, the need to think about the role of human researchers becomes more pressing. While machine learning and robotics can free us from the repetitive aspects of research, we need to understand the strengths and limitations of machine learning and robots and focus on how humans can perform higher creativity. In addition, we also discuss inventorship and authorship in the era of autonomous systems.
収録刊行物
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- Science and Technology of Advanced Materials: Methods
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Science and Technology of Advanced Materials: Methods 3 (1), 2023-07-03
Informa UK Limited
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キーワード
詳細情報 詳細情報について
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- CRID
- 1360021395472613120
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- ISSN
- 27660400
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- データソース種別
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- Crossref
- OpenAIRE