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In this review, I will discuss the reasons for the 2024 Nobel Prize in Physics, the second neural network boom and its demise, which cannot be ignored, and the third neural network boom, backed by steady academic progress. In addition, I will discuss AI for Science, advocated by Demis Hassabis, winner of the Nobel Prize in Chemistry. The contributions of Japanese researchers whose work cannot be ignored will be described, and a new perspective will be presented on information creation, statistical mechanics, and data-driven science. AI for materials engineering, which is an extension of AI for science, is explained in terms of the 3 + 1 model of functional expression and the three levels of data-driven science proposed by our group.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: Neural network, Neuroscience, AI, AI for science, Data-driven science, AI for materials engineering

刊行年月日: 2025-12-31

出版者: Taylor & Francis

掲載誌:

• Science and Technology of Advanced Materials (ISSN: 27660400) vol. 5 2516307

研究助成金:

原稿種別: 著者最終稿 (Accepted manuscript)

MDR DOI: https://doi.org/10.48505/nims.5599

公開URL: https://doi.org/10.1080/27660400.2025.2516307

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更新時刻: 2025-07-17 08:30:16 +0900

MDRでの公開時刻: 2025-07-17 08:20:14 +0900