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Abstract <p>This review summarizes the key developments of the past two decades, highlighting the transformation of scientific research driven by artificial intelligence (AI). It explores both well-established and emerging applications of AI—ranging from biomedicine, pharmaceuticals, nutrition science, education, data science, engineering, and fundamental disciplines to synchrotron radiation facilities and advanced megascience infrastructures. The paper provides a detailed overview of AI approaches and architectures implemented in major international projects, including the Large Hadron Collider and its High-Luminosity upgrade, the FAIR facility, the DUNE and Belle II experiments, the LIGO, Virgo, and KAGRA gravitational-wave observatories, the LSST survey telescope, the SKA radio interferometer, the Euclid space observatory, the ESS, SNS, and J-PARC neutron sources, the ITER and JT-60SA fusion reactors, the NIF laser facility, the ELI-NP laser complex, exascale climate simulation platforms, and cryo-electron microscopy pipelines powered by AlphaFold technology. The article is intended for a broad audience of specialists interested in the methodological, technical, and organizational aspects of AI integration into scientific research.</p>

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Artificial Intelligence As a Driver of Modern Science: From Biomedicine to International Megascience Projects

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • D. D. Musin,
  • E. V. Varlamova,
  • M. A. Marchenkova,
  • A. V. Soldatov

摘要

Abstract

This review summarizes the key developments of the past two decades, highlighting the transformation of scientific research driven by artificial intelligence (AI). It explores both well-established and emerging applications of AI—ranging from biomedicine, pharmaceuticals, nutrition science, education, data science, engineering, and fundamental disciplines to synchrotron radiation facilities and advanced megascience infrastructures. The paper provides a detailed overview of AI approaches and architectures implemented in major international projects, including the Large Hadron Collider and its High-Luminosity upgrade, the FAIR facility, the DUNE and Belle II experiments, the LIGO, Virgo, and KAGRA gravitational-wave observatories, the LSST survey telescope, the SKA radio interferometer, the Euclid space observatory, the ESS, SNS, and J-PARC neutron sources, the ITER and JT-60SA fusion reactors, the NIF laser facility, the ELI-NP laser complex, exascale climate simulation platforms, and cryo-electron microscopy pipelines powered by AlphaFold technology. The article is intended for a broad audience of specialists interested in the methodological, technical, and organizational aspects of AI integration into scientific research.