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Abstract <p>The key developments of the past two decades highlighting the transformation of scientific research driven by artificial intelligence (AI) are summarized. Both well-established and emerging applications of AI are explored: ranging from biomedicine, pharmaceuticals, nutrition science, education, data science, engineering, and fundamental disciplines to synchrotron radiation facilities and advanced megascience facilities. A detailed overview of AI approaches and architectures implemented in major international projects is provided, 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 systems powered by AlphaFold technology. The work 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：

    2025年12月1日

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

摘要

Abstract

The key developments of the past two decades highlighting the transformation of scientific research driven by artificial intelligence (AI) are summarized. Both well-established and emerging applications of AI are explored: ranging from biomedicine, pharmaceuticals, nutrition science, education, data science, engineering, and fundamental disciplines to synchrotron radiation facilities and advanced megascience facilities. A detailed overview of AI approaches and architectures implemented in major international projects is provided, 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 systems powered by AlphaFold technology. The work is intended for a broad audience of specialists interested in the methodological, technical, and organizational aspects of AI integration into scientific research.