Nature Communications (Oct 2022)

Technology readiness levels for machine learning systems

  • Alexander Lavin,
  • Ciarán M. Gilligan-Lee,
  • Alessya Visnjic,
  • Siddha Ganju,
  • Dava Newman,
  • Sujoy Ganguly,
  • Danny Lange,
  • Atílím Güneş Baydin,
  • Amit Sharma,
  • Adam Gibson,
  • Stephan Zheng,
  • Eric P. Xing,
  • Chris Mattmann,
  • James Parr,
  • Yarin Gal

DOI
https://doi.org/10.1038/s41467-022-33128-9
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 19

Abstract

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The development of machine learning systems has to ensure their robustness and reliability. The authors introduce a framework that defines a principled process of machine learning system formation, from research to production, for various domains and data scenarios.