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Understanding the Limits of Artificial Intelligence for Warfighters: Distributional Shift in Cybersecurity Datasets [Mīkstie vāki]

  • Formāts: Paperback / softback, 35 pages, height x width x depth: 279x215x3 mm, weight: 122 g, Illustrations
  • Izdošanas datums: 29-Mar-2024
  • Izdevniecība: RAND Corporation
  • ISBN-10: 1977412793
  • ISBN-13: 9781977412799
  • Mīkstie vāki
  • Cena: 26,85 €
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  • Formāts: Paperback / softback, 35 pages, height x width x depth: 279x215x3 mm, weight: 122 g, Illustrations
  • Izdošanas datums: 29-Mar-2024
  • Izdevniecība: RAND Corporation
  • ISBN-10: 1977412793
  • ISBN-13: 9781977412799

The Department of the Air Force has become increasingly interested in the potential for artificial intelligence (AI) to revolutionize different aspects of warfighting. But in the context of cybersecurity, distributional shift—the divergence of current data from the data on which an AI system was trained—can significantly reduce the longevity of AI applications. This could be especially dangerous as the threat of cyberattacks continues to grow.



Distributional shift can significantly degrade the performance of artificial intelligence systems and limit their application. In the context of cybersecurity, distributional shift could be especially dangerous as the threat of cyberattacks grows.