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TED Talks Daily

How "digital twins" could help us predict the future | Karen Willcox

Sep 1, 2023
Aerospace engineer Karen Willcox discusses the potential of digital twins in engineering, climate studies, and medicine. She explains how personal data collection leads to the creation of personalized dynamic representations called digital twins. Willcox explores the wide range of applications for digital twins, from aerospace engineering to medicine, and highlights the challenges in creating digital twins of complex systems. She also emphasizes the importance of combining physics-based models with machine learning and data simulation to make better predictions and decisions.
15:29

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Quick takeaways

  • Digital twins combine personalized data and mathematical models to create dynamic simulations of physical systems in various domains.
  • Creating digital twins for complex systems is challenging due to multiple scales, sparse data, and the need for predictive models.

Deep dives

The Power of Digital Twins

Digital twins are highly specific, data-driven simulations of existing systems that have the potential to tackle societal problems. They combine personalized data and powerful mathematical models to create dynamic and evolving models of physical systems. Digital twins have numerous applications, including optimizing aircraft maintenance and flight operations in the airline industry, monitoring and maintaining bridges and other infrastructure, increasing energy efficiency in buildings, and guiding medical assessment and personalized treatment. However, creating digital twins for complex systems is challenging due to the scales involved and the need for predictive physics-based models.

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