• Open Problem in Physics Explained - Data Driven Optimization

  • Dec 4 2024
  • Length: 7 mins
  • Podcast

Open Problem in Physics Explained - Data Driven Optimization

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  • Summary

  • In this episode of Simply Science, we explore how data-driven evolutionary optimization is reshaping the way we solve complex problems. Unlike traditional methods relying on straightforward objective functions, this cutting-edge approach uses data from simulations, experiments, and real-world observations to evaluate solutions.

    However, real-world data often comes with challenges like noise and heterogeneity, making optimization more complicated. Enter physics-informed models—AI-inspired frameworks that integrate physical knowledge to reduce computational costs and improve generalization. Coupled with knowledge-driven AI, which condenses and interprets data for greater efficiency, these advancements are driving a shift toward smarter, more interpretable optimization methods.

    We discuss the exciting potential of combining knowledge- and data-driven optimization strategies to tackle some of AI’s toughest challenges. If you’re curious about the future of AI in solving real-world problems with efficiency and precision, this episode is a must-listen!
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