Scientists at Princeton University have developed an AI model that can predict and prevent plasma instabilities, a major hurdle in achieving practical fusion energy.

Key points:

  • Problem: Plasma escaping containment in donut-shaped tokamak reactors disrupts fusion reactions and damages equipment.
  • Solution: AI model predicts instabilities 300 milliseconds before they happen, allowing for adjustments to keep plasma contained.
  • Significance: This is the first time AI has been used to proactively prevent tearing instabilities in fusion experiments.
  • Future: Researchers hope to refine the model for other reactors and optimize fusion reactions.
  • @Pipoca
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    10 months ago

    Although it’s been used for a fairly wide array of algorithms for decades. Everything from alpha-beta tree search to k-nearest-neighbors to decision forests to neural nets are considered AI.

    Edit: The paper is called

    Avoiding fusion plasma tearing instability with deep reinforcement learning

    Reinforcement learning and deep neural nets are buzzwordy these days, but neural nets have been an AI thing for decades and decades.