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