The holy grail of clean energy is Fusion—the process that powers the sun. Reaching ignition requires solving two of the world's most complex engineering and materials challenges: controlling superheated plasma hotter than the sun's core, and building materials strong enough to contain it. Artificial Intelligence is the only tool accelerating the timeline for both, pushing the world toward limitless, carbon-free power.This episode explores AI's two-front war on the fusion challenge:

• Plasma Control (The Real-Time Brain): We examine how machine learning (ML) is essential for real-time control of plasma in tokamaks (magnetic confinement devices). AI models instantly predict and counteract plasma instabilities—which can destroy a reactor in milliseconds—by adjusting magnetic fields far faster and more precisely than any human or traditional control system, keeping the reaction stable and achieving higher performance (Source 1.1, 2.3).
• Inventing Reactor Materials: Fusion relies on exotic, high-performance materials that must withstand extreme heat, radiation, and stress for decades. We look at how Materials Informatics (AI-driven discovery) is trained on existing material data to predict and synthesize novel alloys and ceramics needed for reactor walls and high-temperature superconducting magnets, a process that would take human scientists decades of trial-and-error (Source 1.2, 4.3).

By automating the most complex control loops and accelerating the discovery of essential components, AI is moving fusion from a distant scientific dream to a tangible engineering reality, positioning it to become the backbone of the next century's clean energy grid.

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