AI Is Helping Scientists Stabilize the Sun—in a Bottle

Hello readers,

Welcome to the AI For All newsletter! Today, we’re talking about how AI is giving us a new view of nuclear fusion, how to know if your data architecture is ready for AI, and more!

AI in Action: Seeing Nuclear Fusion

Researchers from Princeton have developed an AI system called Diag2Diag that can reconstruct missing or degraded sensor data in fusion reactors, essentially filling in the blanks using information from other diagnostics, as detailed in a study published in Nature Communications. Like an AI tool that lip-reads and reconstructs a film’s missing audio track, Diag2Diag synthesizes high-resolution plasma data where direct measurements are unavailable. This allows scientists to track critical aspects of the plasma with greater fidelity, improving control and reducing the need for costly or hard-to-maintain physical sensors.

The AI model was trained on fusion experiments at the DIII-D National Fusion Facility and demonstrated impressive capability in reproducing fine-grained data, particularly in areas where traditional diagnostics like Thomson scattering fall short. For example, it generated accurate estimates of temperature and density in the hard-to-measure “pedestal” region at the plasma’s edge. These details are vital to maintaining plasma stability, which is crucial for any future fusion power plant.

Beyond diagnostics, Diag2Diag has real-world implications for plasma disruption prevention and system design. The AI produced new evidence supporting a theory about how magnetic field tweaks suppress harmful energy bursts (ELMs), reinforcing its value not just as a monitoring tool, but as a path to better understanding plasma behavior. Researchers believe this approach could make future reactors more compact, robust, and affordable by enabling fewer physical sensors while increasing visibility into the machine’s most important dynamics.

🔥 Rapid Fire

• Debt is fueling the next wave of the AI data center boom

• Echoes of dot-com bubble: heavy debt, tiny revenue, billions spent

• Analysis: Yes, we’re in a bubble and OpenAI needs a trillion dollars

• AI hallucinations are getting worse and they're here to stay

• AI is dreaming up millions of new materials but are they actually useful?

• Meta will soon use your AI chatbot conversations for targeted ads

• On AI bubble, Mark Zuckerberg says ‘collapse’ is ‘definitely a possibility’

• Replit's latest update is infuriating customers with surprise cost overruns

• Can today’s AI video models actually understand how the real world works?

• A man goes missing after becoming obsessed with an AI chatbot

• Top AI researchers leave Big Tech for a new startup

• Commentary: How the AI bubble ate Y Combinator

• More and more AI startups use ever-more-creative definitions of ARR

• OpenAI's new social app is flooded with Sam Altman deepfakes

• Mira Murati’s stealth AI lab launches its first product

• Anthropic claims new model thinks it's being tested by humans

• Hollywood celebrities come out against AI-generated actor

• If AI is a bubble, the whole economy could pop with it

📖 What We’re Reading

Is Your Data Architecture Ready for AI?