Princeton’s AI Reveals What Fusion Sensors Can’t See

Princeton’s AI reveals what fusion sensors can’t see

A powerful new AI tool called Diag2Diag is revolutionizing fusion research by filling in missing plasma data with synthetic yet highly detailed information. Developed by Princeton scientists and international collaborators, this system uses sensor input to predict readings other diagnostics can’t capture, especially in the crucial plasma edge region where stability determines performance. By reducing reliance on bulky hardware, it promises to ma…

New AI Enhances the View Inside Fusion Energy Systems

A new AI can fill in missing sensor data for fusion systems, offering even more detail than the real-world sensor could have provided. The AI, known as Diag2Diag, could prove essential for commercial fusion energy production by helping to reduce costs and ensure reliability.

New AI Technology Revolutionizes Visualization Inside Fusion Energy Systems

Imagine a futuristic scenario where artificial intelligence (AI) can reconstruct missing or incomplete data with remarkable precision, akin to automatically restoring the missing audio track from a silent movie by analyzing its images. This is precisely the promise behind Diag2Diag, a cutting-edge AI developed by a collaborative team led by Azarakhsh Jalalvand at Princeton University. Published recently in Nature Communications, Diag2Diag repres…