Tag: Challenges

Why AI Can’t Yet Grow a Perfect Crop Model

Imagine trying to beat Elden Ring with only half the map, no health potions, and a sword that breaks every few swings. That’s roughly the challenge agricultural scientists face when applying artificial intelligence (AI) to crop modeling.

Crop models—like the venerable Decision Support System for Agrotechnology Transfer (DSSAT)—simulate plant growth, soil chemistry, and environmental interactions. They’re essential tools for predicting yields, managing fertilizers, and preparing for climate change. But these models are only as good as their inputs, and in agriculture, data is often scarce, noisy, or incomplete.


June 11, 2025 0

Why AI Struggles to Crack the Code of Nondestructive Testing

There’s a common trope in science fiction: an all-seeing machine, unblinking and exact, scanning the world for flaws we can’t detect. In the real world of nondestructive testing (NDT)—the science of using sensors to find cracks, corrosion, and hidden damage in everything from aircraft wings to oil pipelines—that dream still feels frustratingly out of reach.

We have artificial intelligence that can beat world champions at Go, generate Hollywood-quality dialogue, and diagnose rare diseases from pixelated scans. And yet, when we point these same tools at ultrasonic signals or thermographic images from NDT inspections, the results are… inconsistent at best.


June 4, 2025 0