arXiv cs.AIPaper
From extreme weather to agricultural consequences with agentic AI
This is agentic AI solving a real economic problem where the cost of guessing wrong is high. The validation is concrete: AUC 0.98 on cyclone detection, 2% loss prediction error, rank correlation on holdout data. For builders: this shows how agents that reason over causal models beat black-box approaches. For investors: climate-linked agricultural losses are a $100B+ category that hasn't been solved yet.