It is in fact one of the least generalized forms of "AI" out there. A model focused solely on predicting weather.

"gen" stands for "generative". If you read the GenCast paper they call it a generative AI - IIRC it's an autoregressive GNN plus a diffusion model.

Which is surprising to me because I didn't think it would work for this; they're bad at estimating uncertainty for instance.

	▲	Majromax 2 days ago \| parent [-]
		> Which is surprising to me because I didn't think it would work for this; they're bad at estimating uncertainty for instance. FGN (the model that is 'WeatherNext 2'), FourCastNet 3 (NVIDIA's offering), and AIFS-CRPS (the model from ECMWF) have all moved to train on whole ensembles, using a cumulative ranked probability score (CRPS) loss function. Minimizing the CRPS minimizes the integrated square differences of the cumulative density function between the prediction and truth, so it's effectively teaching the model to have uncertainty proportional to its expected error. GenCast is a more classic diffusion-based model trained on a mean-squared-error-type loss function, much like any of the image diffusion models. Nonetheless it performed well.