Pretty much the only thing I think AI could be useful for - forecasting the weather based off tracking massive amounts of data. I look forward to seeing how this particular field of study is improved.
Bonus points, AI weather modeling, for once, saves energy relative to physics models. Pair it with some sort of light weight physical model to keep the hallucinations at bay, and you’ve got a good combo.
I’m not convinced you can ever get that resolution. There’s a big difference between modeling the broad trends and trying to remove the uncertainty from a process that’s inherently probabilistic.
Theoretically with enough data it could predict exactly what is going to happen do we have enough data currently to do that probably not but weather isn’t just completely random we just don’t understand it enough yet
My argument is that that is not the case.
There are many systems in nature that have randomness fundamentally built in. You can model the broad strokes, but the low level details are inherently unpredictable because random processes are involved at the low level. You can predict the general pattern of airflow over a jet wing, but it’s not a lack of input resolution that makes it impossible to project the path of a specific molecule.
It’s an insanely complex, coupled system full of turbulence, so that “theoretically” is doing some heavy lifting. The best models now need to be run on supercomputers, despite scores of scientists and software people constantly trying to find further optimizations for the algorithms. AI isn’t going to better discriminate signal from noise when the biggest constraint on the existing S/N ratio is the lack of suffiicient compute resource.
Furthermore, unless the AI does explainability, which it almost certainly doesn’t, nobody’s going to use its output in life-and-limb-critical applications like first responders, defense, even road gritting.