Well with "AI" all we're talking about is theory-free frequentist modelling.
We can already do that for the weather: just take the mode of the last 10 years of the weather on this day, and some sort of weighted mean for temp/humidity/etc.
All "AI" is doing here is overfitting this process. On the overfit range, yes, you'll get better peformance. But the baseline performance here, from taking averages, is already pretty good.
What we need for the "future" of weather is long-tail events which cannot be modelled by curve-fitting to historical data.
We can already do that for the weather: just take the mode of the last 10 years of the weather on this day, and some sort of weighted mean for temp/humidity/etc.
All "AI" is doing here is overfitting this process. On the overfit range, yes, you'll get better peformance. But the baseline performance here, from taking averages, is already pretty good.
What we need for the "future" of weather is long-tail events which cannot be modelled by curve-fitting to historical data.