Don't be too seduced by the enticing ideas at the end of the article. The disconnect here is that success in learning how to predict the results of an algorithmic simulation is not really indicative of how it would perform with the decidedly non-algorithmic natural behavior of weather or earthquakes, phenomena which don't operate in a closed system with predefined limits and parameters. It sounds like the next step, but even if weather were reducible to machine-discoverable patterns, you first must face the need to collect an immense amount of high-resolution condition data from around the globe on an ongoing basis. I'm guessing our current mesh of satellites and weather stations, as impressive as it is, comes nowhere close to enough raw data to sufficiently feed the beast in this case. And even that assumes that we _know about_ and can measure all of the factors that go into weather patterns. I sincerely doubt that's the case.