> The first step is potentially changing the way data is assimilated into AI-based models. At present, they almost universally use a set of initial conditions produced by a physics model. That is, a model like the ECMWF spends an enormous amount of computing power to collect data from buoys, surface stations, weather balloons, airplanes, ships, satellites, and many other sources and then synthesizes a set of initial conditions for grid points across the planet. All models then take this as the beginning "state" of the planet's weather and forecast from that.
So this is essentially learning the time-stepping part of the physical model, not deriving predictions from raw data. While still interesting and probably still complex, this is far less impressive than the title lead me to believe.