Very cool project. There are some presentations by the PI on youtube that I recommend searching for. One of the interesting takeaways I had was that they were able to do better with mesoscale phenomena and extreme weather prediction than the other players (like Graphcast and Pangu and FourCastNet), in part due to their technique for training a higher resolution data space (0.1 deg vs 0.25 or 0.5). I also found it interesting that they were able to show a scaling relationship where performance increased by 5% every time they doubled the model size - and their loss was still improving when they had to cut it off due to cost constraints.
Very cool stuff!