"In the paper, the research team shows that combined with active learning techniques, the DeepOnet model can get trained on what parameters or precursors to look for that lead up to the disastrous event someone is analyzing, even when there are not many data points. “The thrust is not to take every possible data and put it into the system, but to proactively look for events that will signify the rare events,” Karniadakis said. “We may not have many examples of the real event, but we may have those precursors. Through mathematics, we identify them, which together with real events will help us to train this data-hungry operator.”"

Yeah...

Congrats, the computer gets fed data on things and can recognize them. This isn't anything unusual.

If x->y, and y is rare, but always comes from x, then seeing x can help you prepare if it causes y

I'm ready for it to get banned when it starts pointing out the black crime rate, and that dem policies are actively harmful, and that trannies rape kids