I’m confused why confirming important predictions is considered less impactful than ML in physics. Isn’t experimental confirmation exactly what’s required for a Nobel Prize?
I’m confused why confirming important predictions is considered less impactful than ML in physics. Isn’t experimental confirmation exactly what’s required for a Nobel Prize?
Experimental confirmation of X makes X great physics and X worthy of a nobel prize, not the engineering setup needed for the experimental confirmation.
The setup by itself can also general technique that is useful beyond confirming one thing (example LIGO). But then, ML is itself is a more general technique that has enabled a lot more new physics than one new experiment.
I would couple the Experiment and the theory together, and treat them both deserving of the prize, but not sure how it works in practice. As for the general technique of ML, sure, it's important but it seems to me that it's a tool that can be used in Physics, and the specific implementation/use-case is the actual thing that's noteworthy, not the general tool. I wouldn't consider a new mathematical theorem by itself to be physics and deserving of a physics prize, I view general ML the same way.
Ideally this would be coupled like you say, but often in physics these are increasingly further apart, often by several decades.
And a large number of predictions being made now are unlikely to be ever confirmed.