This is embarrassing. I would say Hopfield networks aren't even very revolutionary in neuroscience, but they're so old I can't tell. In terms of AI... they've been irrelevant for thirty years. I guess you could argue a transformer is a generalized Hopfield network, but of course that's a post-hoc understanding. None of this has anything to do with physics. So what if an energy function lets you approximate the number…
This is the only plausible reason: “These artificial neural networks have been used to advance research across physics topics as diverse as particle physics, materials science, and astrophysics,” Ellen Moons, chair of the Nobel Committee for Physics, said at a press conference this morning.
It may have been state-of-the-art in 1980s, but now is a bit late.
Very smart people in their time though.
In current times, a global prize to the transformers folks at least make more sense considering the context (despite it not being Physics).