Well yeah, so are neural nets. I just meant that these are engineering accomplishments, not scientific per se. Of course experimental science will often take advantage of cutting edge technology, including from computer science.
NNs have absolutely revolutionized systems biology (itself a John Hopfield joint, and the AlphaFold team are reasonably likely to get a Nobel for medicine and physiology, possibly as soon as 'this year') and are becoming relevant in all kinds of weird parts of solid-state physics (trained functionals for DFT, eg https://www.nature.com/articles/s41598-020-64619-8).
The idea that academic disciplines are in any way isolated from each other is nonsense. Machine learning is computer science; it's also information theory; that means it's thermodynamics, which means it's physics. (Or, rather, it can be understood properly through all of these lenses).
John Hopfield himself has written about this; he views his work as physics because _it is performed from the viewpoint of a physicist_. Disciplines are subjective, not objective, phenomena.
parodysbird|1 year ago
adw|1 year ago
The idea that academic disciplines are in any way isolated from each other is nonsense. Machine learning is computer science; it's also information theory; that means it's thermodynamics, which means it's physics. (Or, rather, it can be understood properly through all of these lenses).
John Hopfield himself has written about this; he views his work as physics because _it is performed from the viewpoint of a physicist_. Disciplines are subjective, not objective, phenomena.