> but they have made no contribution to understanding physical laws or phenomena.
Neural networks are used in tons of data pipelines for physics experiments, most notably with particle accelerators.
The Nobel Prize is also occasionally awarded to engineers who develop tools that are important parts of experiments. 2018 for example was awarded for chirped pulse amplification, which is probably best known for being used in LASIK eye surgery, but it is also used in experimental pipelines.
> Neural networks are used in tons of data pipelines for physics experiments
With this argument you could even say Bill Gates should get an award for inventing Windows and popularized the desktop computer... Or at least Linus Torvalds since those pipelines are probably running Linux...
Please explain how Hopfield network influenced modern deep learning models based on supervised differentiable training. All the "impactful" architectures such as MLP, CNN, Attention, come from a completely different paradigm, a paradigm that could be more straightforwardly connected to optimization theory.
They did not bring it into existence. The MLP is older than the Hopfield network. The invention that made it practical was back propagation, which wasn't used here at all.
Neural networks are used in tons of data pipelines for physics experiments, most notably with particle accelerators.
The Nobel Prize is also occasionally awarded to engineers who develop tools that are important parts of experiments. 2018 for example was awarded for chirped pulse amplification, which is probably best known for being used in LASIK eye surgery, but it is also used in experimental pipelines.