Computer scientist Geoffrey Hinton and physicist John Hopfield have won a Nobel Prize for their pioneering work on the neural network architecture that underlies machine learning. Specifically, the…
Using tools from physics to create something that is popular but unrelated to physics is enough for the nobel prize in physics?
So, if say a physicist creates a new recipe for the world’s greatest potato casserole, and it becomes popular everywhere, and they used some physics for creating the recipe to calculate the best heat distribution or whatever, then that’s enough?
Using tools from physics to create something that is popular but unrelated to physics is enough for the nobel prize in physics?
If only, it’s not even that! Neither Boltzmann machines nor Hopfield networks led to anything used in the modern spam and deepfake generating AI, nor in image recognition AI, or the like. This is the kind of stuff that struggles to get above 60% accuracy on MNIST (hand written digits).
Hinton went on to do some different stuff based on backpropagation and gradient descent, on newer computers than those who came up with it long before him, and so he got Turing Award for that, and it’s a wee bit controversial because of the whole “people doing it before, but on worse computers, and so they didn’t get any award” thing, but at least it is for work that is on the path leading to modern AI and not for work that is part of the vast list of things that just didn’t work and it’s extremely hard to explain why you would even think they would work in the first place.
Using tools from physics to create something that is popular but unrelated to physics is enough for the nobel prize in physics?
So, if say a physicist creates a new recipe for the world’s greatest potato casserole, and it becomes popular everywhere, and they used some physics for creating the recipe to calculate the best heat distribution or whatever, then that’s enough?
If only, it’s not even that! Neither Boltzmann machines nor Hopfield networks led to anything used in the modern spam and deepfake generating AI, nor in image recognition AI, or the like. This is the kind of stuff that struggles to get above 60% accuracy on MNIST (hand written digits).
Hinton went on to do some different stuff based on backpropagation and gradient descent, on newer computers than those who came up with it long before him, and so he got Turing Award for that, and it’s a wee bit controversial because of the whole “people doing it before, but on worse computers, and so they didn’t get any award” thing, but at least it is for work that is on the path leading to modern AI and not for work that is part of the vast list of things that just didn’t work and it’s extremely hard to explain why you would even think they would work in the first place.