You have probably heard by now, but about twelve hours ago the Nobel Prize in Physics was awarded to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks”. To say that this prize is surprising is an epic understatement. It's also causing some consternation and even anger in some quarters. I don't normally feel qualified to comment on the Nobels, but in this case let me record just a few thoughts that are enhanced by conversations with and social media postings by a few friends.
Hopfield was faculty at Caltech when I was there, but was oriented more toward biology at the time, and I wasn't aware enough to take the really important and interesting classes. He taught a class on neural networks early during my time, which a few of my friends took but I didn't. In 1981-83, he, Carver Mead, and Richard Feynman taught a triple-listed Bi/CS/Ph course that was reportedly wild. I'm sorry I missed that! (I did take Feynman's class later, in 1985-86, that was a direct descendant of that class. We learned a little about neural networks, and in fact a couple of friends and I implemented one in C, though it wasn't very good. That class changed how I view the process of computation, and indirectly led me into quantum computing several decades later.)
One of my closest friends took a class Hinton co-taught back in the early 80s at CMU. She said it was fascinating, all the way back then.
On the prize itself, at least one of my physicist friends is angry. Paraphrasing, it's not physics and why should we be celebrating things that detract from human accomplishment? I don't agree with the latter, but the former will be the basis of bar arguments for a long time to come.
My opinion? Hmm...
It's not even entirely clear to me, after watching the press conference, whether the prize is being awarded for neural networks being physics, or changing the way people do physics. The former figured prominently in the press conference, as they talked about Boltzmann machines. Yes, Hopfield and Hinton both used ideas from their background in physics, but to me this seems to be a bit of a stretch. The committee also talked about the latter, about the use of neural nets in doing physics. In that case, why not the inventor of the supercomputer, or the laptop? The inventors of the Intel 4004 microprocessor (Faggin, Hoff, Mazor and Shima), most often cited as the world's first microprocessor, are all still alive. The invention of extreme ultraviolet photolithography is also another good candidate.
I've heard funny takes on this prize, including that the tech bro billionaires bribed the committee. My own is that it was ranked voting in the committee and everybody refused to budge on their first choice but somehow they all ranked AI high enough that in the end Hopfield and Hinton had the most points and everyone on the committee went, "wait, what???" But they couldn't undo the decision.
That, or they were all angry that Hopfield was left off of Hinton's 2018 Turing Award, shared with Bengio and LeCun. (Speaking of which, I said that Hinton was the first to receive both the Turing Award and a Nobel, but that's not true -- Herb Simon did it first! Interestingly, both Simon and Hinton were on the faculty at CMU.)
I do think it's okay that the committee is stretching the definition of "physics"; they have done that before, with prizes for information technology. But with only a single prize awarded each year in physics, there are many, many discoveries, and discoverers, out there waiting for the public recognition they most definitely deserve. There are other prizes for computing, of course, notably the Turing Award. So while a broad look at how physics has changed society is a good thing, but I think it would be okay to say, "Nah, they already have a prize in their main area, that should be enough."
But in the end, it's recognition of the importance of machine learning, neural networks and ultimately artificial intelligence in our lives already, a fact that will continue to grow. And if it gives Hinton (and others) more of a platform for and recognition of his (and their) reservations about where we are headed with AI, all of that's a good thing. It's a necessary conversation we need to be having, now.
Finally, the score so far for the science prizes this year:
- White men from elite institutions: 4
- Everyone else: 0
