Subject: Re: OT: AI Nobel Prizes
Here's a conjecture, FWIW:
Chemistry Nobel:
The case for a chemistry Nobel for Baker (a biochemist), Hassabis and Jumper (both AI at DeepMind) was pretty clear. A long standing and important problem in computational biology is predicting how proteins fold given their amino acid sequence, and this was solved using AI as a tool and physical intuition. Baker had long been active and eminent in structure prediction, and his group went beyond, to design new sequences for new proteins to accomplish new tasks. The impact of the totality of this work, heavily involving AI, will probably be (literally) life-changing.
Physics Nobel:
Hopfield is a physicist, and while Hinton has some background in physics he is more of a polymath (his career associations have been as a computer scientist).
Hopfield's original neural net work relates to Ising models and spin glasses, stuff physicists understand. This lured a whole generation of physicists into neural networks, including me (I then got into computational biology, so I'm not expert on the technical details of the new "AI"s). Geoff Hinton doesn't have a classical physics background, e.g. a PhD in physics, but he thinks in a very physical way. For example, one of his earlier and very interesting work was on something called the Boltzman Machine, which is a stochastic neural net with a temperature. He later invented "deep learning" and other ways to make neural nets able to solve real world problems.
Conceivably the Nobel committee, having decided that the Chemistry prize would be awarded for solving protein folding and also to design new proteins using AI as tools, then felt the need to honor key people who made AI available. Some may consider the physics Nobel for Hopfield and Hinton a stretch, but there's a case to be made for it. Also the old divisions of science into physics, chemistry, etc are getting broken, both with cross-disciplinary work, and from basically creating entirely new fields.
BWDIK - I'm an old retired dog on the internet.