38 Comments
Oct 9Liked by Gary Marcus

As a physicist I'm quite disappointed to see that the physics Nobel was awarded for developments in computer science and not physics. The press release fails in its attempt to justify the award by suggesting that the algorithms (Hopfield network and Boltzmann machine) were inspired by physics.

Being inspired by physics does not make it a physics discovery.

I've lost all respect for the Nobel committees. They are too interested in trying to make political and cultural statements to maintain some sort of relevancy. In the process they are actually dimishing their relevancy as their rationalizations for their awards become more and more ridiculous.

If they want to give computer science awards they should start a new category rather than betray their stewardship of the existing awards.

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The Nobel committee can’t really start a new category because Nobel himself specified the categories.

The so called “Nobel” prize in economics was not specified by Alfred Nobel and is therefore not a real Nobel Prize and some descendants of Alfred Nobel have been quite unhappy (“disgusted” or even “revolted” would better represent their feelings) that that is often portrayed as a “Nobel Prize”.

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Agreed, see my comment above re new category

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Oct 9Liked by Gary Marcus

Nonattribution; nonreplicability; and, emphasis on what is marketed, especially by larger, entrenched groups will continue to pollute recognition for the original creators, innovators, inventors and risk takers.

The first mouse gets the guillotine: the second mouse gets the cheese.

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Oct 9Liked by Gary Marcus

Demis hassabis is really a quiet and responsible leader in our AI world he really can turn his approach based on situation. Not like Sam altman who are just hungry for power and money without any contribution to field.

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Thanks Gary, in full agreement. That also tells us another couple of things:

- The Nobel committee has contrived the definition of traditional disciplines to accommodate new fields. Algorithms, while significant, do not fall neatly into Physics or Chemistry categories.

I would prefer instead to see new categories emerge, such as "Applied Mathematics," despite the existence of the Fields medal. 😎 and yes, it was my reaction too "What does have to do with Physics??".

- AI has now achieved Nobel recognition in both disciplines, mirroring the accomplishment of only Marie Curie. 😉 😋 (yes, this is tongue-in-cheek, we still have humans in the driver seat).

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Oct 9Liked by Gary Marcus

"the first Nobel Prize for Neurosymbolic AI" — I hope it won't be the last. We need more great minds working on solving actual problems society faces instead of spewing out plastic art and poetry

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Gary: To an outsider reading your post, it seems like Hassabis is the main researcher here, with Jumper as a sidekick. But it's actually the other way around. Jumper and Baker are the trained chemists in this group, while Hassabis is not. John Jumper, in particular, has inspired countless grad students at UChicago and beyond, including Hassabis himself. Jumper developed an early version of AlphaFold for protein folding during his PhD, using a hybrid physics-ML model trained with contrastive divergence. (So, by the increasingly relaxed criteria of the Nobel committee, Jumper could've easily snagged a Nobel Prize in Physics. Maybe next year? 😊)

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author

is there a good writeup about Jumper? would love a link

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There are a couple of general links about John Jumper:

https://www.gairdner.org/winner/john-jumper

https://news.uchicago.edu/story/uchicago-alum-john-jumper-shares-nobel-prize-model-predicting-protein-structures

For insights into Jumper's college days, outside of speaking to him directly, the best source would be his Ph.D. advisor, Karl Freed.

In addition, Charles H. Martin, Ph.D., shared this on LinkedIn:

John Jumper's work in protein folding is what inspired me to start the WeightWatcher project back in 2015. I was discussing his work with our mutual Ph.D. advisor, Karl Freed, and it got me thinking... this could be applied to AI. Here’s a blog post from way back when that started it all:

https://calculatedcontent.com/2015/03/25/why-does-deep-learning-work/

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Oct 10·edited Oct 10

In June, Quanta published a piece about the impact of AI on protein science. While not about Jumper specifically (also touches on Baker's work), his experience does get the most coverage: https://www.quantamagazine.org/how-ai-revolutionized-protein-science-but-didnt-end-it-20240626/

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Yeah great so Hinton did quite a bit for CS but what major contribution did he make TO PHYSICS, specifically? Let's turn every one of these awards into some kind of influencer award instead of recognizing advancements _to_ a particular field.

OK OK hear me out

The Turing Prize should start to be awarded to whoever manages to get Something Really Big Done FROM a computational device!

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Oct 9·edited Oct 9Liked by Gary Marcus

My impression is that the physicists of the Nobel comitee didn't want physics to be left out of the revolutionary discovery of artificial neural networks. They used the pretext that Hopfield network and Hinton's Boltzmann machine / network that are based on concepts from statistical physics. However, they couldn't award a Nobel Prize on neural networks to the physicist Hopfield alone then Hinton.

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Hinton should have gotten a Nobel in Literature :)

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I think ChatGPT should have got the physics prize for “valiant effort” on the farmer boat/goat/cabbage/wolf river crossing problem.

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Yes! AlphaFold does appear (at least to this non-expert) to actually advance Chemistry. But I have seen nothing that I would call evidence that Hinton's work on the Boltzmann machine has contributed anything to understanding of the physical models that inspired it.

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Interesting distinction you make between the deserving-ness of the Hinton vs DeepMind prizes - I wonder if that's because you know a little less about the antecedents to alphafold industry ...and the work they critically relied on? (Full disclosure - I am biased). This is not to take away from their amazing work in terms of engineering at that scale, accuracy compared to crystal structures. But .. the ability to predict shapes of proteins that are not sequence similar to solved crystals depended critically on insights from work done earlier that they reference poorly. Maybe all discoveries re like this .. though I think Victor Ambros and Gary Ruvkun ( Monday's Nobel) that is much less the case ..

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Very strange award. There are so many talented physicists out there that deserve credit. Still not as bad as the fake Nobel in economics and this year is pretty egregious. I think I've only thought about 5% of them were ever really deserved. The Nobel has often been fairly political but this year it seems like Oscars and it seems clear that this physics Nobel is in large part trying to award whatever is being hyped in science right now.

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I'm resonating with @Steven Ray Scott's comment (below) that the Physics Nobel was awarded to computer science/neural modeling work and discoveries -- completely non-adjacent fields, requiring different skills, research-focus, and methods.

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In his Turing lecture, Hinton dismissed DeepMind (specifically its use of reinforcement learning) as reductio ad absurdum. And he left Google a few months after Hassabis got management responsibility for all of Google AI.

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Oct 10·edited Oct 10

It's occurred to me that a lot of work with LLMs has a symbolic "feel." A simple prompt is just that, a simple prompt. But once you starting creating scripts of prompts, you're basically using symbolic means to direct the behavior of the LLM. And the hidden prompts of OpenAI's o1 technology are even more elaborate. It's as though they want to use a production system to control inference in the LLM. It's as though they're trying to smuggle symbolic computing in by the back door.

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