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Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

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Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#701
post #84

For what it's worth, the "Advanced information" PDF does a somewhat better job of trying to explain the rationale than the linked press release: https://www.nobelprize.org/uploads/2024/09/advanced-physicsp...

Thanks for finding/providing that link. p.10

"Highly sought-after fundamental particles, such as the Higgs boson, only exist for a fraction of a second after being created in high-energy collisions (e.g. ~10-22 s for the Higgs boson). Their presence needs to be inferred from tracking information and energy deposits in large electronic detectors. Often the anticipated detector signature is very rare and could be mimicked by more common background processes. To identify particle decays and increase the efficiency of analyses, ANNs were trained to pick out specific patterns in the large volumes of detector data being generated at a high rate." (emphasis mine)

It concerns me reading stuff like this (one can find similar for the original LIGO detection of gravitational waves) without accompanying qualification. B/c I want to hear them justify why it shouldn't sound like 'we created something that was trained to beg the question ad nauseam'. Obvs on a social trust basis I have every reason to believe these seminal discoveries are precisely as reported. But I'd just like to see what the stats look like - even if I'm probably incapable of really understanding them - that are able to guarantee the validity of an observation when the observation is by definition new, and therefore has never been detected before, and therefore cannot have produced an a priori test set (outside of simulation) baseline to compare against.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#703

My perspective as a PhD in theoretical physics, who's been doing deep learning in the last 4 years: 1. The prize itself makes zero sense as a prize in _physics_. Even the official announcement by the Nobel Prize Committee, taken at a face value, reads as a huge stretch in trying to link neural networks to physics. When one starts asking questions about the real impact on physics and whether the most important works o…

> because physics is currently stalled.

Even if it's not completely true, maybe some introspection is required?

I understand developing new theories is important and rewarding, but most physics for the last three decades seems to fall within two buckets. (1) Smash particles and analyze the data. (2) Mathematical models that are not falsifiable.

We can be pretty sure that the next 'new physics' discovery that gives us better chips, rocket propulsion, etc etc is going to get a nobel prize pretty quickly similar to mRNA.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#704

This is totally bizarre, no precedent for it really. The reality of the prize means that less and less are the winners names every physicist has heard of, but even today they're still big names in each subfield. For e.g. Kosterlitz, Thouless and Haldane weren't exactly household names but they really deserved the prize in 2016. In this case, there's a good argument that Hopfield had conducted strong work as a physici…

Bob Dylan got a Nobel prize in literature, which feels something like a precedence.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#705

Earlier quoted context omitted.

More to do with neuroscience than you think. Fukushima took direct inspiration from Hubel & Wiesel's nobel prize in the 1960s when developing the neocognitron, which turned into convolutional neural networks. Hopfield networks are a model for associative memory. And, well, then there is the perceptron. There was always a link and mutual inspiration. Recommended reading: Lindsay, G. W. (2021). Convolutional neural net…

As inspiration, yes. However, a neural network neuron and a biological neuron are, to modern understanding, entirely unrelated.

Discussing the right levels of abstraction is a huge thing in computational biology. At what level is 'the algorithm' of natural computation implemented?

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#706
post #693
post #501

I find the prize a bit odd this time since it focused on Hopfield networks and Boltzmann machines. Picking those two architectures in particular seems a bit arbitrary. Besides, Parisi got the prize last year (edit: actually 2021, time flies) for spin glasses. Hopfield networks are quite related. They could have included Hopfield & Hinton too, and it would have looked more coherent. It is also concerning that lately t…

> Hopfield networks and Boltzmann machines Think of this as a Nobel prize for systems physics – essentially "creative application of statistical mechanics" – and it makes a lot more sense why you'd pick these two. (I am a mineral physicist who now works in machine learning, and I absolutely think of the entire field as applied statistical mechanics; is that correct? Yes and no: it's a valid metaphor.)

You ain't wrong.

Lots of ML is heavily influenced by fundamental research done by Physicists (eg. Boltzmann Machines), Linguists (eg. Optimality Theory / Paul Smolensky, Phylogenetic Trees/Stuart Russell+Tandy Warnow), Computational Biologists (eg. Phylogenetic Trees/Stuart Russell+Tandy Warnow), Electrical Engineers (eg. Claude Shannon), etc.

ML (and CS in general) is very interdisciplinary, and it annoys me that a lot of SWEs think they know more than other fields.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#707

This is totally bizarre, no precedent for it really. The reality of the prize means that less and less are the winners names every physicist has heard of, but even today they're still big names in each subfield. For e.g. Kosterlitz, Thouless and Haldane weren't exactly household names but they really deserved the prize in 2016. In this case, there's a good argument that Hopfield had conducted strong work as a physici…

Bob Dylan got a Nobel prize in literature, which feels something like a precedence.

The key is field. A physicist use maths will not get maths prize if just use it for physics.

He use words and its lyrics has meaning, like any literature. Cannot say poetry is not literature. Then why not poetry with music, probably more traditional as many poems are songs. In some culture, it must be singable.

These use physics but not in the field of physics. Otherwise anyone use qm can get Nobel prize and chemistry people can get one as they all use physics. Really need to be in the physics field. You can use other method like computer, maths.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#708
post #703

My perspective as a PhD in theoretical physics, who's been doing deep learning in the last 4 years: 1. The prize itself makes zero sense as a prize in _physics_. Even the official announcement by the Nobel Prize Committee, taken at a face value, reads as a huge stretch in trying to link neural networks to physics. When one starts asking questions about the real impact on physics and whether the most important works o…

> because physics is currently stalled. Even if it's not completely true, maybe some introspection is required? I understand developing new theories is important and rewarding, but most physics for the last three decades seems to fall within two buckets. (1) Smash particles and analyze the data. (2) Mathematical models that are not falsifiable. We can be pretty sure that the next 'new physics' discovery that gives us…

Those two buckets only contain the work in physics that have a sustained presence in popular media. But take gravitational wave astronomy as a counterexample. It doesn't make it into the news much, but I'm pretty sure the entire field is less than ten years old.

Re: Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]

#710
post #703

My perspective as a PhD in theoretical physics, who's been doing deep learning in the last 4 years: 1. The prize itself makes zero sense as a prize in _physics_. Even the official announcement by the Nobel Prize Committee, taken at a face value, reads as a huge stretch in trying to link neural networks to physics. When one starts asking questions about the real impact on physics and whether the most important works o…

> because physics is currently stalled. Even if it's not completely true, maybe some introspection is required? I understand developing new theories is important and rewarding, but most physics for the last three decades seems to fall within two buckets. (1) Smash particles and analyze the data. (2) Mathematical models that are not falsifiable. We can be pretty sure that the next 'new physics' discovery that gives us…

> most physics

That's an interesting definition of "most physics". I mean, I find high-energy physics as fascinating as the next guy but there are other fields, too, you know, like astrophysics & cosmology, condensed-matter physics, (quantum) optics, environmental physics, biophysics, medical physics, …

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