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Comment by VHRanger | Hacker News Reader

Geoffrey Hinton wins the Nobel prize in physics for giving physics postdocs more reasonable job market options

And as an ML engineer with a PhD in physics I can tell you that I am deeply grateful that I didn't have to go the postdoc route.

I know we are joking around here, but damn, just for that alone I'm happy that he got it.

For whether it is actually physics? That I'll leave for another discussion.

This prize is more of a settler colonialist land grab by physicists. ML is just a subfield of physics (like every other field), so let's make sure that everyone knows that it's in our domain.

Speaking as a onetime physicist now in ML...

Eh, I doubt Hinton would have won if he hadn't turned to alarmism in his dotage. The prizes are as political these days as they are scientific.

machine learning is math, not physics. physics uses math, not the other way around. ML can be used in any field of science, not vice versa.

The actual process of computation, sure, but machine learning was born from physics-based methods and applications to understand complexity and disorder.

I think ML depended on math/statistics/computing much more than physics. It's much easier to see what Hopfield and Hinton did as inspired by mathematical models that were created to help study statistical mechanics. Which is fine and just shows how stochastic scientific discovery is.

It's compsci, but nice try.

Computer science is math. Just math.

Math, Logic, Epistemology, et al are not "subfields of physics" - The other way around is more likely.

I also had this view, but thinking a bit more about it, what we consider 'reasonable axioms' in math, all come more or less from our logical intuition. Which was built from our evolution, which respects the laws of physics.

This has changed my point of view to where math is kinda derived from physics, as the axioms (but even the derivation rules, like modus ponens) are chosen because they respect what feels intuitively 'logical'. But this intuition cannot be disentangled from physics, as it was a product of physics.

I mean mainstream maths sure, that doesn't mean you can't replace the axioms with one's that aren't.

I would agree.. But it took Computer Scientists to put neural networks on the map by getting them to scale. Basically by asking the question what happens if we turn it up to 11.

Statisticians would never have done that due to parsimony and something something Bayesian.

Engineers would never have done it, nor mathematicians either.

It took Computer Scientists because it is computation.

Ok, now I understand why this is a notable achievement in physics

lol,All for employment

Lol I almost choked laughing at this lmaoo

...than finance

It's been a generation since it was easy to go into finance from physics.

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