[FRIAM] neural operators seem promising
Stephen Guerin
stephen.guerin at simtable.com
Wed Jul 16 20:10:26 EDT 2025
On Wed, Jul 16, 2025 at 11:19 AM Steve Smith <sasmyth at swcp.com> wrote:
>
> - Did Harold Morowitz make a strong assertion to the tune: "we learned
> more about thermodynamics from steam-engines than vice-versa"? EricS or
> StephenG might have first-hand knowledge?
>
>
Yes, that quote is the last paragraph of chapter 30 in Harold's "The
Emergence of Everything: How the World Became Complex":
"The role of technology in science is summed up in this statement: steam
engines have taught us more about thermodynamics than thermodynamics has
taught us about steam engines."
It is one of my favorites about applied technique informing theory.
At a SFI tea around the kitchen table, I propposed to Harold a potential
modern equivalent of an applied engineering potentially informing
Complexity theory. The prevalence of the bidirectional path tracing on the
primary and dual model to find 'least action" or optimal transport paths.
eg
- operations research routing logistics,
- rendering light
<https://en.wikipedia.org/wiki/Path_tracing#Bidirectional_path_tracing>
- sound in games <https://www.youtube.com/watch?v=DzsZ2qMtEUE>
- ant foraging algorithms
<https://phys.org/news/2013-04-ants-fermat-principle.html>,
<https://ieeexplore.ieee.org/document/6475940>
- internet routing path selection
<https://ieeexplore.ieee.org/document/6475940>,
- bidirectional maze solving,
<https://github.com/cejast/bidirectional-maze-searching>
- bidirectional dijkstra, etc.
Might primary and dual transactional processes be a general theory of
complex systems in at least a nche neighborhood of the discipline? I think
he appreciated the system/ecological perspective which was also consistent
with his work with Eric in Origin of Life. He certainly was patient with
my wild hair speculations - He was one of the kindest and most insightful -
suspenders and all. :-)
-Stephen
_________________________________________________________________
Stephen Guerin
CEO, Founder
https://simtable.com
stephen.guerin at simtable.com
stephenguerin at fas.harvard.edu
Harvard Visualization Research and Teaching Lab
<https://hwpi.harvard.edu/eps-visualization-research-laboratory/home>
mobile: (505)577-5828
On Wed, Jul 16, 2025 at 11:19 AM Steve Smith <sasmyth at swcp.com> wrote:
>
> - Anima's presentation reminded me quite nicely of the Numenta/Redwood
> work of Jeff Hawkins et al? Cortical columns, etc.
> - Did Harold Morowitz make a strong assertion to the tune: "we learned
> more about thermodynamics from steam-engines than vice-versa"? EricS or
> StephenG might have first-hand knowledge?
> - Is this theory/practice dichotomy just another form of
> meta-scaffolding in evolution (of any system) with the cut-and-try
> providing the mutation/selection and the theory/formalism binding the
> "lessons learned" into well... "lessons learned"?
>
> On 7/16/2025 2:12 AM, Pieter Steenekamp wrote:
>
> Both the video of Anima Anandkumar’s Stanford seminar and her scientific
> paper on Neural Operators really got me excited—the ideas feel fresh and
> powerful.
>
> The paper is quite technical and digs into the math behind
> Neural Operators, without talking much about robotics. In her talk, though,
> she clearly links the work to robots, and it sounds as if robotics is a big
> focus for her team.
>
> What jumped out at me is how different her style is from Elon Musk’s
> approach with Tesla’s Optimus robot. Anandkumar begins with deep theory,
> building firm mathematical foundations first. Musk takes a “just build it”
> path—make it, test it, break it, fix it, and keep going.
>
> This contrast reminds me of engineering school and the Faraday‑Maxwell
> story. Faraday was the hands‑on experimenter who uncovered the basics of
> electricity and magnetism through careful tests. Maxwell came later and
> wrote the elegant equations that explained what Faraday had already shown.
>
> So I wonder: will the roles flip this time? Will deep theory from
> researchers like Anandkumar guide the breakthroughs first, with practice
> following? Or will practical builders like Musk sprint ahead and let theory
> catch up afterward?
>
> Either way, watching these two paths unfold side by side is thrilling. It
> feels like we’re standing on the edge of something big.
>
> On Wed, 16 Jul 2025 at 04:11, Jon Zingale <jonzingale at gmail.com> wrote:
>
>> Even if just for the freedom of scale, learning infinite dimensional
>> function spaces, etc...
>>
>> https://www.youtube.com/watch?v=caZyFlSSKtI
>> https://arxiv.org/pdf/2506.10973
>>
>>
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