* 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 <[email protected]> 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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