[FRIAM] neural operators seem promising

[Pieter Steenekamp]

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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