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      <li>Anima's presentation reminded me quite nicely of the
        Numenta/Redwood work of Jeff Hawkins et al?   Cortical columns,
        etc.  </li>
      <li>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?</li>
      <li>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"?</li>
    </ul>
    <div class="moz-cite-prefix">On 7/16/2025 2:12 AM, Pieter Steenekamp
      wrote:<br>
    </div>
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cite="mid:CAPerSOJ+P7PTzjMgKSwnJyEgxEYYhvAO1H2GDHGqznQ+=KGGPg@mail.gmail.com">
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      <div dir="ltr">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.<br>
        <br>
        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.<br>
        <br>
        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.<br>
        <br>
        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.<br>
        <br>
        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?<br>
        <br>
        Either way, watching these two paths unfold side by side is
        thrilling. It feels like we’re standing on the edge of something
        big.</div>
      <br>
      <div class="gmail_quote gmail_quote_container">
        <div dir="ltr" class="gmail_attr">On Wed, 16 Jul 2025 at 04:11,
          Jon Zingale <<a href="mailto:jonzingale@gmail.com"
            moz-do-not-send="true" class="moz-txt-link-freetext">jonzingale@gmail.com</a>>
          wrote:<br>
        </div>
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style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
          <div dir="ltr">
            <div class="gmail_default"
style="font-family:verdana,sans-serif;font-size:small;color:rgb(51,51,51)">Even
              if just for the freedom of scale, learning infinite
              dimensional function spaces, etc...</div>
            <div class="gmail_default"
style="font-family:verdana,sans-serif;font-size:small;color:rgb(51,51,51)"><br>
            </div>
            <div class="gmail_default"
style="font-family:verdana,sans-serif;font-size:small;color:rgb(51,51,51)"><a
                href="https://www.youtube.com/watch?v=caZyFlSSKtI"
                target="_blank" moz-do-not-send="true"
                class="moz-txt-link-freetext">https://www.youtube.com/watch?v=caZyFlSSKtI</a></div>
            <div class="gmail_default"
style="font-family:verdana,sans-serif;font-size:small;color:rgb(51,51,51)"><a
                href="https://arxiv.org/pdf/2506.10973" target="_blank"
                moz-do-not-send="true" class="moz-txt-link-freetext">https://arxiv.org/pdf/2506.10973</a></div>
            <div class="gmail_default"
style="font-family:verdana,sans-serif;font-size:small;color:rgb(51,51,51)"><br>
              <br>
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