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The Legend of von Neumann (1973) [pdf]

311 points · 186 comments · suopspaces

  1. srejk · · focus · HN ↗
    When you look at it holistically, von Neumann was more influential in science and mathematics in the 20th century than either Einstein or Planck. He wasn't as obvious a symbol of the scientific revolution, but his contributions to SO MANY THINGS at a fundamental level makes him stand out to me.
    1. JoeAltmaier · · focus · HN ↗
      It's odd that even today, different disciplines are still silo'd. My son started a research cross-database search engine because different disciplies use different terms for nearly identical concepts. Even within medicine it's silo'd.

      Trouble with that startup was, the medical folks with money don't use computer tools. And the students in training have no money.

      1. baruz · · focus · HN ↗
        A researcher submitted a paper to the medical journal _Diabetes care_ in the nineties that basically redescribed integral calculus as a novel finding. How’s that for a silo?
        1. mmulqueen · · focus · HN ↗
          For anyone else who is curious:

          <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Tai%27s_model" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Tai%27s_model

          <a href="https:&#x2F;&#x2F;pubmed.ncbi.nlm.nih.gov&#x2F;8137688&#x2F;" rel="nofollow">https:&#x2F;&#x2F;pubmed.ncbi.nlm.nih.gov&#x2F;8137688&#x2F;

          1. jablongo · · focus · HN ↗
            This is really funny. A less extreme example is how much domain-specific terminology in Reinforcement Learning and Control Theory&#x2F;Model Predictive Control refer to the same underlying phenomena, but we must translate between the two. I understand there are many unique concepts as well, but it would be so helpful if the overlap here used the same terminology and notation.
            1. Animats · · focus · HN ↗
              I still get IEEE Trans. on Control Theory, and it&#x27;s all machine learning now. Except that the controls people are desperately trying to solidify the underpinnings of machine learning, so that control systems don&#x27;t suddenly misbehave for some sets of inputs. Controls people want a guarantee that if it does something reasonable for inputs of 5.1 and 5.2, it doesn&#x27;t do something completely unexpected for an input of 5.15.
              1. donquichotte · · focus · HN ↗
                Reminds me of my favorite abstract, from John Doyle&#x27;s paper &quot;Guaranteed Margins for LQG Regulators&quot;.

                <a href="https:&#x2F;&#x2F;improbable.com&#x2F;wp-content&#x2F;uploads&#x2F;2011&#x2F;10&#x2F;ThereAreNone.gif" rel="nofollow">https:&#x2F;&#x2F;improbable.com&#x2F;wp-content&#x2F;uploads&#x2F;2011&#x2F;10&#x2F;ThereAreNo...

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