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davidlowryduda

davidlowryduda@mathstodon.xyz

<p>Mathematician, programmer, and other things at other times.</p>

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    Sleep when the baby sleeps, clean when the baby cleans, and cook when the baby cooks.

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    These are awesome. https://arstechnica.com/science/2026/10/meet-the-2026-winner-of-nikons-small-world-photomicrography-contest/

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    I hear fears about the interaction of LLMs and the sciences. People worry how the sciences will change. One challenge with discussing this is that it&amp;#39;s hard to describe *how the sciences work now.* #science #mathematics

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    Some of my recent work is now public: https://institutional.org/posts/extending-institutional-books/

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    OpenAI solves Navier-Stokes using on the order of 16M dollars of better-than-Astra internal model power. https://openai.com/index/navier-stokes-solution/ Possibly including side-channel information from Tristan and Levent&amp;#39;s work? (See https://cims.nyu.edu/~tristanb/statement.pdf) This is a remarkable result. It&amp;#39;s a good example of computationally-assisted math. But is it an example of how to generate new mathematical insight? Messy.

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    Should I take the fact that none of my work or research has been scooped as a sign that it&amp;#39;s not exciting enough?

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    Navier-Stokes, Alpoge-Buckmaster, and OpenAI have made bigger waves than I expected. I&amp;#39;ve read many takes and opinions. 1/3

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    But can AI ever give me the same satisfaction as watching &amp;quot;tail -f my_great_process.log&amp;quot; on a screen?

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    I&amp;#39;ve somehow found myself with some devops responsibilities. Today is rotate-all-the-keys day. It&amp;#39;s not hard, but it is annoying.

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    Updated #introduction: I&#39;m a senior research software engineer at the Institutional Data Initiative at the Harvard Law School Library. I think about data and ML and NLP, mostly in service of libraries and knowledge institutions. I used to be a research scientist at ICERM working in theoretical and computational number theory. I still think about math and computation and would be happy to talk more about it. I usually write either #python or #cpp and I like talking about #data or #code or #...