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    AI’s potential to make mathematics more essential

    A user predicts a shift away from human-posed conjectures toward AI systems continually formulating, solving and using mathematics for science, engineering and computing.

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    6 Sources, ,

    TLDR

    Invoking Jevons paradox—the idea that lower costs can spur greater use—a user predicts that cheaper, deeper mathematics will become even more fundamental to future infrastructure. In that vision, math is no longer centered on human-posed conjectures: AI systems continually formulate, solve, process and apply it while tackling hard scientific, engineering and computing problems.

    Combined views

    37K

    6 Sources, first seen 19d ago

    Combined views

    37K

    6 Sources, first seen 19d ago

    753 likes
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    19d ago
    first seen 19d ago
    753 likes
    52 comments
    44 saves
    131 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    52 comments
    44 saves
    131 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    6 Sources

    @EMostaqueUsing AI models is just using math to do math I think AI teams should stop feeling ashamed of solving these problems making math less “pure” It’s like feeling ashamed to use a calculator or mathematica We build the best tools we can to solve everything That is human
    @willcbmath and code is just neurosymbolic grokking that’s already been done by human subagents
    @CarinaLHongRT @ChrSzegedy: If I did not believe in the intrinsic and underrated usefulness of mathematics, I would be somewhat sad about what AI is do…
    @aminkarbasiOne thing I’ve learned from coding with LLMs is how much human-written code is simply bad, like really bad. LLMs are already very good at cleaning it up and following good coding practices. I believe the same will be true in mathematics. Many exisitng proofs are correct , but often badly written. We are not there yet, and we still need Lean to verify proofs generated by LLMs. But soon, many existing and nee proofs will be rewritten more clearly and beautifully. And that will be good for mathematics and mathematicians.
    @minilek@thegautamkamath I think this focuses too much on the current state of affairs without any forecasting. Re slop: the models will only get better at writing.

    6 Sources

    @EMostaqueUsing AI models is just using math to do math I think AI teams should stop feeling ashamed of solving these problems making math less “pure” It’s like feeling ashamed to use a calculator or mathematica We build the best tools we can to solve everything That is human
    @willcbmath and code is just neurosymbolic grokking that’s already been done by human subagents
    @CarinaLHongRT @ChrSzegedy: If I did not believe in the intrinsic and underrated usefulness of mathematics, I would be somewhat sad about what AI is do…
    @aminkarbasiOne thing I’ve learned from coding with LLMs is how much human-written code is simply bad, like really bad. LLMs are already very good at cleaning it up and following good coding practices. I believe the same will be true in mathematics. Many exisitng proofs are correct , but often badly written. We are not there yet, and we still need Lean to verify proofs generated by LLMs. But soon, many existing and nee proofs will be rewritten more clearly and beautifully. And that will be good for mathematics and mathematicians.
    @minilek@thegautamkamath I think this focuses too much on the current state of affairs without any forecasting. Re slop: the models will only get better at writing.