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Terence Tao's quote about AI's math proofs is relatable outside of pure math: "the writing very often dwells at length on trivialities while passing briefly thr
by highfrequency 28d ago
Terence Tao's quote about AI's math proofs is relatable outside of pure math: "the writing very often dwells at length on trivialities while passing briefly through — or even actively obscuring — the most interesting and novel portions of the argument."
- paulpauper 28d agoSimilar to Ai writing. Lots of bloat.
- piker 28d agoCoding, too.
- TMWNN 28d ago>Terence Tao's quote about AI's math proofs is relatable outside of pure math: "the writing very often dwells at length on trivialities while passing briefly through — or even actively obscuring — the most interesting and novel portions of the argument." I noticed a long time ago, that the more people focus on trivialities like typos when arguing against someone online, the more compelling the original argument is. Basically, bikeshedding. The most compelling evidence of the compelling nature of the original argument is when the most-upvoted reply is a joke or a meme. That's when you really know that those responding have nothing else to say. It's a white flag being run up, or the dog turning over and exposing its belly.
- jltsiren 28d agoI noticed another thing a long time ago. Some academic cultures have a tradition of formal debates. They are based on the premise that an educated person should be able to argue convincingly for or against any idea, regardless of whether they believe in it. A natural corollary is that you should not let convincing arguments convince you, as the merits of the argument have little to do with the merits of the idea itself. LLMs have made the situation worse. People's ability to generate convincing arguments now greatly exceeds their ability to evaluate the value of ideas.
- xdavidliu 28d ago> They are based on the premise that an educated person should be able to argue convincingly for or against any idea, regardless of whether they believe in it. In many situations, people doing this, skillfully even, has had quite pernicious consequences.
- noosphr 28d agoThat's also true for regular math proofs. No one talks about why the proof works, but they will happily spend thousands of pages explaining how it works.
- ipdashc 28d agoSomeone just brought up this point to me a few days ago on here, I'm definitely increasingly convinced that it's one of the main reasons (maybe even the main reason?) AI prose is so annoying to read through, and so rarely seems able to convey true understanding. It assigns the same narrative importance and dramatic tone to everything (the load bearing whatever, the crucial insight, the smoking gun) even when it's trivial.
- chrisjj 28d agoWhat surprises me is anyone is surprised. Obviously a stocastic parrot has no understanding, so any conveyance of true understanding it delivers will be rare and accidental.
- ipdashc 28d agoI mean, having said what I said, we are literally in a thread about the future of mathematics being in question because LLMs are solving advanced problems. I feel like the "stochastic parrot" meme is a bit outdated by now. The bots' output may be annoying to read but they're clearly onto something, whether we call it "understanding" or not.
- chrisjj 27d ago> I feel like the "stochastic parrot" meme is a bit outdated by now. The stochastic parrot of my reference is not a meme. https://en.wikipedia.org/wiki/Stochastic_parrot https://en.wikipedia.org/wiki/Stochastic_parrot The term was introduced in a 2021 paper on AI ethics titled "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? " that was authored by Timnit Gebru, Emily M. Bender, Angelina McMillan-Major, and Margaret Mitchell.[a] > The bots' output may be annoying to read but they're clearly onto something Sure. Next-token prediction with huge source set and computation power. Nothing new there.
- deleted 27d ago[deleted]
- addag 28d ago[dead]