Comment by hintymad

2 days ago

> The Jacobian Conjecture

Interestingly, Yitang Zhang of the twin-prime-conjecture fame spent 7 years working on the Jacobian conjecture under the advisor Tzuong-Tsieng Moh at Purdue. A key step in his thesis used a corollary of Moh's. It turned out that the corollary was incorrect. As a result, Moh refused to write any recommendation letter for Zhang, and Zhang couldn't find any teaching or research job and ended up spending years working at a Subway[1].

Imagine Zhag had ChatGPT in 1986 when he started working on the Jacobian Conjecture.

[1] Of course now this has become an inspiring story. That said, the story definitely invokes complex emotions. The best way to describe it is probably this Chinese poem, which I have no idea how to translate: 庾信平生最萧瑟,暮年诗赋动江关

I was once in a presentation for a math PhD thesis. During the thesis, the evaluator of the thesis noticed a flaw in their proof. The student understood and then asked “What now?” The evaluator prof simply shrugged.

  • I personally know a story in this vein with a (sort of) happy ending.

    A PhD student discovered that a result of his professor would imply the solution to a big conjecture in another field. The people in that field then analyzed the prof's result and found that the proof was flawed. The student was still allowed to graduate based on this since the finding of the connection between fields was brilliant. Then he quit academia (not because of this story, he had planned it before). Then a year later the prof figured out how to fix the flaw in his proof and published a paper with his former student, thus solving the conjecture. The two are still on good terms, writing papers together.

    • > The two are still on good terms, writing papers together.

      Why are you framing this like this? Do mathematician take these kind of things personally?

      1 reply →

  • That sounds like the worst "exam nightmare" scenario imaginable, but did the student get the PhD in the end?

    • Mistakes in proofs are relatively common, but such a mistake doesn't automatically mean that the proof is entirely wrong. Many times, the mistake is just in the exposition, and can be fixed easily. Other times, the mistake is fixable and the fix is apparent. Perhaps the author forget to treat a relatively trivial edge case. In the first two cases, the student would likely just pass with minor corrections to be submitted soon.

      Sometimes, of course, the proof is just wrong. That is the dangerous case, which will cause either major corrections or failure.

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  • I first heard that kind of story about a thesis defense at Princeton. The twist was that they had been short one person to judge it, so they roped in a professor who was available at that moment ... and he found a counterexample on the fly.

    The professor was John Milnor.

  • A recording of a car crash: discovering on live radio/podcast that the central tenet of your book is wrong, and amateurishly so.

    Naomi Wolf 'death recorded' on BBC[1], skip to 5:51. After this the book was pulped and she had some sort of psychotic break during COVID and allied with ultra-right and COVID denialist loonies.

    [1] https://www.bbc.com/news/av/world-us-canada-48639663

    • Is the video available not through a proprietary player?

      > After this the book was pulped and she had some sort of psychotic break during COVID and allied with ultra-right and COVID denialist loonies.

      That's quite an extreme shift considering she had previously been a leading figure in third-wave feminism and an OWS activist.

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    • It doesn't seem too egregious an error to assume "death recorded" means they were executed, rather than the opposite where death was recorded as the verdict but not actually executed.

      Not checking newspaper reports of the period is lazy though and exactly the kind of thing I'd expect a journalist to do and therefore be the one to discover the flaw.

      1 reply →

Inspiring? Because of the twin prime conjecture success following his time in the wilderness? I suppose so.

I'm tired of tales like this in academics though. That's not a criticism of you for telling the tale, I'm just so tired of this kind of thing in academics in general. So, so, so much politics and public reputation management. Zhang should have never had to suffer like that.

As my own research has drifted more into math, I've been surprised at how many assertions in the literature turn out to be false. Not just false, but propagated into the applied literature extensively, and even when you point out the problems a lot of defensiveness and denial about it along the lines of Zhang's story.

I agree about wondering what would have happened if LLMs had been around in 1986. My guess is the outcome would have been the same for the same reasons?

My experience with LLMs in proofs is they can be very helpful, but also very wrong. It's like having another person with another set of hunches about what path to go down.

  • > So, so, so much politics and public reputation management. Zhang should have never had to suffer like that.

    Very true. Unfortunately, when there are people, there will be politics. I remember when reading Yau's autobiography, I kept marvel how much calculation, or "politics" if you will, that Yau mentioned or implied in the book.

    > My guess is the outcome would have been the same for the same reasons?

    At least Zhang didn't have to spend 7 years working on the Jacobian conjecture. He said in an interview that he always wanted to work on number theory. Moh asked him to work on Jacobian, and he obliged.

  • Planck's Principle: 'Science advances one funeral at a time.' [1]

    In his exact words: "A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it... An important scientific innovation rarely makes its way by gradually winning over and converting its opponents: it rarely happens that Saul becomes Paul. What does happen is that its opponents gradually die out, and that the growing generation is familiarized with the ideas from the beginning: another instance of the fact that the future lies with the youth."

    And he said that having lived, as a outsized figure, through the late 19th to mid 20th century of physics, which was the absolute golden age for such.

    [1] - https://en.wikipedia.org/wiki/Planck's_principle

    • The more important lesson for those of us are are "old" is to not get stuck in things that were learned in the past when they are found false.

      If you are not yet old, remember this - it is very likely you will old in a few years.

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ChatGPT's idiomatic translation of the poem:

Yu Xin’s was a life of utter desolation; in old age, his poems and rhapsodies stirred the riverlands.

  • Opus:

    No life ran more bleak and desolate than Yu Xin's —

    yet in his twilight years, his verses stirred the rivers and the passes.

  • I guess that works, it is always difficult to capture the cultural and linguistic melancholy of such poetry.