The stuff about Gabelsberger shorthand sounds ludicrous to me. My father would write notes in a custom version of it until his death 2020.
Officially (i.e. in schools teaching stenography, back in the day) it was long ago replaced by "unified German shorthand" (Deutsche Einheitskurzschrift IIRC), but he always considered Gabelsberger to be superior.
Well, maybe he too was one of the 6 people in the world who could read it (or yes, maybe that was hyperbole, I'm not sure) :D
I can't remember the exact quote but I believe I read that Gödel confided to Einstein (in their walks in Princeton) on his deep worry of his work being forgotten. If only he knew.
This is incredibly exciting! Gödel is unquestionably the most important logician in history, but unfortunately he published very little. For instance, the Dialectica interpretation was published approximately 20 years after his first ideas on the subject.
Plus, Jan von Plato is the world's leading expert on Gödel -- the number of people who can read Gödel's handwriting can be counted on the fingers of one hand, and I think that every single one is part of Jan von Plato's research group. If he is excited about the output, this is a huge deal.
This might be an actual concrete example of someone making themselves obsolete with AI.
> Von Plato said he had started his Gödel project in 2017 because he was facing mandatory retirement from Helsinki University. “What should I do to make myself indispensable? Oh yes, I’ll start reading Gödel’s enigmatic shorthand pages!” He received a €2.5m (£2.1m) grant from the European Research Council, taught himself Gabelsberger shorthand – “I am one of only six people who can read it in the world” – and assembled a small team.
The professor's value was/is in being one of a few people with the capability of interpreting the shorthand. By translating it with AI, his value as an interpreter begins evaporating as the translated workbooks become accessible to more logicians.
It's clear though. Even if an AI had connected all the dots on the obsolete shorthand, it would never have recognized the human value. I doubt that any AI process would choose to spend the energy on interpreting this particular obsolete handwriting and then understand that it was from the hand of a genius.
Using AI to do your job does not mean that AI suddenly walks in the door and escorts you out and starts collecting your paycheck.
Someone is still driving these studies, and probably will be for a while. Or maybe not. But still we can reward this guy for opening up this can of theorems that had before.
Silliest case:
Imagine a dusty basement terminal screen open to claude code with "There we go! Cancer is cured as you requested, let me know and I'll send off the results" and nobody is around to approve it.
"You don't get credit for the work you don't tell anybody about"
This has been a problem long before Godel: famously, Newton tried to get credit for inventing Calculus only after Leibniz published his work, leading to a bitter dispute that lasted long after they both died.
I wonder if this problem is now going to be significantly exacerbated by AI, as mathematicians are getting more incentives to keep their works secret —
— or, to the contrary, the community will get a push to publish incomplete ideas, scratch work, etc. early to establish a record of thinking about a problem before others did.
In the end, as always, it's a social problem created by " publish or perish " institutional incentives which reward (and require!) published results, but not the work that led to to them.
Maybe we'll see a solid societal use case for zero-knowledge proofs here, establishing one had a set of documents at a given date without revealing them.
At least that's how traditional Western universities used to work. The profs sometimes published something, and they taught students. Looking at science back then, it seemed to work out rather well.
Nice timing for the IPO. Cooked Nvidia numbers on the 17th are still missing, and the 19th will go well!
The AI was of course trained on existing pre-AI transcriptions of Goedel's shorthand, which he was taught in school around 1920 and which was widespread and only technically "obsolete".
In the first paragraph, we have an evidence-free insinuation that the foremost expert on this subject is some kind of shill running a campaign for Anthropic. What does this campaign involve? Is he just making it all up? Let me hear your theory of what is happening here and how it invalidates the claimed abilities of the model (or why the abilities do not matter).
In the second paragraph, we have what appears to be a claim that the model knows how to read Gödel's shorthand because it has been exposed to past examples of that shorthand. What is your point here? I think the model learning to generalize by training on a few examples is a point in its favor.
Why? His incompleteness work explains why software and math suck so he would already expect them to; they're rhetorical and can never fully be a closed loop body of knowledge as we can never with rhetoric concretely observe/define the far future or far past; merely simulate rhetorically
Ergo all defined axiomatic systems have sentences about the far past and future that cannot be defined in those languages with certainty. Most do not make the connection to physics. Gödel did and would 100% aware the limits exist and will always exist
Scaling laws aren't just for computers; humans lived experience does not scale infinitely through time, just approximately 2-3 generations
As I understand immutable physical truth like this played a huge role in his early research and ultimately were the forcing function that led him to incompleteness
Officially (i.e. in schools teaching stenography, back in the day) it was long ago replaced by "unified German shorthand" (Deutsche Einheitskurzschrift IIRC), but he always considered Gabelsberger to be superior.
Well, maybe he too was one of the 6 people in the world who could read it (or yes, maybe that was hyperbole, I'm not sure) :D
Plus, Jan von Plato is the world's leading expert on Gödel -- the number of people who can read Gödel's handwriting can be counted on the fingers of one hand, and I think that every single one is part of Jan von Plato's research group. If he is excited about the output, this is a huge deal.
genius often comes with side effects
> Von Plato said he had started his Gödel project in 2017 because he was facing mandatory retirement from Helsinki University. “What should I do to make myself indispensable? Oh yes, I’ll start reading Gödel’s enigmatic shorthand pages!” He received a €2.5m (£2.1m) grant from the European Research Council, taught himself Gabelsberger shorthand – “I am one of only six people who can read it in the world” – and assembled a small team.
Someone is still driving these studies, and probably will be for a while. Or maybe not. But still we can reward this guy for opening up this can of theorems that had before.
Silliest case: Imagine a dusty basement terminal screen open to claude code with "There we go! Cancer is cured as you requested, let me know and I'll send off the results" and nobody is around to approve it.
This has been a problem long before Godel: famously, Newton tried to get credit for inventing Calculus only after Leibniz published his work, leading to a bitter dispute that lasted long after they both died.
I wonder if this problem is now going to be significantly exacerbated by AI, as mathematicians are getting more incentives to keep their works secret —
— or, to the contrary, the community will get a push to publish incomplete ideas, scratch work, etc. early to establish a record of thinking about a problem before others did.
In the end, as always, it's a social problem created by " publish or perish " institutional incentives which reward (and require!) published results, but not the work that led to to them.
This, I hope, will finally change.
The AI was of course trained on existing pre-AI transcriptions of Goedel's shorthand, which he was taught in school around 1920 and which was widespread and only technically "obsolete".
https://link.springer.com/book/10.1007/978-3-030-67606-3
In the second paragraph, we have what appears to be a claim that the model knows how to read Gödel's shorthand because it has been exposed to past examples of that shorthand. What is your point here? I think the model learning to generalize by training on a few examples is a point in its favor.
Ergo all defined axiomatic systems have sentences about the far past and future that cannot be defined in those languages with certainty. Most do not make the connection to physics. Gödel did and would 100% aware the limits exist and will always exist
Scaling laws aren't just for computers; humans lived experience does not scale infinitely through time, just approximately 2-3 generations
As I understand immutable physical truth like this played a huge role in his early research and ultimately were the forcing function that led him to incompleteness