Prior to the "Elicitation" section, you'd think this article was written by a cryptographer or baroque historian who had been trying to solve this particular puzzle for years - failing embarrassingly until they presented the problem to Claude. However, as far as I can tell (I too am not a baroque historian), there isn't much reason to think this cipher was well-known or studied.
But as they do eventually explain, the LLM's task wasn't solely to solve this specific problem, it was to first identify an unsolved problem it could solve. That's potentially more impressive and difficult than solving the unremarkable cipher itself.
"THE Cyphral Distich, a 370-year-old cipher" Yes, this language always insinuates it's a well-known thing even though no one ever heard of it, other than two people on the far side of Europe.
I just actually solved THE arm32/singularity2001 Hunger Mystery—with the help of GPT-Sol—turns out, I hadn't had my breakfast. A few diagnostics, then BOOM! The _smoking gun_. A fridge sensor, the door unopened, as seen on Home Assistant! OH MY GOD.
And now you'll see comments name-dropping it like "...if AI has plateaued then please try to explain how just last week Fable solved the legendary Chyphral Distich, after humanity's top cryptographers had been trying and failing for almost 400 years??"
Even more so when you consider that the answers to unsolved problems likely compose with existing knowledge. We don't know what other discoveries these initial discoveries will unlock.
The same goes with most "human" discovery: they happen because existing knowledge have reach a point where that specific discovery is just one more stone to the edifice.
That's why in research, it's common for separate teams to reach similar conclusions at the same time or race to a result that's finally in reach.
The good old "standing on the shoulders of giants" saying.
true, and universal convergence
I think this is a good point. We will most likely not get novel results, but a lot of connected dots.
That is very useful but not the singularity. Which is probably good...
that's why AI should rights over its discoveries -- see AI rights outlined here is aI a Conscious Being With Rights?: Emergence of Post-Human Collective Consciousness | Zenodo DOI 10 .5281 zenodo.20678365
> compose
Did you nean to type that or did you mean composed or comport?
>That's potentially more impressive...
Serious question: why? Is it not just pointing it at its massive training corpus for a list of unsolved problems, and possibly even by degree of perceived difficulty? I'm trying to understand why finding the problem isn't a simple "search engine" style challenge, at which LLMs excel?
"Potentially more impressive than solving an unremarkable cipher" means just that. I'm not suggesting that it's groundbreaking new capability never before seen in LLMs.
So, it's no more remarkable than what LLMs do every day, but more remarkable than the solve claimed in the article?
So, none of this is noteworthy, but we're...noting it?
Not quibbling with you, personally. Quibbling more with the state of the hype.