Posted by u1hcw9nx 6 hours ago
> Caveats, stated plainly. [from the Fable transcript pasted in the article]
I had a visceral reaction to these three words.
The answer the tool gives has never been the real reward. The real reward is the path taken through a complex landscape to get to Maxwells Equations for example. At the end of that story what we get is not just the equation but a map of the landscape explored. That map has larger influence and value than the equations or answers themselves. Because all future exploration find it super useful.
People are just learning they can start asking for maps rather than answers.
You should have seen the discussion of this on the Schneier blog a few days ago.
Someone had their agent check the solution, presumably it emailed a librarian to check that it was correct for the original edition. Then their comments read like "The BL/EEBO witness lacks it, so the discrepancy is copy-specific, not a disproof of the cipher." and "A complete 285-coordinate physical replication is still pending."
arghhhhh
https://www.schneier.com/blog/archives/2026/09/claude-fable-...
> The run baseline was captured without a physical MAC; the current device is not durably bound to it.
> Engineering mode confirmation is the ESPHome component read-back; the LD2410 UART acknowledgement is not observed, so this is not proof the radar itself applied the sensitivity change.
No clue what the fuck any of it means.
https://www.analog.com/en/resources/analog-dialogue/articles...
(Its negging your soldering)
This made me laugh hard.
Their skills formats are basically identical, so I setup simlinks from their own skills directories into a shared one so Claude, Codex, Cursor, and anything else that comes out will all read and write to the same shared skills.
It's great having access to the same skills no matter the harness being used
I'm not sure that telling it to "try explaining that again, simply and briefly" is helping my ego.
"If the crashes stop, the factory overclock is marginal; run a small negative offset."
This looks like it's saying: "If the crashes stop then we know the factory overclock is marginal." (This makes no sense.)
What it's trying to say is: "If the crashes stop then we can run a small negative offset, because the factory overlock is marginal."
What I would write: "If the crashes stop, we can avoid crashes by underclocking slightly. The speed difference between that and factory clock is marginal."
Succinct and precise; a well crafted sentence. A marginal OC results in unpredictable crashes and can be corrected with a small offset; marginality describes the behavior and explains the solution.
Inscrutable clues casually conveyed can now be readily explained, at least, unlike the training data of [silence]. Brevity is the soul of wit, but perhaps also exasperated confusion.
Because good lord, does claude waffle when left to its own devices.
it's absolutely not just you, the text it produces causes my blood pressure to go up.
Whenever I come to a wall of complicated text I kick into gear and think through getting it to distill this into the high-level useful bits that I actually need to know.
I guess I could create an actual agent skill for this :) And next-gen models might eventually be trained to simplify their output themselves...
(sorry)
It seems like it doesn't have enough of a theory of mind to know that other people don't think exactly like it thinks.
ChatGPT told me its "semantic compression"
UART is a hardware circuit for communication, possibly a serial port. Were you trying to reverse engineer a consumer device or appliance?
This particular instance doesn’t seem terse, but I’m sure it has been on other occasions :)
> I told it to look online at some of Fable’s strongest feats, especially the math problems it has solved, and that something like this should be easy in comparison.
Wait. Wait wait wait. Are we supposed to be giving them pep talks?
I have not seen this in other models.
The LLM likely needs to be reminded of its abilities.
Modern AIs have very limited metaknowledge - they don't know exactly where the limits of their capabilities lie. So you can get things like "a task is doable for an AI, but the AI thinks it's impossible, so it doesn't try hard enough".
Usually you get the opposite - AI overconfidently trying at tasks it has no conceivable way of reliably solving, falling far short, and failing to self-check, fail gracefully and self-report the task as failed. But having piss poor metaknowledge cuts both ways!
So you can, in fact, get better performance sometimes by applying some variant of "assume this problem is solvable" or "other problems like this were already solved by AIs" pep talk. Not always, far from it, but it does happen on the occasion with frontier capabilities.
Are you superstitious?
Hmmm… this is giving me thought actually. Given the choice between that and the current administration where the goals of self destruction are strongly in evidence, it’s actually worth thinking about. At least. Let me get back to you :)
On a tangential note, I’m curious if researchers have started running virtual simulations, where sandboxed AIs are used as decision makers of key political and business positions?
Just a thought experiment, no one ever said the world was fair, and all history points to it
AI, being the super hungry energy monster it is right now, in my view accelerates this trend not reverses it. Even with renewables the need for reliable, stable power in a dense form (data centres use A LOT of power per sqm) means lots of land clearing, energy for construction, cooling/pumping, chip manufacturing and other uses. All want stable quick to deploy power due to the AI race (e.g. fossil fuels).
> we still have the same weather.
Oh.... So your local weather is now deciding the global temperature patterns, averages or temperature records being broken year on year?
OMG....
Then you realize it never really mattered and you reach enlightenment.
Really makes one think, if they try. Would need to ask Claude if there is some real middle ground here.
It makes us realize there are people who gets fed climate denying propaganda, simply because they're not yet going through it. And these people are like flat earthers, blind to see the reality lay beyond them in full view. Or worse sees the reality but ignores it
There's no both sides here. One side is staffed by scientists, the other by dictators and corporate lunatics.
We have it. We've had it for a long time. We've had several such technologies, take your pick: solar, nuclear, hydro, wind. The technology is not holding us back, politics, ignorance and greed are. I'm not at all hopeful AI will help us with any of those three very human flaws.
One can dream of dumb conspiracy theories.
It might take a couple of decades and a lot of reorganisation to build the capture facilities. But CO2 is not an unsolvable problem with current tech.
What's missing is the political and organisational intelligence to make it happen. Part of that is solving problems at planetary scale.
AI is the only tech that might - possibly, maybe, perhaps - have a chance of solving that problem without breaking anything critical.
We don't need a revolutionary technology. We need to experience immediate pain from reckless innovation so that we realize that innovation and tech is not the answer.
Technology only proceeds in one direction: unfettered growth, which necessitates unsustainable resource extraction. Your take is just your instinct for optimism, which in turn is just a trait that is only adaptive in primitive environments but is grossly misleading in a surplus-based society...
The direction of technological progress is not just linearly/exponentially upwards. Significant global technological fallbacks have happened, as in knowledge and processes disappearing for hundreds of years. This could happen again.
Even on the trajectory of unfettered growth fed by unsustainable resource extraction, tech and innovation might potentially take us beyond local pessima. That seems to be happening with solar, wind and batteries replacing inferior tech today. Still unfettered growth of energy production and consumption. Still fed by unsustainable resource extraction. Less harmful growth than the inferior tech being pushed out.
I expect datacenter load has a similar sort of day to day demand curve as everything else. Consider for example global bandwidth use during work hours versus in the evening when people get home and pull up a streaming service.
Of course you can use more flexible tasks to demand shift but the same applies to the electric grid.
That doesn't seem correct to me. There is always energy available that is not used because it is not cost-effective to do so. (Consider - the grass in your yard is not harvested and burnt for power). AI may yet turn out to be a paperclip maximiser, but humanity itself is not there yet.
I've been wondering what exactly the point is for being the meat proxy who pays for these things. I mean, obviously there's personal satisfaction and maybe some glory. And there's the fact that someone has to be the first to do a thing.
But I've been thinking about it like a sort of lazy loading of knowledge. AI has brought us to a new frontier for some amount of undiscovered knowledge. Do we discover it for the sake of discovering it? I think for the most part we've been lazy loaders: we discover all kinds of stuff when we need to. Whether it's a war or a space race or chasing wealth. Then again, there's all kinds of academics who do it for the sake of doing it.
Information propagation mechanisms are often seen as malicious before they're commonplace. To be fair sometimes they are, but by and large humanity has benefitted from increasing the number of bits of information we can consume on a per second basis.
It is a threat. We need to run.
It's the meat methane and cement CO2 that's now a big question.
We will hit 1TW per year of new solar soon, but to get to 100% electricity by the end of 2033 I think we would need closer to 3TW per year.
Or it is simply implies that most of decision‑making agents has formed a consensus that climate change isn't that big of a problem.
I still don’t know the answer.
Come for the AI doom, stay for the programming languages (remember those?) catching strays
That ability to create ad hoc tools makes up for a lot of shortfalls.
For example, I'm a nerd. I'm bad at baseball. I lack that kind of intelligence, even though it's more common than the ability to program. That doesn't also imply that you can't trust my Python code.
And yes, I've taught 8 year olds how to crack Caesar ciphers...
Recently I ran a bit of an "escape room" concept with some kids at a campground where I had a secret message that was Caesar ciphered, where we were handing out the letter/symbol combinations as prizes for completing the other challenges, and I made sure not to hand out the actual message until they were done collecting the keys because otherwise some clever clog would very likely have short-circuited the entire thing and worked it out without the key at all. I did dump all the letters I didn't use into the message into an "authorization code" at the end which in principle they could only have worked out which letters were in it but not the order, but still, that was not the intended route today.
I wonder how many of the recent results are due to the fact that very few looked at the problem to start with. Still great results, but the general impression is that it's more about the so many low-hanging fruits than the actual capability.
Now on to the Voynich Manuscript :)
That does not mean that specific instances of it are still very interesting though. This article is the "I had claude vibecode a thermostat for my bathtub" of cryptography.
* And in this case I'm not sure it even meets that bar. For all we know a couple readers back when the book released had a delightful afternoon with it, solved the riddle, then forgot about it.
More money than the GDP 90% of the sovereign countries around the world is hanging in the balance, and people are taking everything OpenAI and Anthropic are saying at face value as if this isn't the financial / marketing equivalent of war, assuming they they wouldn't use every legal and shady tactic, bending every truth available to them to sway the balance of public opinion in their favor. It makes me feel like I'm living in the twilight zone. People need to wake up.
Is that why you feel the need to share it with the class?
Given the close relationship between compression and intelligence, I'm somewhat surprised at how poorly the cutting edge models do with being concise.
For Earth, the proof presented for NS is just our first attempt navigating from our previously known facts to the proof.
I expect we will be able to shorten it dramatically (most likely with human and AI insights), but I don't think we should read too much into the length. If you want a similar point of comparison, see the original proof (by humans) of Fermat's last theorem. It has been shortened significantly. This is normal.
because they're not intelligent in the sense you're hinting at (conceptual integrity or generalization) but they are as the name suggests, large. Like comparing a forklift to a human. It's easier to bulldoze through a lot of things than tie your shoes.
If we weren't quite as impoverished conceptually and still had the vocabulary of the Catholics we'd recognize this as ratio (discursive knowledge) vs Intellectus (apprehending knowledge)
The successor to Klaus's blog is Satoshi Tomokiyo's Cryptiana site, so a month ago I asked Opus 5 to scrape it all, rank them and have a go at solving some. It didn't get the ranking right. But I knew the Civil War Stager ciphers were ripe for solving, so I had it do those https://cryptiana.blogspot.com/2026/09/route-transposition-c...
The art of solving historical unsolved ciphers is knowing what is on the boundary of solvability. Since this site attracts so many OpenAI and Anthropic employees, I'll mention one that was featured by both Klaus and Satoshi in 2023, presumably Spanish transposition, which should be on that boundary but has resisted all attempts at solution https://cryptiana.blogspot.com/2023/09/a-telegram-from-switz...
Also, that section is vague and doesn't explain the actual methodology.
The definition of solving a cipher must be something like getting a highly meaningful result (like intelligible natural language text) by applying a process with relatively low Kolmogorov complexity relative to the length of the output. If you don't have a constraint like that, it could literally be meaningless what should count as a solution. For example, a cipher that was encrypted under a one-time pad can be successfully decoded to any plaintext just by choosing the appropriate key; there's no reason to prefer any plaintext over any other unless you have external knowledge that constrains the plaintext and/or the key. (That's what it means for the one-time pad to be information-theoretically secure, which is the lack of a constraint that helps distinguish a "good" solution from a "bad" solution.)
Basically you could say that every cipher is a transformation of a plaintext with some kind of computer program. (The human who invented the cipher may not have thought of it as a computer program, perhaps because computers hadn't even been invented yet, but there should be an equivalent program to the encipherment and decipherment process.) A good solution in that Kolmogorov complexity sense is like "a short program produced a meaningful decryption". There are statistical methods to recognize some kinds of plaintext, and there are statistical methods to recognize properties of specific ciphers (for example, to guess the most likely length of a Vigenère key), but it doesn't seem that this can inherently generalize across "all possible programs".
But if you want to limit the family of ciphers to specific things like Vigenère or Playfair or something, then yes, there are good statistical tests. It's just that it creates a higher-order question of how much flexibility the cipher creator could have had to choose a cipher method, conceivably including one that isn't attested anywhere, or one that has more good security properties of some kind than other classical ciphers did.
It seems like this will intersect with historical research, like "well, I don't think that so-and-so was actually sophisticated enough to literally create an interesting new kind of cipher from scratch, so therefore if this is a real message, it's probably one of these methods that would have been known in that cultural environment at that time and place", which maybe is enough of a constraint to have decent statistical tests. But we still have some idiosyncratic things like the Voynich Manuscript where experts have been fighting for decades over the baseline question of whether it's actually an enciphered human language plaintext!
The worst case problem is not even an error in encipherment but the idea that the apparent ciphertext could literally be random (chosen by throwing dice or spinning a wheel or drawing letter tiles or something), so there's no form of meaningful decipherment possible by any means, even with the original creator's knowledge.
This cipher context "rhymes" well with Kryptos K4 in many ways.
In the same way if you tell an LLM to go and find an unsolved cipher it can solve, of course it finds the one it can solve out of the set of all possible ciphers. Of course it finds one that uses a one time pad that is public and referenced nearby in the text.
It's the same trick used by those people who film themselves throwing a basketball backwards into the hoop. You do it enough times and don't show the misses. You pick the best one to show. It makes it look like you're a basketball genius when you aren't.
It is of course, still a cool trick. Those videos are fun to watch, and so is an LLM solving a cipher. It is absolutely incredible to live in the timeline where you can tell a computer in plain language to go and find a puzzle on the internet and solve it, and it does exactly that. It's truly a mind boggling miracle.
The first principle is that we must not fool ourself, and ourselves are the easiest people to fool. (Ht Feynman)
>It looks impressive but that doesn't make it a good game, or the game anybody actually asked for.
The game I wrote manually hits 0/3.
Sounds more like brute forcing than intelligence, this time.
I don't think we can really call "trying lots of different ideas for an extended period" "brute-forcing," unless we use that term for lots of humans who have struggled with hard math problems for years.
I've been around for a few of these and I remember what was being said and written at the time. The after effect is very different to what was being predicted. Is it the same this time? Who knows. But the hype machine is at full power for this one.
Though I believe the core of his opinion hasn't changed so any video would tell you a similar thing or at least that's how I understood it. That LLMs, in the hands of an "expert", can enhance the way you work. Which is very different and a lot more realistic to what the current AI companies are saying(or were saying before they toned it down a bit for their IPOs).
Do you have a criterion that distinguishes between whatever you mean by those two respective terms?
Next thing you know, we'll have a WattsApp to help AIs connect and discuss.
Fascinating. I wonder if you could show "fake news" to a weaker model and get it to be more ambitious in its attempted solutions, even if it's not fundamentally any smarter.
EDIT: In 1939, George Dantzig was a graduate student at UC Berkeley studying under the statistician Jerzy Neyman. He arrived late to class one day, saw two problems written on the blackboard, assumed they were homework assignments, copied them down, and turned in solutions a few days later. He apologized for being late -- the problems had seemed "a little harder than usual."
software engineer -> prompt engineer -> positive affirmation engineerI have a plug-in to do this. I don't know if it's effective but Claude said it was genuinely helpful (obviously would say that about anything)
Pygmalion pandererI also don't find it on the site of "Klaus Schmeh" that it claims to be on a list of "Top 50 unsolved encrypted messages": https://klausschmeh.net/?s=Cyphral
Looks like the best source I can find is this: https://scienceblogs.de/klausis-krypto-kolumne/2014/11/17/we... which seems real-ish?
which links to: https://archive.org/details/s9notesqueries03londuoft/page/12...
which is in reference to the original proquiritations here: https://archive.org/details/worksofsirthomas00mait/page/416/...
i had also never heard of this before today and wonder if people had even seriously tried to decipher this at all?