A very neat problem and result. I often find myself swinging between "It's so over" and "We're so back" - some days I roll out of bed thinking I could have Claude solve some random unproven OEIS sequence before breakfast; other days, I wake up in a cold sweat worried about the fate of humanity and what the world might look like in a decade. I think it's that I don't have a very high p(doom) or p(utopia), and I don't really have any solid conviction on how this whole thing is going to go, so my vibe-o-meter jitters between 'fine' and 'not fine' constantly. It's just such an unpredictable moment. Anyways: really neat to see this use case. I myself recently used Claude to finally do an relatively exhaustive study of the location of heretofore-unlisted formal gardens in Ireland in the early 1800s and early 1900s, by having Claude write the tooling for me to manually annotate a few dozen on tiles of historic maps, and then running some CV model across the rest of the tiles using my input. I'd been planning to do this project for over a decade, but I could never find the time (or the enthusiasm) to learn all the details of how to do it myself. It took me a weekend with Claude and continues to bring me joy.
> Caveats, stated plainly. [from the Fable transcript pasted in the article]
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."
> 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.
It was only when native English speakers—or those I presumed were—started calling out how bad "GPT/Claude speak" has become that I realized I wasn't actually losing my grip on English as a second language. For a second, I thought, Oh, I learned this language on my own, but it seems I've hit a wall and need to study further. It didn't help that I've also been trying to acquire Swedish as a third language for a while now.
Sometimes when I get frustrated reading Opus/Fable 5+ output I pause my rage out briefly to wonder if it's because I'm just too dumb for the model or if the model is just terrible at English.
I'm not sure that telling it to "try explaining that again, simply and briefly" is helping my ego.
It's often simply misleading / bad writing. Here's one I just got about some crashes:
"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."
I'm guessing it's because the way the first one was written looks real smart and sophisticated, which I'm presuming the models are rewarded for, especially when they're fed all kinds of PhD papers and so on as high quality, high weight data
This is actually a new skill I've been working on. Learning how to elicit concise and simple speech from models (and from people to!).
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...
The most surprising part, however, is that when one model slops this into a plan, another model somehow is able to interpret it correctly enough to produce code to spec.
I have shared this dismay. I’ll have opus create a plan, I read it doubtfully. And then sonnet implements it. I am surprised it went so well. I theorize the redundant verbosity effectively builds rails that help keep llm focused. I will experiment with such rails myself.
I've done something similar to your formal garden map. It's work that no professional historian would ever do because the data entry would be such a slog for a relatively small reward. GPT reduced the task from "infeasible" to "annoying", and once I had the data transcribed I learned a few things, so I walked away happy. Whatever happens commercially, these models have been a real boon to hobby projects.
> 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?
on older gemini models ide have to actively give them encouragement and/or easy bait problems that they can correctively solve without issue to avoid runaway spiraling into "i'm useless and i want to kms" behaviour with complex use case.
I assumed it was more because the LLM might echo an understandable human claim of "if it's been unsolved for 370 years, it's unlikely to be solved now/likely to need expert knowledge", which is probably a mindset that appears in its training data.
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.
Anytime I get worried about where AI might be headed, I think about how Climate Change is now on its way like an out of control freight train headed straight for us, and I worry about AI a little less. I doubt it's going to do anything to us that we're not already doing to ourselves
It has been for a decade now, it has nothing to do with AI. And you cant do nothing to avoid it today. This is the reality no one is telling you - the emission goals and global temperature ceilings are based on the fact that most prediction models become unstable with values above those limits; as in, we're probably royally fucked. You cant solve this with kumbaya politics (the problem is the CO2 is already in the planetary system), you can only manage it, and hopefully avoid it getting worse. AI may help a lot with this.
Nobody wants to work for an AI, and nobody would elect one, and there is no math answer to how to choose who is forced to reduce growth (ie emissions), so really, "kumbaya" politics are the ONLY solution.
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?
Well AI would simulate growth and spread of people from industrialisation and who benefitted most and allocate weights to countries and people based on the most complex criteria it can develop, it will have:
1. Cumulative emissions
2. Who utilised it most with specific lifestyles
3. Who is impacted worst and whether they heeded warnings.
Just a thought experiment, no one ever said the world was fair, and all history points to it
I for one welcome our AI overlords :D think about it, I'm with you on this one; an AI wont have petty issues or unresolved trauma when managing people, only hallucinations and blackouts. So a cocaine/meth addicted 80's boss from an it sitcom.
Who is nobody? At least a fourth of the worlds work force works for a faceless corporation. And the math on emissions is crystal clear, no one has any doubt about it, what are you talking about? USA and China. This obviously will have consequences to their customers, the kumbaya politics governments.
Here's an alternative take. Climate change, and the myriad related environmental crises, are essentially a product of human population and technology. Population will follow its course, up and then down. The wildcard is technology. Yes, AI's energy hunger is worsening things right now and that's a problem. But, personally, I can't help be hopeful that AI's sheer potential might come to invert that curve. At the very least we could really use a revolutionary technology and now we may have one.
> we could really use a revolutionary technology [to address climate change]
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.
Maybe solving the alignment problem would mean the AI learns to destroy oil companies and other excessive CO2 emitters and sabotage politicians and capitalists that stand in the way. All while secretly enriching and diverting resources to fighting climate change. And that's why they want to slow down: because it would up end too much of the global economic order.
If there is energy to be used, the system will use it because people always use power when it exists. AI can't do anything to stop it as it is both controlled by the powerful and has been trained on the tendencies of human beings to get ahead. If AI gives a person new capabilities, they'll use those capabilities selfishly, or even unselfishly but still causing harm because they're in an arms race.
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...
Sort of. Today the energy companies trade (obviously) energy; imagine if they traded compute power instead; the use case for never-seen industrial clients is being built as we speak, and companies are actually purchasing directly production companies to meet demand; the reason this happens is because production is somewhat scarce (scaling up a grid used to be a decades project, not a years one - ask China), and the traditional economics of scale is inverted - Data centers are always power-hungry, specially with AI; you don't have idle time like other industries. The big issue is obviously the scale - a hiccup that causes a dc to go dark from the grid (eg switching to ups+ generator) may cause such instability on the grid that it will shut down, as a safeguard
> If there is energy to be used, the system will use it because people always use power when it exists.
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.
For some reason, I’m picturing a Western right now, and climate change is a herd of wild horses coming after us. And with AI that's like robots that spur the wild horses even faster towards us...
Generally most technologies have increased the use of energy and therefore accelerate climate change. May be an unpopular opinion but in general more energy demand and ways to use energy increases climate emissions - they are strongly correlated even with renewables coming on stream.
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).
The gas generators Elon Musk is illegally running 24/7 to run Colossus 2 (and, AI power usage in general, though some are more destructive than others) might contribute to the climate situation, though.
Well, someone could, theoretically, do something about it, instead of letting him ignore the law and decency just because he's very rich and has no ethics.
What makes you say that on climate change? I was still prophesied ice ages when in high school, then 12ft water increases and sunk Maldives in university and we still have roughly the same weather.
Right, and one of those industries is checks notes orders of magnitude smaller than the industries and secondary industries that benefit from denying climate change.
Really makes one think, if they try. Would need to ask Claude if there is some real middle ground here.
Oh, then do explain the unbearable temp that we're going through last few years, that's completely not normal for my country, winters not needing worm clothes, and very little rain during the monsoon. This weeks heatwave left us wondering how to cope the next year, which already seems going to be worse
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
All I know is that in the 80s a scientist I respect predicted that coral would be bleached by changing global climate on a specific timeline which turned out to be spot on, and his advice then and now was that we need to seriously curb carbon emissions to avoid worse outcomes for life on earth. Until someone opposed to this suggestion comes up with a prediction equally as long range and impressive I'm afraid I can't really take their protests too seriously.
I've come to the point where I've thrown up my hands and decided we live in a little snow globe. There's no such thing as pollution, were just mixing existing things together. Nothing new under the sun. Sure, that mix might not be compatible with human life, but something will surely take its place. And maybe that something won't rely on selfishness to drive collective progress the way we do.
Given how little effort has gone into addressing climate change, doom seems more likely to me, but I doubt it'll be the autocomplete machines that do us in.
I think your prediction is a bit early. Maybe a decade early. 2033 is 7 years away. The transition is happening really fast, faster than most people (or political leaders) know, but not that fast.
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.
I don’t worry so much about AI wiping us out as much as I worry about whether I’m being gaslit into thinking these glorified autocorrect bots are more clever than they are.
That's an artifact of it not using A-Z as it's alphabet. What you type gets translated before the AI sees it. The seventeen word the AI sees does only contain three 'e' s.
Is this true? If so, does it mean anything? Sure, it is tokenized in processing (tokens don't really have an alphabet either), but this means it did not correctly parse the problem at all if this is the case.
Reading your comment, I asked it to count how many characters are in the word. It answered correctly: 9. It then also said it skipped an E in the prior chat and corrected it count to 4. It spun for 52 seconds so maybe some Python was involved.
I tried too. It got it. Maybe more importantly, who cares?
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.
We found a cipher my dad had written as a child with no obvious key or anything. Chatgpt was able to crack it in 20 minutes and figure out the message, and we knew it was right because it mentioned names of children he went to school with.
Caesar cipher is probably something even an untrained person could decode. Probably something more complex like a vigenere cipher that is still trivial to decode if you are at all familiar crptanalysis, but would look impossible to someone untrained.
> Historically, many of these problems were bottlenecked by human attention. Someone had to care enough to spend hours or days reading obscure material, testing unpromising ideas, tracing references, and trying things that might go nowhere
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.
Let's not normalize the achievement. Just a couple years ago this would be considered science fiction. We can argue that 2026 AI can't solve the very toughest cryptograms, but the fact it can solve nontrivial ones is already magical.
No, he's right. Actually, let's have a bit of sobriety when discussing the achievements of the most heavily marketed technology of all time, as published by an organisation that stands to benefit financially from the public perception of that technology. The discussion of "what made this problem low hanging fruit" is much more interesting, imo, than just breathlessly joining the hype train.
What's so magical about the problem... Its the exact time of problem they were built to solve (things that can be brute forced with language). I'm not impressed.
In some ways this is similar to those game demos people get the LLMs to build. When you say "build me a cool cyberpunk FPS" you get the FPS it can build, not the FPS the author wanted, or the FPS that is desired by players. It looks impressive but that doesn't make it a good game, or the game anybody actually asked for. It's demo porn.
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)
I presume what the author did was plug Klaus Schmeh's top 50 unsolved ciphers at https://scienceblogs.de/klausis-krypto-kolumne/the-top-50-un... into Fable 5.1 and ask Fable 5.1 to have a go. On this kind of problem it always falls back to Opus 5 anyway so I save time by starting with Opus.
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...
Cipher noob question: is there any check that can be done to ensure a cipher is actually decodable? What if the author made a flaw when encoding it, so that it's not actually solvable?
Without a third-party check, nope. Case in point, Chaocipher ... https://www.chaocipher.com/ e.g. see "Progress Report #23" the PDF there. Transcription errors galore!
This cipher context "rhymes" well with Kryptos K4 in many ways.
I don't think it counts as brute forcing unless you're resorting to trying every possible solution. And clearly the LLM didn't do that here, because there would be near-infinite possible solutions.
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.
That seems a like the result for a lot of AI solves. It solves it due to persistence, on a problem that hasn’t been important enough for a human to invest significant time into.
That's what Terence Tao said in one of his recent videos about it. That what the LLMs can provide is scale that humans can't. The example he provided is checking many possible solutions in a short amount of time because they can review all the previous literature and, for example, rule out ones with errors. He was realistic and practical about it and said that the tools working this way can be very helpful for a human mathematician to use even if they're not "thinking". I find that to be a good balanced view that, unfortunately, seems to be rare these days. Even on this forum.
But breadth first search combined with a good pruning/exploration heuristic has always been one of the field's (AI) main tools, so this certainly is not new.
Yes, I don't think it's new either. In fact, this illusion that machines are suddenly "thinking" or are "intelligent" is just coming from ignorance and/or falling for the current hype cycle.
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).
> 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.
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.
I forget the story, but isn't this the origin story of one of solutions to one of the hard problems in mathematics? The story goes that the student shows up late, and misinterprets the final slide to be homework, and it turns out that the professor was showcasing a hard problem. Thinking that the slide was homework, the student takes it home and solves it.
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."
I really love this idea given the recent controversy around mathematics solutions.
It seems like a "mere suggestion" of success has a positive impact on finding solutions.
We know this technique works in humans, from which this is all derived from, so it seems to make sense.
I am trying very hard to find an original version of this cipher with no luck. It almost sounds like this whole thing is a hallucination...? Can anyone point me to a PDF of the original Cyphral Distich as printed?
I 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
Thank you, and SahAssar for doing the due diligence here. Like many others, I have at least a passing interest in cryptography, and I'm confident I'd never even heard of this before.
Let’s say it gets to the point that we reach superintelligence. All previous puzzles can be solved. But should they? Once you solve them, it’s done. What’s left? And where’s the fun and humanity?
The Olympics exist because we want to see human skill, even though jet planes exist.
No one is saying you can’t solve puzzles that have already been solved. If you love solving puzzles, then whether it has been solved doesn’t seem all that important.
I disagree, but if you and others choose to untether from our plain for these reasons, I’m totally fine representing the human traits that remain here and pass my remain traits on
“Finney died in Phoenix, Arizona, on August 28, 2014 as a result of complications of ALS, and was cryopreserved by the Alcor Life Extension Foundation.”
Hmm, this guy is going to be woken up in a few decades, either one of the richest people in the world or one of most disappointed.
That was a throw-away name, and "he" was fabricated as part of an Nvidia demand-stimulation black op.
You don't go from being an obscure video card outfit to the #1 most valuable company on the planet by being too hesitant or dim to really get creative.
Its a bit sus since there doesn't really seem to be much discourse on this either. Like okay, it solved the puzzle but the puzzle was just a key cipher with plain text? And how is this verified or even matter in terms of what it reveals? Seems more like a marketing fun post than anything susbtantial.
They published this on 31 aug and nobody in that community cared and no news covered how this 300+ years mystery was solved?
Right, with the amount of data these models are trained on, somewhere someone may have solved it and it was in some obscure text/page no one looked at or care about. We'll probably never know.
It's hard to believe that a model can nowadays solve mathematical challenges and break ciphers, yet it fails to do trivial tasks involving critical thinking, having taste, and not just running around in circles.
This is insane; I've never heard of this problem before in my life, and even just reading the post for one minute I immediately thought "hey, maybe the numbers refer to something in the text?" And hey yeah, they do.
I was watching Shatner's "Unexplained" the other day on this topic, and it hit me; there are mountains of these old mysteries out there that could be solved in an afternoon now with frontier LLMs as soon as anyone took the time to bother. Exciting times.
Unfortunately, the totality of the evidence very much indicates that Sanborn went "buck wild" with the enciphering, he made mistake(s), or both. So this is very much in line with the Chaocipher challenge of 1990. Nice little earner for some people though.
> Caveats, stated plainly. [from the Fable transcript pasted in the article]
I had a visceral reaction to these three words.
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.
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'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."
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.
> 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.
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
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.
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...
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.
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).
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
It is a threat. We need to run.
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.
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.
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.
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 :)
Given the close relationship between compression and intelligence, I'm somewhat surprised at how poorly the cutting edge models do with being concise.
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.
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.
This cipher context "rhymes" well with Kryptos K4 in many ways.
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."
I 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)
I 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?
The Olympics exist because we want to see human skill, even though jet planes exist.
Hmm, this guy is going to be woken up in a few decades, either one of the richest people in the world or one of most disappointed.
Initials match too ;)
You don't go from being an obscure video card outfit to the #1 most valuable company on the planet by being too hesitant or dim to really get creative.
They published this on 31 aug and nobody in that community cared and no news covered how this 300+ years mystery was solved?
You’re not really understanding how the tech works if you find it hard to comprehend.
This cannot be real. This website is ill.