> 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.

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.

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.

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....

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.

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.

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.

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.

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 :)

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.

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.

Obviously this is just survivorship bias/p-hacking/insert-other-buzzword but can't help but anthropomorphize it, it is hard for me to wrap my head around the idea that the same person who cannot produce code without 2 unrelated bugs both not present does this for someone else.

Imagine a math teacher struggling to understand what he is teaching casually solving a millennium problem, then go back to not understanding what he is teaching, doesn't happen in our world.

I am not confused by any of this, I am just trying to communicate an idea.

Remember when they said it didn't sound like Claude anymore

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 engineer

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)

    Pygmalion panderer

All of these breakthroughs are in verifiable brute force domains, and some of them are probably wrong because of a typo in a lean specification or just a base level axiom being incomplete.

I think the better the way to think about LLMs is like they are new substances, like when we first discovered clay or bronze, but confined to the digital realm. Previously we were chipping away at stones trying to make to things as close to useful as possible, then we found a step change. LLMs are like clay but they have their limitations. Wake me up when they are proposing new, { conjecture: interesting|useful|new } and not as a side effect of trying to get to a goal.

The Olympics exist because we want to see human skill, even though jet planes exist.

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?

He wrote the cipher, and then, upon hearing Charles II was Restored to the throne he laughed until he died. The cipher reads, "O GOD UPHOLD KING CHARLES THE SECOND AND MAKE HIM THE SUPREME RULER OF THIS LAND" and so he was laughing because he just made an excellent joke that he can't tell anyone about until someone figures it out.

Someone needs to add this to Wikipedia. It will be necessary to first convince an academic to make the claim so there's a reasonable citation.

Oh, and haha. It was a nice one, Thomas.

They published this on 31 aug and nobody in that community cared and no news covered how this 300+ years mystery was solved?

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.

And yes, it is just a next token predictor.

LLMs are a great search tool. It searches connections in the collective human knowledge that humans have written down through all the years....

They are very good at it, and that is about it.

You’re not really understanding how the tech works if you find it hard to comprehend.