It's a shame that I have to run a local model to decipher Opus, but them "dumber" models read far more naturally - https://github.com/gvzdv/claudish-to-english

Astra told me yesterday:

> 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.

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 have not seen this in other models.

It won't be necessary in a year when the information "AI is superhuman" in all its guises enters the training data.

Sometimes!

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.

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.

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.

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.

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.

[citation needed]

Four sail: the story is clearly about the Olivebank (née Caledonia), a four-masted barque that hit a mine and sunk in the North Sea in 1939.

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.

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.

It's good at poking holes at my galaxy brained newfangled ideas for ciphers too. I thought I had something good, pasted the ciphertext and got a "it was embarrassingly simple..."

"AI solves niche thing you've never heard of" is a daily headline at this point. What's genuinely cool isn't that AI managed to solve some specific problem only a handful of people even cared about, it's that humanity can now cheaply clean up its backlog of such things.*

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.

Someone wrote a prompt, that included instructions for finding the problem itself and got handed a solution by a machine trained on all available text. I don’t see any achievement for the prompter. As for the machine, we can’t keep being perpetually shocked 24x7. It’s tiring (unless if we’re being paid for it)

It is indeed absolutely incredible that it can solve these puzzles given plaintext instructions with very little context.

I’m pretty sure the Beale ciphers are a hoax, but I’d love to be proven wrong.

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.

You know, the first time you navigate somewhere (if you don't already have perfect directions) will probably be the longest route you'll ever take to get there

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.

>I'm somewhat surprised at how poorly the cutting edge models do with being concise.

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)

This appears to be an euphemism for "prompting".

Also, that section is vague and doesn't explain the actual methodology.

My intuition is no, the family of cipher methods (even those that could be implemented by hand) is too open-ended, so there's no particular statistic that you could expect to see for all solvable ciphers and no unsolvable ciphers.

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.

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.

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.

Power (Watts).

https://github.com/stbenjam/skills/tree/main/plugins/hype

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)

-> AI Morale, Welfare and Recreation Officer (let's be real here, heh)

    Pygmalion panderer

Is it wrong to presume they tried to run a similar prompt on all ciphers that come before this one in search results, and this was the only one that worked?

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.

Conversely, the cipher could be so boring that no one in any academic circle bothered publishing on it.

Haha - I'm just seriously wondering, how can anyone tell at this point?

“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.

imho it is https://en.wikipedia.org/wiki/Nick_Szabo

Initials match too ;)

This is one of the best conspiracies I've ever heard...

Sure, but it is a token predictor, and it is not intelligent not because it works by predicting a token, but it shows dumb behavior...

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.

The article mentions it.