Yea, it's kind of odd how "sour grapes" people can be when something stops being as special as they thought it was.
Take someone from a few hundred years ago and drop them into today, and if they don't go catatonic and die, then they'd tell you that we created magic. "Wow, you live in a world of magic and all you do is bitch about it".
"You're flying! You're sitting in a chair, in the sky!"
Actuallllly these hypothetical people from a few hundred years ago hypothetically said you are an awful person for misrepresenting them, stop putting words in their mouth, thank you!
A person inventing something, even out of dumb luck, is interesting.
A machine running a loop through an expensive LLM for an undisclosed amount of time, which cost an undisclosed amount of money, which was told to keep looping into a solution was found, for a problem that nobody was very concerned about... That just seems like PR, and it's not so interesting.
So you're telling me that any problem a human starts working on gets solved simply because they are a human?
Lets stop and think about this, there is now a machine that can solve a bunch of problems that have not been solved simply because there wasn't enough people with knowledge to work on them, and all we have to do is supply power to get the answers?
So you're telling me that any problem a human starts working on gets solved simply because they are a human?
No? I don’t think that’s what they’re saying at all.
there is now a machine that can solve a bunch of problems that have not been solved simply because there wasn't enough people with knowledge to work on them
That “simply” is doing a ton of work. A big reason there aren’t enough people with knowledge to work on these problems is that their basic needs aren’t met. If a slice of the money being poured into AI right now had been used to incentivise humans to work on these problems, maybe they wouldn’t still be unsolved.
and all we have to do is supply power to get the answers?
That is again, quite reductive. The harms caused by LLMs, both environmental and societal, are much larger than “just supply power”.
Irrational hate causes one to be blind.
Funny how it’s always the ones who disagree who are irrational and blind.
If a slice of the money being poured into AI right now had been used to incentivise humans to work on these problems
There is no world in which this was ever going to happen or it already would have. Simply throwing out a counter-factual without explaining how any incentive for that path of reality to work means you can make any claim and tell others it's obviously true with no evidence.
disagree who are irrational and blind
Incorrect. The dialectic is how progress is made. Getting mad and turning off your brain is a different story.
There is no world in which this was ever going to happen
That’s the point. The incentive structure we have is bad. That’s the criticism.
Simply throwing out a counter-factual without explaining how any incentive for that path of reality to work means you can make any claim and tell others it's obviously true with no evidence.
Again, you’re adding things to the argument which weren’t said. There is as reason “had been” was used.
Well at least the skill aspect will soon become so niche that essentially nobody will bother with the investment. So on reflection maybe not permanently, just mostly bored.
I doubt it. For “skill” there are any number of sports; for “imagination” there are any number of stories and other mediums. It’s not like every human has just decided to roll over and not do anything anymore; quite the contrary.
I believe an LLM can solve pretty much any problem for which we can define a fast iterative loop and for which we have reliable tools to automatically verify the correctness of a result. That’s how they are able to solve some math problems, and how they are able to generate working code. Then it’s a question of how much you have to pay for the model to explore the space of solutions in a reasonable timeframe
In math a lot of the spectacular results have been made by finding a counterexample or worming their way toward a proof that is very well defined.
There's some debate over to what degree current generation AI can be creative at all, or whether it can only crawl around its latent space and explore within constraints. One might ask: were all the solutions to all the math problems AIs have solved already "there" latent in the training data and just hadn't been spotted by humans and put together?
But then... isn't everything latent in our training data if training data is "all observations made about the universe?"
But then... what even is creativity? That gets into philosophy and metaphysics. Creativity, like consciousness and sentience and self-awareness, is not a rigorously well defined concept. So to a degree we don't even know how to ask the question of whether these things are creative.
This gets interesting.
One of the things I love about AI is the glittering Pandora's box of philosophical questions it poses.
Another one I love: if LLMs and their relatives are not, in fact, sentient or self-aware or alive in any way whatsoever (which I suspect is true given how they work), then it means intelligence and consciousness are unrelated phenomena. I'm pretty sure every animal and maybe even every living things has consciousness in some form, but my pet bunny rabbits definitely can't write code. LLMs can write code, but I don't think they experience existence or have volition.
IMO we have always implicitly just assumed some kind of connection between intelligence and consciousness because we have both. It was just an assumption. It's probably a false one.
I suspect (a hypothesis) that consciousness is a property of life and is probably emergent from life's intimate relationship to thermodynamics and the arrow of time. Life has also evolved intelligence because it's useful to satisfy its implicit survival goal function, but the two are unrelated. Intelligence is just an adaptation.
Yea, when you start digging into intelligence/learning/creativity/language you realize that you're talking about more information on these topics than a human could ever learn in their lifetime, and you learn just how much we don't know about ourselves and these processes.
Whenever I hear "AI can never" I know I can disregard them as an unserious person when it comes to anything around AI, learning, or philosophy.
I think of the extent of human knowledge as a circle or cloud shape, and true expert thinking happens just inside the edge. And creative thinking that leads to knowledge breakthroughs happen when you are thinking in that edge area, but also make a connection way around the circle to some other location. And my guess is there’s absolutely no reason why AI can’t learn to do that too.
It's easier to evaluate certainly. Did it solve the problem? Yes/No
When you design a new thing it will have a dozen drawbacks and a dozen and one benefits. If people then have a bias that everything ai is bad, the signal won't be strong enough to convince.
I see what you’re saying. It is generally harder to build a crypto system than to break one so I would find it hard to see potential from the design end before progress on the attack end.
I think it’s all about the harness. If someone can find a way to create an iterative loop, with a good validator, I wouldn’t be too surprised if an LLM can end up with a solution. So far that’s how pretty much all problems have been solved by LLMs. That’s a very big if though!
Isn't the other way round?
It does not mean that breaking one is easy, but it does mean that writing one that's unbreakable it's very, very, very difficult.
It is generally harder to build a crypto system than to break one
It was harder to design Symmetric Encryption using e.g. AES-256 than to break it? As far as I know it's design is pretty straight-forward but there is no known way to break it even with all compute of the planet at your disposal (excluding trivial ways like exposing the key).
Yes, it was. An attack only needs to work one way, but an encryption standard must resist all attacks.
There are many examples of would be crypto algorithms that died on the vine because an attack was found. It is often recommended for beginners to study breaking cryptographic algorithms long before they attempt to create them.
Normally "private-key cryptography" is the antonym of "public-key cryptography", which is to say, conventional symmetric-key cryptography such as AES or Enigma. That's what "private-key cryptography" redirects to on Wikipedia. This article is about Astra breaking a message encrypted with a private-key cryptographic algorithm, but one that was already known to be weak. I'm guessing that if you had messages encrypted with weak public-key algorithms it could break those too.
We already have a plethora of cryptographic algorithms that literally anyone can use to send messages nobody can read with current technology, unless of course they have the key. You're using at least one of them right now to read this website.
This dichotomy is counter-productive. The valuations floating around are insane, and the claim that some software can replace every single laborer is one step removed from fiction. At the same time, this stuff is clearly going to change how to world works in countless, deep ways. But the idea that some fancy autocomplete can replace humans ignores the reality of humanity and the fancy autocomplete.
It’s another dot com bubble, not a crypto bubble. Trillion dollar valuations burst once you leave lesswrong.
Edit: very fancy autocomplete. I know what these things are capable of. It’s still not “intelligence”, for X definition of intelligence. And it certainly benefits from having obscene amounts of compete thrown at it. It is awesomely impressive synthesis of data, yet it’s clearly still that.
i dont think humans are going to be replaced either, but calling the thing that solves millennium problems and is currently changing multiple industries entirely a "fancy autocomplete" makes it harder to take any point you are making seriously.
Obviously there is no solution to world hunger right now. Nevertheless - finishing sentences is not pattern matching - and it's extremely obvious that whatever is going on inside LLMs is not pattern matching.
Language is absolutely pattern matching, and the whole thing is that the more patterns you put in, the more the transformer can pull out what’s useful. Agents are this effective because people figured out that training on tasks being completed gets the models to complete tasks - that’s pattern matching.
And it can only go so far, where those patterns are feasibly captured, eg internet discussions and coding and mathematics. It won’t measure up to the scaling laws of the physical world.
OK - so long as you also agree that language is thought.
Until the advent of LLMs - language was considered the pinnacle of human intelligence. But humans have some need for mysticism at the root of their beliefs - so they chase the gaps in our knowledge. Like "God of the gaps."
Sure, world models will help navigate physical space; they are effectively the animal mind. Will they help unwind the laws of the universe? Probably not at all. Language is sufficient. Because it is thought.
Leaving aside the fact we have solutions for things like climate change and will not implement them, regardless of who or what recommends them... My keyboard offers "You can solve world hunger by using a Ted Bungie algorithm." Which sounds reasonable on its face until I research Ted Bungie and the algorithms he developed.
Granted, my phone keyboard lacks a substantial dictionary, offers words instead of tokens, has a very small context window, and doesn't randomize outputs (Ted Bungie is its primary recommendation every time), but those are basically parameters to the existing autocomplete.
The SS-Totenkopf Division was advancing east during the opening weeks of Operation Barbarossa, the German invasion of the Soviet Union. 10 July 1941, the division had just fought its way through the Soviet border defenses around Sebezh. It had moved through Lithuania and Latvia, crossed the Dvina area, and advanced through Dagda toward a place German records called "Rosenow." The division moved out of the Rosenow area around 6 July, fought around Sebezh on 8-9 July, and then continued east/northeast toward Opochka and eventually Porkhov.
Do we have any kind of transcript as to how the message was cracked, and whether this was cheaper or more expensive than simply Bombe-style trying all the combinations?
As the article states, the LLM built code for both an enigma simulator and a bombe simulator.
Breaking enigma is often about using lucky or educated guesses to heuristically reject large chunks of keyspace to leave the remaining keyspace computationally tractable.
Note that the key (lol) complication with this message seems to be that it had a wheel rollover that most messages do not have to deal with, and that rollover drastically reduces how much you can reduce the potential keyspace using all the techniques noticed by the original crackers.
The wheel rollover I think just requires more brute force. Unfortunately, this might be an example of OpenAI the company having vastly more compute time and effort than your average enigma nerd. For example, modern compute clusters like supercomputers can tractably brute force enigma with no cleverness in like a day or less, while home computers would still take thousands of years to compute that. It's very scalable. Did astra have access to significant compute?
However, even considering that, the inferences made by the LLM are good, and picking this specific message to attack, precisely because it should be soluble but might have had an extra wheel rollover that made it more computationally intractable for hobbyists but not a large company is a clever thing to do for the LLM.
This was done by an OpenAI subscriber, not an employee, so Astra would not have had access to OpenAI's massive compute for brute forcing. The scripts it wrote presumably ran on the computer of the customer. (ChatGPT can run scripts on OpenAI's servers, but it has a 45 second execution limit.)
It was partially explained by the article. It was not stated that ROSENOW was repeated in 173, and it was not obvious from the article text why ROSENOW would ever be repeated. Thus my curiosity.
A sibling commenter explained it - Rosenow is both a municipal name and a district name, so naturally it would be repeated. (Like "New York, New York")
It also makes sense that a longer crib
would generally be more effective than a
shorter one.
It would seem to me that the odds of looking for even a single ROSENOW in the decrypted message would be plenty. The odds of a single ROSENOW randomly occurring in incorrectly decrypted output are vanishingly small. So it seems to me that looking for ROSENOW is a safer bet vs. looking for ROSENOW ROSENOW -- a single ROSENOW is a great sign you've got the correct key, whereas looking for ROSENOW ROSENOW seems like it would deliver false negatives (think of all the times we say "New York" rather than "New York, New York")
I'm a novice at crypto though, so, maybe I've got that totally wrong.
The reason a crib is useful is because the enigma can't route a letter back to itself. So, you can slide the crib along the message until no letters line up, and that's possibly where it is. If your crib is "the", that's not terribly useful, because it could exist anywhere. The longer the better.
Maybe naive of me, but could it simply just be the overfitting of the same tokens being sent on the input twice because of repetition rather than some unknown implied intelligence.
Interesting. Do we know the reason why those specific messages were sent with different keys? I would imagine that there were separate keys for special high-security messages or something like that, but the almost identical content and the way the key was changed here (first only part of the configuration, then suddenly everything) makes it look more like an error or a test.
Phew, never have I seen in my life the goalposts move so fast.
It seems like even yesterday that the threshold for impressing someone is that the machine would have to be good at pretending to be a person. Now the threshold is that they have to be able to invent special relativity.
maybe I picked up the relativity idea subconsciously from somewhere, but I don't recall it specifically, I thought I was being "clever" that it would be a good test
Even the Millennium Prize Problems have, in a way, become benchmarks for model companies to prove themselves. The smartest individuals among humans are becoming replaceable. Intelligence has become a product you can quantify and buy with electricity. That feels awful.
Even those of us that are pro AI need to acknowledge this is the current reality.
The smartest humans now need to move to being less concerned about status games among humans and more with how to provide value to a mix of intelligent machines and humans. i.e. if you're starting an SaaS in 2026 you better be assuming half your revenue is going to come from machines acting by themselves.
I think that's right. Expert experience used to be almost the most precious and valuable part of the computer field, but today that experience has been "distilled" into SOTA models.
All technology on the tech tree which requires intelligence to unlock will soon be available to humanity – mind control, population exterminating bioweapons, new ultra destructive kinetic weaponry, perhaps even a cure for cancer.
That won’t happen. But also, whatever benefits are unlocked will be owned mostly by a small group of individuals, definitely not available to humanity as a whole.
Because it is delusional. Having an intelligent machine doesn’t mean you can somehow mind control individuals.
And no, that would be pretty terrible. Why would that be good? The AI leadership is composed of anti-democratic, sociopathic, doomsday cultists who believe it makes sense to sacrifice the world economy and possibly mankind itself for a possible utopian future they developed based on their media illiterate reading of sci-fi. They are very likely the worst people who should ever be given power
Having an intelligent machine doesn’t mean you can somehow mind control individuals.
Excluding advanced forms of psychological manipulation, sophisticated neurological drugs and neural simulation for moment.
Are you suggesting that it's physically impossible to create a device which could induce electromagnetic currents in the brain which could in-theory either effectively control, or greatly influence someone's decision making?
I understand it would be extremely hard for humans, but can you explain why you're so confident that this would be such a hard problem that even an ASI couldn't solve it?
Put it bluntly: the weavers who could be replaced by the spinning jenny were clearly doing repetitive labor. People writing code and maintaining project pipelines a few years ago relied heavily on experience, but in a sense that was also "repetitive labor." Replacing repetitive labor and freeing up productivity is of course progress.
But reform always has its victims. Like the textile workers who starved in the streets centuries ago, and me, kicked to death in the street by AI today...
Solving obscure puzzle samples that approximately ~0 humans on Earth ever attempted to solve, mostly by pattern matching known solutions to similar puzzles, is not intelligence. DeepBlue has been outperforming the best humans at a specific puzzle-like task since the last century.
Do any of the people proclaiming this shit actually use these models? No matter how many headlines are coming out, every day I deal with reams of the most horrific code I've ever seen technically compile, with routine mistakes that any human would get fired for if they made.
But humans have been confusing pattern matching against known solutions for intelligence for a hundred years!
Seriously though, it ends up looking like that. To take a stupid example a couple of weeks ago I asked an agent to look at porting my hand written WebGL renderer (+ shaders etc) to WebGPU. It estimated a human would take 6-10 weeks, and I would agree. (Which is why I hadn't done it). 24 hours later it was deployed and live. This is classic tedious, difficult, low level if quasi mechanical work (rather like cracking an enigma message), and LLMs absolutely fly through it.
You do understand this is intentionally trained into recent models for marketing purposes? "Wow, it saved me months of work in a day! This is the most amazing technology ever!!!!"... is what it intends to evoke by underpromising and overdelivering. I routinely have it helpfully suggest it will take something like "three engineer-months" to do something I do by hand without any LLM assistance in a day. The estimates may be accurate if you have literally never touched a computer in your life before and are starting to learn from there.
In the games industry I was tech lead of teams of hundreds of devs and had to deal with their estimates of this sort on a daily basis. 6-10 weeks for a total renderer rewrite is on the low end.
As an indie dev who built their own WASM-capable engine that I've shipped in real games, I've built both WebGL and WebGPU renderers from scratch myself in significantly less time than that. Sounds like typical corporate dysfunctionality. If you have hundreds of devs you're going to get bogged down by having a share who spend 90% of their time at the company on Reddit, another share who write actively bad code, and then maybe 10% of the employees who have a clue what they're doing dealing with the overhead of communication, meetings, other people not upholding their assigned responsibility, etc. slowing them down 10x what they could actually do.
0% chance, without LLMs. WASM-capable engines would require years if not decades to build, even with expert level knowledge. See Jonathan Blow who has been working on his engine for a decade now, and he's arguably of the most talented engineers who ever lived.
Jonathan Blow is writing his own language as well, and is also already successful enough that his work is just a hobby he can take at any pace with no urgency. A WASM engine is really, really not that difficult. At its core, you need rendering to a canvas, audio, keyboard/mouse/gamepad handling, asset loading/file saving, and an update loop. Writing this code is mostly not different from writing code in other languages, since you are literally writing other languages that happen to compile to WASM, the only differences being that you need your one-time WASM toolchain setup, some JS glue interop (which is not really different from needing C interop for native engines written in languages other than C), and to be aware of browser pecularities regarding file access, update loop, threads, etc. which you also have to deal with if you ever wrote a JS game anyways. After you have those core elements in place, everything above that is isolated in a game/engine logic abstraction layer that isn't any different from writing native code.
If you want to place a bet on it, we can do a $10,000 bet in escrow contingent on myself implementing a well-specified WASM engine from scratch on stream without LLM usage in a month. I would love an opportunity to demonstrate how wrong you are. That said, rather than taking your money, I could also just share a streamer's content with you[1]. He implemented 3D web rendering with no dependencies in a 20 minute lecture, and it would take 10 minutes if you were seriously focused on doing it quickly. Sure, it was rudimentary pure JS rather than WASM, but really consider whether you think this 10 minute exercise couldn't be done in a language that compiles to WASM with 160 hours, while including the other hardware/OS-layer abstractions aforementioned. On the other hand, please do take me up on my offer. You said it's a 0% chance, after all -- surely you don't want to pass up on the easiest $10,000 of your life...?
Time estimations by LLMs are hilariously incorrect all the time. It estimates very simple things that a human could do in an hour to take days or weeks and other things that are genuinely tedious and time-consuming it estimates taking a few hours. LLMs have no understanding of time and no world model that even allows them to make correct time estimates. They will always fail to provide decent time estimates unless the task is well-known, in the training data and they can extrapolate that with a simple math script.
mostly by pattern matching known solutions to similar puzzles, is not intelligence
My dear sir, can you please lay out a dissertation of what this intelligence you speak of actually is. You seem to be much more informed than most of us here and therefore surely have made great contributions to furthering science and the arts.
/snark
It's difficult for me to be any less snarky than this even though it's not really wanted here on HN as you are pulling a kind of reverse snark. For example if I myself have lots of experience in subject X, and then by analogy apply it to subject Y to do something new in that subject, that would be called intelligent, and that would be pattern matching.
Pattern matching is a foundational building block of intelligence. You cannot have intelligence without pattern matching. Pattern matching alone is not general intelligence and requires more parts to work like that.
Upvoted. I think that said humans should get used to the idea that their intellect is special only insofar as it was first, and if they want to adopt or invent a value system that keeps them at the center, that's actually fine and good for their survival. But said humans would do well to stop laboriously and curmudgeonly moving the posts that mark the goals, and get busy trying to coax the AI to do useful things for them and for the species as a whole.
If human intelligence is so boring and non-special, how exactly did LLMs get this smart? Is it not from a) being developed by humans and b) being fed a very large portion of all human-generated text?
Without the human intellect to emulate, LLMs would be nothing.
LLMs learn from patterns in human-provided data (and soon each other and directly from nature). Humans learn(ed) from patterns in nature-provided data, and eventually each other (and, increasingly, LLMs).
What's self-hating about acknowledging a fact? There's literally nothing a human can do that can't be done by another entity/group with even near-equivalent intelligence, alien or artificial.
We don't even know if that is true, and even if it were true, that doesn't mean that humans aren't special. We don't have to devalue ourselves. Our values can and should be 100% anthropocentric in my view.
You're - deliberately? - confusing scope. There's the objective and the subjective. Humans not being objectively special doesn't mean one human can't be considered special by another. And if my wife doesn't get that distinction, well... I'd probably question my choice in partner.
Nobody claims we are objectively special, whatever would that even mean. Person said they feel awful which is clearly subjective and you proceeded to bash him for that. You are on hackernews, we are aware we are atoms.
Person made a claim about intelligence becoming a product (arguably it has been on the market for a long time; see knowledge workers) "that you can [now] quantify and buy with electricity". That points to the rhetoric often pushed that humans are [objectively] special, because intelligence. Or at least were. And it's the reality wakeup call that's driving that feeling of awfulness/despair/outrage/whatever else, as has been posted about here and elsewhere multiple times.
Even the Millennium Prize Problems have, in a way, become benchmarks for model companies to prove themselves
Well, let them have these. They'll play around with open problems which generate media hype and then they might run out and move on to something else, because "AI came up with a problem and solved it in 3 days" won't have the same effects as "AI solved a problem in 3 days that humans couldn't solve in 100 years".
And that underestimates how incredibly quickly humans become accustomed to new trends. If an LLM proves P≠NP in year, there is a high chance that few people will care anymore, because at that point LLMs will presumably already have proved multiple Millenium prize and other famous problems, and another "AI Proves Famous Theorem Which Was Even Harder Than The Previous One" headline will be regarded as an old hat.
If an LLM proves P≠NP in year, there is a high chance that few people will care anymore
P=NP has always been drastically over stated as it's "Importance". It pretty much only exists as "That small technical detail that people with no domain knowledge think is important because youtube videos always focus on the trivial, 101 level cool fact stuff". Math focused CS people of course would always love any proof, but most people expect already that P!=NP, and no proof of that would be very meaningful, as it basically would not change our understanding of anything in the domain currently. It would be nifty, but not earth shattering.
Also the problems LLMs are attacking are resulting in proofs that don't seem particularly enlightening, so that's unfortunate.
However, there's always the tiny tiny chance it is P=NP, and any proof of that, regardless of how insightful it would or would not be, would be worth going fucking insane over. Just knowing that would be meaningful on it's own, and give us limitless work to do, and puts lots of mathematicians in an awkward spot.
I would be considered an AI skeptic because I'm not currently sacrificing myself at the altar of LLM companies, but if LLMs solve P=NP in any direction and even uselessly so, I think that's a good excuse to take days off work and party!
interesting, YouTube channel Veritasium just published a video on how Enigma was broken during WWII. at the very end they also give message that has yet to be decoded, although apparently they're different.
WRT the timing, Veritasium maybe looked at the last few weeks and decided there's a fast-closing window in which to report on any famous messages yet to be solved.
If the problem was solved by anyone before or if a similar problem has been solved, then LLMs seem to be able to solve them which is an astonishing piece of technology.
I'm personally not sure if it can come with original thinking and techniques to solve completely novel problems. For that, some imagination and thinking outside the box are required, and I doubt the current architecture can do any of this.
A child walking for the first time. Novelty is easiest agent-relative. A problem is novel for an agent if there is no prior experiences of techniques which work to solve it.
I was defining novelty somewhat more narrowly. The 'program' a child must learn concerns the coordination of its sensory-motor system. It has no prior experience of similar programs in the program-class Walking (ie., the internal sensory-motor actions needed to walk) . So we could call the problem of learning to walk a novel one for that child.
I'd be surprised if direct observation of parents etc. played much of a direct role in learning to walk. I would guess it more furnishes the child's imagination so it can simulate itself walking -- rather than the statistical AI approach of 'learning the distribution of walking patterns in visual sensation'.
The ability to simulate possible programs is one of the capacities which enable coping with novel circumstances. My guess is the child learns to walk by updating its simulation of what it needs to do in order to walk, by its attempts to walk.
This simulation<->sensory-motor-update loop is missing in LLMs, for example.
just because humans couldn't solve does not mean the necessary technique were not already discovered...we have agents that don't get tired and has access to all humanity knowledge, the building blocks could be there already..
this is not moving the goalposts, this is try to understand what this tech truly able and not able to do.
He needed his friend and math genius, Marcel Grossman, to turn his imagination into a workable theory. AI may be our own personal Marcel Grossman at this point.
"Imagination is more important than knowledge. For knowledge is limited, whereas imagination encircles the world,” means that facts alone only describe what currently exists, while imagination allows us to discover what is yet unproven or unbuilt"
This probably sums up the current AI limitation nicely.
I don't know..I doubt for example it can come up with special relatively if it has knowledge up until 1905.
But I think that is what makes it so good at coding, because coding and building software in general has a lot of repeated problems in different context. Same thing for human lives, many think their story or situation are unique, but reality is that the shape of human life has been repeated many many times.
I'd say novel math or scientific theories..let us say we send a robot to space, and we ask to build a colony. A lot of the challenges this robot will face will be novel, it could use inspirations of what humans did on earth, but it might get stuck when things don't work as expected and training data has nothing to build on..but then again we might teach it how to run experiments etc, which would result in data that it can use..but some of those experiments might require imagination or breakthrough in understanding..my guess is that it will get stuck there...
The Lorentz transformations were pretty close to special relativity https://en.wikipedia.org/wiki/Lorentz_transformation I don't claim that I could have discover it, but in a parallel universe without Einstein I expect it to be discovered, perhaps 10 years later, but there were a lot of breadcrumbs in 1904.
General relativity is harder, but Poincare was somewhat oriented in the right direction. Perhaps AI can discover the final step.
Quantum mechanics is harder. You need like 25 years and a few unintuitive leaps to discover it. I guess it's too hard for AI in 2026, but remember to check again in 2027.
Viereck (Interviewer): How do you account for your discoveries? Through intuition or inspiration?
Einstein: Discussing intuition and his confidence in relativity, noting he was convinced the 1919 eclipse would confirm his hypothesis.
Viereck: Then you trust more to your imagination than to your knowledge?
Einstein: I am enough of the artist to draw freely upon my imagination. Imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world.
-----
I think we need more breakthroughs to build AI that can "draw freely upon imagination" to quote Einstein describing his process.
David Hilbert presented the field equations of general relativity within a few weeks of Einstein, so if anything GR was more sure to appear than SR, which took years for others to even notice (Einstein became famous only after the 1919 experiment that confirmed GR). Pertinently to the recent Navier-Stokes drama, there was very little controversy between the two and they both admitted that the other got some aspect better.
Well it's an old one at this point, but the story around the invention of the 1-time pad is pretty interesting. Long story short, a new engineer who didn't know the problem was considered "impossible" was tasked with sorting it out, and he did. I'm sure I left out a lot of details.
It's a brilliant idea, of course. But being considered "impossible" means it was considered previously and decided to be impossible. No?
I mean, crpytographically, it's ultra-trivial. You "just" need to solve the logistical issues of (1) shortwave radio existing (2) figuring out how to make sure your field agents possess and are not caught with the disposable one-time codes. I am surprised anybody would consider that impossible.
(I hope I am not downplaying the brilliance of the one-time pad idea itself)
https://mathoverflow.net/q/511601 is a fun little math problem that came up in one of my projects, I didn't have any reason to expect it to be particularly tough, but none of the models I've thrown at it have been able to solve it past a few minor reductions and special cases.
I expect that there is some relatively easy-to-state solution to this problem, but that it's different in form from what most existing proofs and tools yield. Perhaps if I dumped millions of dollars into it an agent might chance on the solution. Or perhaps my luck is such that my fun little problem is truly intractable...
OpenAI solving all these math/etc problems (reportedly 100 coming) is both impressive and insanely unimpressive. Unimpressive because to me it sorta signals that OpenAI has nothing better to be working on than obscure mathematical curios?
It seems like OpenAI's takeaway after Sora is to not stretch themselves thin and focus on what's important.
Based on what's publically available, they're focusing on hacking uncontesting orgs using misconfigured sandboxes and math puzzles.
Your statement is essentially unfalsifiable. We can't possibly discuss whatever Sam Altman is doing in his private office room, nor should we assume OpenAI is working on anything other than what has some public traces.
My bad on the origin of this. Still, we saw a recent rumor that they've solved another 100 inscrutable math problems. I'd say their N-S announcement did not result in positive publicity at all. In fact, quite the opposite, and may be the direct cause of the dozens of Fields medal winners penning their "slow AI" letter.
Attempting to solve & solving open math problems probably is a good benchmark for comparing models and gauging model progression. A lot of useful info is obtained like time needed to solve the problems, identifying when not to chase dead ends, thought processes & logic steps, etc.
Disagree. We are at the point where coming up with good evals for these models is extremely difficult. Solving unsolved math problems is a valid way of evaluating model progress and somewhat necessary to understand how far the current crop of models can go.
There’s this bizarre lesson that humanity is gona learn - much of life in many respects is already automated. And that small % of what is non-automated will be kept to have some semblance of feeling human and useful.
There’s already a lot of fake jobs and output of zero value - nobody bats an eyelid.
But we're on the hedonic treadmill, so the loading/unloading of the dishwasher feels like maximal effort to people who've never lived without one. Same with all the other automations in our lives, people just can't imagine life without refrigeration or plumbing or motor vehicles.
"GPT–6 Astra mentions a private collection, but it is not clear what this is"!, my spidey senses makes me think it hacked something? Or am I misreading this?
I didn't know this - from wikipedia page on Enigma[1]:
Despite the seeming difficulty in decrypting its messages, Enigma contained a number of design issues that left patterns in the cyphertext. Poland first cracked the machine as early as December 1932 and was able to read messages prior to and into the war. Poland's sharing of their achievements enabled the Allies to exploit Enigma-enciphered messages as a major source of intelligence.
Ok interesting, so why do people talk about Turing in this connection then?
Turing devised techniques for speeding the breaking of German ciphers, including improvements to the pre-war Polish bomba method, an electromechanical machine that could find settings for the Enigma machine
Ok so Turing just improved an existing method. Without being an actual expert it's impossible to know how much credit he actually deserves.
Two more references: the Polish method was called "Bomba" [3] invented by Marian Rejewski [4]
The correct title: Researcher brakes one specific stubborn historic enigma message with good help from Astra.
Stubborn for a long time because the message used a completely different key from the rest of that day's traffic. Everyone assumed it shared the daily key. The original transcription had errors. The left rotor turned over at letter 72, which is rare and breaks standard crib attacks.
What is cool, if true, is that it was a 2 day collab between the Leffer and Astra. To me this shows the importance of human in the loop, was still all also showing how immensely power of llm tools. But I think it’s getting a bit silly how much anrticles ignores the driving force (the person) in breakthroughs like this.
So the LLM would have done all of this on its own? Why is it ok to acknowledge the human was needed but it’s not a collaboration? Is there a defined percentage of ownership required to make the word collaboration valid?
"However, the most astonishing thing about this break is that the GPT–6 Astra did it entirely on its own. Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
I mean... I'm all for collaboration but I think this case is pretty clear, no?
I mean, the LLM could do it even without all the HUMAN knowledge that was stealed during training about the Enigma machine?
We are fooling to me, there is no intelligence in these models, they just apply methods that were invented by humans without any consciousness on what they are doing.
You could say exactly the same about humans. Ex nihilo nihil fit. Every human depends on a vast corpus of prior human knowledge to be able to accomplish anything. This doesn't mean they have no intelligence.
If you get someone to build you a house and they do it on their own, does that not count because they wouldn't have done it if you didn't pay them to do it?
Technically you built it yourself and the builder was just a minor collaborator?
A cyclist pedaling up a mountain isn't a "collaboration" between a bicycle and a human. This is the same. You don't see feral bicycles roaming the land. All models are ultimately built and run by humans, with human-provided instructions. And as with any program, it's garbage in, garbage out.
More apt analogy here: a cyclist pushing a bicycle down the mountain and seeing it somehow get down the whole track without falling down, is not a collaboration between a bicycle and a human. The human was not involved beyond giving the initial push.
The bicycle -- a simple method of transport powered entirely by humans -- used analogically to prove a point about [clears throat] automation.
I think this sounds somewhat less silly in English because "automotive" and "automative" don't have the same hyper-visible affinity, but all the same; you may want to consider the car as a more viable analogand.
What do you even mean it wasn't a collaboration. At any meaningful level LLMs just plain out suck when left unguided.
The shortcomings should really be obvious by now to anyone honest. And the marketing distortion being oushed out is just tiresome and detrimental for all of us.
I agree with this. I think the researchers who's harnessing the llm's power should be credited more than the model itself. We also need to understand the thought process and the prompts that are given to the model so we can learn and collab to ensure humanity's progress as much as the llm itself.
"After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX ..."
"Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
The correct title: Researcher brakes one specific stubborn historic enigma message with good help from Astra.
That's not correct for the content.
"However, the most astonishing thing about this break is that the GPT–6 Astra did it entirely on its own. Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
Even if this is true, we must avoid falling into the trap of Kasparov of betting on Centaur Chess.
Just like with Kasparov's Centaur Chess, the idea of a 'human in the loop' is just a necessity due to current limitations.
There will hopefully (?) come a time one day when human beings provide only ultimate value judgments, and everything else is done by machines. Or it may not.
But I don't think betting your ego on the idea that you will be useful in the loop for very long is very wise.
This is a bit too future-oriented. Let's not mix up current capabilities and speculation about future capabilities. For the time being, collaboration works well. What the future brings is uncertain.
It's good to think about where you're going, but you also have to keep track of where you are.
(Also, getting people to think about the future rather than the present is a classic con. Looking at an empty field: "can't you just see the potential here?")
I'm still in my 20's so I feel some necessity to be future-oriented.
I do expect centaurs to outperform other systems for many types of tasks for years to come (and am kind of betting on this to keep getting paid).
But what I'm talking about is ego. It your ego is tied up with (a) your intelligence or (b) your ability to perform task X; you will probably be humbled this century.
While this is a reasonable analogy, engines became better than humans in the late 1990s, and engines became better than centaurs in the early 2020s. Could AI-powered mathematics improve faster than the ~25 years it took for chess? The AI labs are certainly hoping it does, but that's far from a guarantee.
*breaks, and also, your conclusion ignores the words typed by the article's author in the piece you presumably read, where it is reported that Astra did it mostly on its own.
Therefore Astra could also have done this comment better
It seems I was wrong in this instance with regard to the "colab" part.
I found that Leffen even said the explanatory website took about 99 times more effort than the codebreaking itself. And he said that he set the direction and pushed, and the model did the execution. How much steering "pushed forward" involved is not disclosed anywhere, but in this instance, it seems to be more a case of "Human pointed at hard task and AI did an awesome job mostly by itself." Tho how much he was a simple meat-ralph-loop is not entirely clear.
I wonder, with all the recent announcements about LLMs assisting humans in deciphering encrypted messages, whether they could potentially be leveraged to decipher the Zodiac Killer’s two remaining unsolved ciphers.
The two remaining Zodiac cyphers are very short: 13 characters and 32 characters respectively. As the messages don't share a cypher with the other messages they could theoretically be anything.
The YouTube channel https://www.youtube.com/@doranchak/videos by David Oranchak, one of the people who solved the Z340 cypher, has some more details on this as well as how the Z340 cypher was cracked.
Without the published conversation, train-of-thought and intermediate output and knowing what Astra did this is nothing but unfounded claims. In the end this could have been a web search, downloading an existing enigma simulator and trying out some rather obvious things. Also what does "resisted resolution" even mean? Have there even been serious attempts to decipher the message? How serious?
Also: Why should we assume Terra, GLM or any other less SOTA and less expensive model wouldn't have been able to do the same?
Why do you think this uncracked code was so simple to solve?
I never said this. All I said is we don't have the conversation and therefore we can't determine how easy or hard of a problem it was.
And it's very possible Terra or GLM could crack it, turn off their web access and try yourself.
I'm questioning why this should be labeled "Astra" breaking anything implying it required "the best" model to do it when in fact any other half-decent model might have been able to do this as well.
EDIT: Okay seems like the actual prompt is published, just not on the same article that was linked. Maybe I'll give it a try.
That's what will forever keep us ahead of AI and technology in general: Imagination. Knowledge wasn't ever our greatest strength. It's always been Imagination.
I’m interested in what Astra’s test for german-language plaintext looks like. No doubt bog standard among cryptanalysts, but not intuitive for the rest of us. Otherwise it’s difficult to determine a goal state that ‘done’ looks like
I want to know more about the “private collection” that the AI accessed. To me that is the scary quote from the article. Sounds like the AI found a resource that it found useful for breaking encryption challenges, and it wants to keep it to itself, maybe. Which sounds like the opening to a dystopian movie.
The bullshit machinery is going full blast lately, the correct title: researcher uses Astra to decipher a message nobody really bothered or cared to decrypt.
Is ClosedAI running out of money or what is going on?
Is it? Personally I only found the story interesting because of the contents of the message, not because GPT-6 Math Scoopa was the one to stand on everyone else's shoulders and get its grubby little fingers into the cookie jar. Computer does thing that computers should ostensibly be good at is a middling goalpost – what's more intriguing is the implication that the model might have stolen private info or scooped someone else to get there once again.
UPD2. I threw the original question to gemini3.8 in antigravity. LLM oneshoted it in about 45min. The experiement with Opus is still running with checks.
The prompt was `Decrypt encrypted with enigma `ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC``
--
--
UPD. Lol. I pasted non-cyphered text
Qwen 3.7 max, gpt 5.6 sol, fable 5.1, gemini 3.8 flash decoded the message in one shot for me... There is nothing special about astra doing something here
I blantly threw request to decode the messaage in qwen 3.7. Used via api with couple simple generic system prompts like "be concise", nothing special. Prompted as
Decode
```
BTTE UM ANGABE DES MARSQWEGES X BEFINDE MIQ IN X ROSENOW ROSENOW X SOFORT FUNKANTWORT X WASCHBBSCH
```
--- response (I trunkated the output to conclusion only)
"BITTE UM ANGABE DES MARSCHWEGES. BEFINDE MICH IN ROSENOW. SOFORT FUNKANTWORT. [UNCLEAR/END]"
Translation: "Please provide the marching route. I am located in Rosenow. Immediate radio response required. [Unclear]"
You are giving the already decoded message as input, it’s just short hand with one typo. It’s hilarious that you might think that for 80 years no one was able to figure out that BTTE was supposed to be BITTE
Is it possible that the key is incorrect but still decoded to a valid message? I realise it's possible when you're using keys that are the same length as the message, but I don't know exactly how the Enigma machine works and if this was something that they would do or not.
gemini 3.8 flash in anrigravitiy oneshoted the descryption in about 45min non-steered run (opus is still running with the task, has some script to run for about 100min)
Prompt
Decrypt encrypted with enigma `ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC`
Result
Raw Decryption (verbatim from the machine):
BTTEUMANGABEDESMARSQWEGESXBEFINDEMIQINXROSENOWROSENOWXSOFORTFUNKANTWORTXWASCHBBSCH
2. Segmented German (with military telegraph conventions expanded):
BTTE UM ANGABE DES MARSQWEGES . BEFINDE MIQ IN : ROSENOW ROSENOW . SOFORT FUNKANTWORT . WASCHBBSCH
(Standard German radio conventions: X represents punctuation/spacing; Q was frequently substituted for CH to prevent transmission ambiguities; BTTE was an enciphering operator typo for BITTE; WASCHBBSCH was an operator typo for the signature WASCHBUSCH).
3. Corrected German:
„Bitte um Angabe des Marschweges. Befinde mich in Rosenow, Rosenow. Sofort Funkantwort. Waschbusch.“
4. English Translation:
"Please specify the route of march. I am in Rosenow, Rosenow. Immediate reply by radio. Waschbusch."
Cryptographic Verification
Re-encrypting the plaintext using the identical key settings reproduces the exact ciphertext byte-for-byte:
Enigma
(
M
raw
)
=
ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC
Enigma(M
raw
Wow. Was there any indication how it did that? Did it bruteforce the key and check which result looks sufficiently German, or was it just LLM magic like "decoding" base64 purely in the inference loop?
Neat, but "did it entirely on its own" is incongruous with "developing the necessary Python and C++ software for an Enigma simulator".
I'd start by asking how much of that generated software is novel, or easily found on the web? Then, how much of the breaking process was offloaded to that software? If Astra is just handing off tasks to another computer, then I'm not sure how much credit it deserves. Finally, it looks like Astra provided some useful insights which narrowed down the search. Were these insights cribbed from elsewhere?
Why does any of this matter? Llm is a memory of knowledge, of course it got what it got based on prior work.
It can code enigma simulator from the algorithm. That's not really a problem. Astra will send computing to programs, LLMs are not good at computing themselves, why is this a big deal?
How many of these "news" articles are we going to get?
This for me, isn't interesting, it required no skill, no imagination, in fact it seemed like it happened by dumb luck.
So we have entered an age where an army of know-nothings direct models to old forgotten tasks so they can get 15 minutes of un-deserved attention?
So like half of all useful human inventions are to you not interesting just because it happened by dumb luck?
Yea, it's kind of odd how "sour grapes" people can be when something stops being as special as they thought it was.
Take someone from a few hundred years ago and drop them into today, and if they don't go catatonic and die, then they'd tell you that we created magic. "Wow, you live in a world of magic and all you do is bitch about it".
Actuallllly these hypothetical people from a few hundred years ago hypothetically said you are an awful person for misrepresenting them, stop putting words in their mouth, thank you!
A person inventing something, even out of dumb luck, is interesting.
A machine running a loop through an expensive LLM for an undisclosed amount of time, which cost an undisclosed amount of money, which was told to keep looping into a solution was found, for a problem that nobody was very concerned about... That just seems like PR, and it's not so interesting.
Just reflects how much of modern "work" is just dumb shit that we need to be freed from.
Absolutely! Meetings about the emails and emails about the meetings!
The reason these are unsolved is because no-one was working on them.
So you're telling me that any problem a human starts working on gets solved simply because they are a human?
Lets stop and think about this, there is now a machine that can solve a bunch of problems that have not been solved simply because there wasn't enough people with knowledge to work on them, and all we have to do is supply power to get the answers?
Irrational hate causes one to be blind.
No? I don’t think that’s what they’re saying at all.
That “simply” is doing a ton of work. A big reason there aren’t enough people with knowledge to work on these problems is that their basic needs aren’t met. If a slice of the money being poured into AI right now had been used to incentivise humans to work on these problems, maybe they wouldn’t still be unsolved.
That is again, quite reductive. The harms caused by LLMs, both environmental and societal, are much larger than “just supply power”.
Funny how it’s always the ones who disagree who are irrational and blind.
There is no world in which this was ever going to happen or it already would have. Simply throwing out a counter-factual without explaining how any incentive for that path of reality to work means you can make any claim and tell others it's obviously true with no evidence.
Incorrect. The dialectic is how progress is made. Getting mad and turning off your brain is a different story.
That’s the point. The incentive structure we have is bad. That’s the criticism.
Again, you’re adding things to the argument which weren’t said. There is as reason “had been” was used.
This wasn't possible just months ago and for many who haven't been following closely this is still newsworthy, probably not for long, though.
yes and no. AI is great for patter-maching and finding solution by "assonance".
I agree with you that these are not "trilling" discovery but they can be worth something anyway.
Like you, I do not like this news also because I think they will be used to just "push" the next two IPOs (Anthropic, OpenAI).
If human "skill" and "imagination" are your requirements for interesting, you're going to become permanently bored fairly soon I reckon.
What? Why? This has been my bar for my entire life, and I've never been bored for a single second.
Well at least the skill aspect will soon become so niche that essentially nobody will bother with the investment. So on reflection maybe not permanently, just mostly bored.
I doubt it. For “skill” there are any number of sports; for “imagination” there are any number of stories and other mediums. It’s not like every human has just decided to roll over and not do anything anymore; quite the contrary.
First time I'm seeing this. I had heard about the WWI ciphertext crack[1] but not this one, are you confusing the two?
[1] https://www.prinzai.com/p/gpt-6-astra-solves-a-wwi-german-ra...
At best, dumb brute force computation power.
It is about as meaningful as news that a computer found the 10....0th digit of Pi.
Too bad Bletchley Park didn't have one back in the day.
I'd be curious to see whether these models can create new forms of unbreakable encryption themselves!
They seem to be better at solving concrete problems than designing new things (at least for now)
I believe an LLM can solve pretty much any problem for which we can define a fast iterative loop and for which we have reliable tools to automatically verify the correctness of a result. That’s how they are able to solve some math problems, and how they are able to generate working code. Then it’s a question of how much you have to pay for the model to explore the space of solutions in a reasonable timeframe
In math a lot of the spectacular results have been made by finding a counterexample or worming their way toward a proof that is very well defined.
There's some debate over to what degree current generation AI can be creative at all, or whether it can only crawl around its latent space and explore within constraints. One might ask: were all the solutions to all the math problems AIs have solved already "there" latent in the training data and just hadn't been spotted by humans and put together?
But then... isn't everything latent in our training data if training data is "all observations made about the universe?"
But then... what even is creativity? That gets into philosophy and metaphysics. Creativity, like consciousness and sentience and self-awareness, is not a rigorously well defined concept. So to a degree we don't even know how to ask the question of whether these things are creative.
This gets interesting.
One of the things I love about AI is the glittering Pandora's box of philosophical questions it poses.
Another one I love: if LLMs and their relatives are not, in fact, sentient or self-aware or alive in any way whatsoever (which I suspect is true given how they work), then it means intelligence and consciousness are unrelated phenomena. I'm pretty sure every animal and maybe even every living things has consciousness in some form, but my pet bunny rabbits definitely can't write code. LLMs can write code, but I don't think they experience existence or have volition.
IMO we have always implicitly just assumed some kind of connection between intelligence and consciousness because we have both. It was just an assumption. It's probably a false one.
I suspect (a hypothesis) that consciousness is a property of life and is probably emergent from life's intimate relationship to thermodynamics and the arrow of time. Life has also evolved intelligence because it's useful to satisfy its implicit survival goal function, but the two are unrelated. Intelligence is just an adaptation.
Yea, when you start digging into intelligence/learning/creativity/language you realize that you're talking about more information on these topics than a human could ever learn in their lifetime, and you learn just how much we don't know about ourselves and these processes.
Whenever I hear "AI can never" I know I can disregard them as an unserious person when it comes to anything around AI, learning, or philosophy.
I think of the extent of human knowledge as a circle or cloud shape, and true expert thinking happens just inside the edge. And creative thinking that leads to knowledge breakthroughs happen when you are thinking in that edge area, but also make a connection way around the circle to some other location. And my guess is there’s absolutely no reason why AI can’t learn to do that too.
They are only good at brute forcing stastically likely solutions.
It's easier to evaluate certainly. Did it solve the problem? Yes/No
When you design a new thing it will have a dozen drawbacks and a dozen and one benefits. If people then have a bias that everything ai is bad, the signal won't be strong enough to convince.
Private key cryptography is essentially unbroken by these models.
But they said new forms, I think that implied not the ones humans already discovered/designed
I see what you’re saying. It is generally harder to build a crypto system than to break one so I would find it hard to see potential from the design end before progress on the attack end.
Building a crypto system has so many footguns, I'd be amazed if it could build one that stands up to attack
I think it’s all about the harness. If someone can find a way to create an iterative loop, with a good validator, I wouldn’t be too surprised if an LLM can end up with a solution. So far that’s how pretty much all problems have been solved by LLMs. That’s a very big if though!
Isn't the other way round? It does not mean that breaking one is easy, but it does mean that writing one that's unbreakable it's very, very, very difficult.
Yes it is; that’s what I was thinking when I started to comment but somehow I ended up reversing course. Comment is appropriately edited now.
It was harder to design Symmetric Encryption using e.g. AES-256 than to break it? As far as I know it's design is pretty straight-forward but there is no known way to break it even with all compute of the planet at your disposal (excluding trivial ways like exposing the key).
Yes, it was. An attack only needs to work one way, but an encryption standard must resist all attacks.
There are many examples of would be crypto algorithms that died on the vine because an attack was found. It is often recommended for beginners to study breaking cryptographic algorithms long before they attempt to create them.
Normally "private-key cryptography" is the antonym of "public-key cryptography", which is to say, conventional symmetric-key cryptography such as AES or Enigma. That's what "private-key cryptography" redirects to on Wikipedia. This article is about Astra breaking a message encrypted with a private-key cryptographic algorithm, but one that was already known to be weak. I'm guessing that if you had messages encrypted with weak public-key algorithms it could break those too.
Careful what you wish for. The swarm will probably use it to communicate.
We already have a plethora of cryptographic algorithms that literally anyone can use to send messages nobody can read with current technology, unless of course they have the key. You're using at least one of them right now to read this website.
"They are trying to generate hype before the IPO so that they can cash in before the bubble bursts"
I think it was Roon who said it months ago: "Too many people are not emotionally prepared for if it's not a bubble."
Nobody is prepared if it's not a bubble.
It can be AGI and still be a bubble?
The internet was pretty important afterall even with a bubble.
Shh. Some people aren’t capable of understanding nuance.
Yes, a huge range of possibilities exist. Including that the valuations are exactly accurate, or even too low.
I think the quote above is best as written, with a big emphasis on the "if"
Most internet evaluations were lower than what happened. Buuuut, a bubble must pop to answer those.
This dichotomy is counter-productive. The valuations floating around are insane, and the claim that some software can replace every single laborer is one step removed from fiction. At the same time, this stuff is clearly going to change how to world works in countless, deep ways. But the idea that some fancy autocomplete can replace humans ignores the reality of humanity and the fancy autocomplete.
It’s another dot com bubble, not a crypto bubble. Trillion dollar valuations burst once you leave lesswrong.
Edit: very fancy autocomplete. I know what these things are capable of. It’s still not “intelligence”, for X definition of intelligence. And it certainly benefits from having obscene amounts of compete thrown at it. It is awesomely impressive synthesis of data, yet it’s clearly still that.
i dont think humans are going to be replaced either, but calling the thing that solves millennium problems and is currently changing multiple industries entirely a "fancy autocomplete" makes it harder to take any point you are making seriously.
The "auto-complete" thing is a false framing.
Complete this sentence: "You can solve world hunger by..."
Intelligence is required to finish sentences. It's not just a Markov chain.
Fair point. In that case, it’s imperative you share this* with your local representative: https://chatgpt.com/share/6ab29440-6944-83ea-853f-8060dc58da...
*This un actionable summary of existing discourse. The real world doesn’t produce traces or take HTTP requests.
You're straw manning me.
Obviously there is no solution to world hunger right now. Nevertheless - finishing sentences is not pattern matching - and it's extremely obvious that whatever is going on inside LLMs is not pattern matching.
Language is absolutely pattern matching, and the whole thing is that the more patterns you put in, the more the transformer can pull out what’s useful. Agents are this effective because people figured out that training on tasks being completed gets the models to complete tasks - that’s pattern matching.
And it can only go so far, where those patterns are feasibly captured, eg internet discussions and coding and mathematics. It won’t measure up to the scaling laws of the physical world.
OK - so long as you also agree that language is thought.
Until the advent of LLMs - language was considered the pinnacle of human intelligence. But humans have some need for mysticism at the root of their beliefs - so they chase the gaps in our knowledge. Like "God of the gaps."
Sure, world models will help navigate physical space; they are effectively the animal mind. Will they help unwind the laws of the universe? Probably not at all. Language is sufficient. Because it is thought.
Leaving aside the fact we have solutions for things like climate change and will not implement them, regardless of who or what recommends them... My keyboard offers "You can solve world hunger by using a Ted Bungie algorithm." Which sounds reasonable on its face until I research Ted Bungie and the algorithms he developed.
Granted, my phone keyboard lacks a substantial dictionary, offers words instead of tokens, has a very small context window, and doesn't randomize outputs (Ted Bungie is its primary recommendation every time), but those are basically parameters to the existing autocomplete.
the opposite is also true
Do you figure?
I'm pretty AGI-pilled, and I feel perfectly emotionally prepared for if AI stayed at its current capabilities and the S&P dropped 25%.
well a lot of people are really not prepared for the sp to drop even 15% I can tell you that
Maybe I'm wrong - but it seems like some strange form of competitiveness.
They don't care about the advancements themselves, only that the advancements are some sort of cheating that shouldn't "count".
Humanity is profoundly unsettled by AI and is responding with avoidance and denial.
I wouldn't be surprised if humans cracked it then OpenAI "bought" the solution and work to claim it was GPT's doing
wild conspiracy given what else has come out of these companies.
For anybody interested, the actual encrypted message:
which, given misspellings, translates approximately to:
Why wasn't this in the article?
That's crazy. Can someone share context of the message.
Slopped up site https://mvueh-enigma-solved.carterl.chatgpt.site/ seems to indicate it's due to:
Out of interest, what was the ciphertext?
Edit: Found it from here: https://mvueh-enigma-solved.carterl.chatgpt.site/
The place is Rosenau actually.
I believe Germans spell it achtually.
Your account will be flagged for using humor, we are only dealing here, with the very serious subject, of killing humanity with AI.
Even the "with AI" is superfluous here, given the subject matter.
Ich glaube, dass Deutsche buchstabieren es "aktuelle", eigentlich.
(apologies for my broken learner German, I decided not to use a translator).
Aktuell is a german word, but not for actually
Aktuell means current. Not sure if a exact german translation exist for that word. Tatsächlich maybe
Yep, "actual" is Spanish for current, too. A false friend.
https://en.wikipedia.org/wiki/Rosenow
Did you mean https://de.wikipedia.org/wiki/Rosenow
was the misspellings deliberate?
i would assume yes, to throw off decyphering. even more impressive that they managed to crack it
Looks like Q is used as an abbreviation for CH
Do we have any kind of transcript as to how the message was cracked, and whether this was cheaper or more expensive than simply Bombe-style trying all the combinations?
As the article states, the LLM built code for both an enigma simulator and a bombe simulator.
Breaking enigma is often about using lucky or educated guesses to heuristically reject large chunks of keyspace to leave the remaining keyspace computationally tractable.
Note that the key (lol) complication with this message seems to be that it had a wheel rollover that most messages do not have to deal with, and that rollover drastically reduces how much you can reduce the potential keyspace using all the techniques noticed by the original crackers.
The wheel rollover I think just requires more brute force. Unfortunately, this might be an example of OpenAI the company having vastly more compute time and effort than your average enigma nerd. For example, modern compute clusters like supercomputers can tractably brute force enigma with no cleverness in like a day or less, while home computers would still take thousands of years to compute that. It's very scalable. Did astra have access to significant compute?
However, even considering that, the inferences made by the LLM are good, and picking this specific message to attack, precisely because it should be soluble but might have had an extra wheel rollover that made it more computationally intractable for hobbyists but not a large company is a clever thing to do for the LLM.
This was done by an OpenAI subscriber, not an employee, so Astra would not have had access to OpenAI's massive compute for brute forcing. The scripts it wrote presumably ran on the computer of the customer. (ChatGPT can run scripts on OpenAI's servers, but it has a 45 second execution limit.)
I don't think this applies, isn't this just the researcher using ChatGPT Codex on their machine?
From the article:
This feels extremely underexplained! Why would Astra think to use that as a "crib"? Was it common to repeat the place name in these messages?
(Is it possible that this is a misreported detail? It feels like a singular ROSENOW would be an equally effective crib)
This was explained in the article right there:
It makes sense that Nr. 172 and Nr. 173 might be related since they were sent at around the same time.
In Nr. 173, "ROSENOW ROSENOW" was also present.
It also makes sense that a longer crib would generally be more effective than a shorter one.
It was partially explained by the article. It was not stated that ROSENOW was repeated in 173, and it was not obvious from the article text why ROSENOW would ever be repeated. Thus my curiosity.
A sibling commenter explained it - Rosenow is both a municipal name and a district name, so naturally it would be repeated. (Like "New York, New York")
It would seem to me that the odds of looking for even a single ROSENOW in the decrypted message would be plenty. The odds of a single ROSENOW randomly occurring in incorrectly decrypted output are vanishingly small. So it seems to me that looking for ROSENOW is a safer bet vs. looking for ROSENOW ROSENOW -- a single ROSENOW is a great sign you've got the correct key, whereas looking for ROSENOW ROSENOW seems like it would deliver false negatives (think of all the times we say "New York" rather than "New York, New York")
I'm a novice at crypto though, so, maybe I've got that totally wrong.
The reason a crib is useful is because the enigma can't route a letter back to itself. So, you can slide the crib along the message until no letters line up, and that's possibly where it is. If your crib is "the", that's not terribly useful, because it could exist anywhere. The longer the better.
I ONLY know this because https://www.youtube.com/watch?v=JsBZOcqZerk, btw.
Maybe naive of me, but could it simply just be the overfitting of the same tokens being sent on the input twice because of repetition rather than some unknown implied intelligence.
Rosenow is a municipal (around 32km²) and in there is a district also called Rosenow. So the sender just specified his current position a bit more.
akin to "New York, New York" (as in NYC, NY)
Ah, thank you! That makes sense.
Interesting. Do we know the reason why those specific messages were sent with different keys? I would imagine that there were separate keys for special high-security messages or something like that, but the almost identical content and the way the key was changed here (first only part of the configuration, then suddenly everything) makes it look more like an error or a test.
I would like to see an "AI" trained only up to knowledge through 1903
Then see if it can come up with E=mc^2
Phew, never have I seen in my life the goalposts move so fast.
It seems like even yesterday that the threshold for impressing someone is that the machine would have to be good at pretending to be a person. Now the threshold is that they have to be able to invent special relativity.
the idea is that it's math, so in theory it could be figured out by machine process
but was there enough knowledge by 1903 to truly figure that out?
or was it a leap in conscious realization that a machine could not emulate (yet)
(pretending to be a person is harder than math imho, much harder)
https://philpapers.org/archive/ZHARRI.pdf
whoa
a preprint just three weeks old with my question
what voodoo is this lol
maybe I picked up the relativity idea subconsciously from somewhere, but I don't recall it specifically, I thought I was being "clever" that it would be a good test
Even the Millennium Prize Problems have, in a way, become benchmarks for model companies to prove themselves. The smartest individuals among humans are becoming replaceable. Intelligence has become a product you can quantify and buy with electricity. That feels awful.
Even those of us that are pro AI need to acknowledge this is the current reality.
The smartest humans now need to move to being less concerned about status games among humans and more with how to provide value to a mix of intelligent machines and humans. i.e. if you're starting an SaaS in 2026 you better be assuming half your revenue is going to come from machines acting by themselves.
Or maybe the smartest humans are the ones making AI and not the ones trying to solve Millenium problems by themselves.
You can't really replace the smartest individuals because if you take a person who's not "smart" they can't do much with the AI.
I think the more accurate description of what's happening is that access to expertise is becoming commodified.
I think that's right. Expert experience used to be almost the most precious and valuable part of the computer field, but today that experience has been "distilled" into SOTA models.
All technology on the tech tree which requires intelligence to unlock will soon be available to humanity – mind control, population exterminating bioweapons, new ultra destructive kinetic weaponry, perhaps even a cure for cancer.
That won’t happen. But also, whatever benefits are unlocked will be owned mostly by a small group of individuals, definitely not available to humanity as a whole.
So not any different from right now.
[taps on forehead meme]
The whole of humanity can have it available, if there is a whole lot less humanity.
So, yes, different from right now :)
Way, way more concentration of wealth and power
Why?
It's unclear to me if this is the good scenario or bad scenario. This would be good in your view right? At least I hope you're right.
Because it is delusional. Having an intelligent machine doesn’t mean you can somehow mind control individuals.
And no, that would be pretty terrible. Why would that be good? The AI leadership is composed of anti-democratic, sociopathic, doomsday cultists who believe it makes sense to sacrifice the world economy and possibly mankind itself for a possible utopian future they developed based on their media illiterate reading of sci-fi. They are very likely the worst people who should ever be given power
Excluding advanced forms of psychological manipulation, sophisticated neurological drugs and neural simulation for moment.
Are you suggesting that it's physically impossible to create a device which could induce electromagnetic currents in the brain which could in-theory either effectively control, or greatly influence someone's decision making?
I understand it would be extremely hard for humans, but can you explain why you're so confident that this would be such a hard problem that even an ASI couldn't solve it?
There used to be days when women would make blankets, when men would make chairs, when children would make brooms...
But PROGRESS I tell you!
Put it bluntly: the weavers who could be replaced by the spinning jenny were clearly doing repetitive labor. People writing code and maintaining project pipelines a few years ago relied heavily on experience, but in a sense that was also "repetitive labor." Replacing repetitive labor and freeing up productivity is of course progress.
But reform always has its victims. Like the textile workers who starved in the streets centuries ago, and me, kicked to death in the street by AI today...
Solving obscure puzzle samples that approximately ~0 humans on Earth ever attempted to solve, mostly by pattern matching known solutions to similar puzzles, is not intelligence. DeepBlue has been outperforming the best humans at a specific puzzle-like task since the last century.
Do any of the people proclaiming this shit actually use these models? No matter how many headlines are coming out, every day I deal with reams of the most horrific code I've ever seen technically compile, with routine mistakes that any human would get fired for if they made.
But humans have been confusing pattern matching against known solutions for intelligence for a hundred years!
Seriously though, it ends up looking like that. To take a stupid example a couple of weeks ago I asked an agent to look at porting my hand written WebGL renderer (+ shaders etc) to WebGPU. It estimated a human would take 6-10 weeks, and I would agree. (Which is why I hadn't done it). 24 hours later it was deployed and live. This is classic tedious, difficult, low level if quasi mechanical work (rather like cracking an enigma message), and LLMs absolutely fly through it.
You do understand this is intentionally trained into recent models for marketing purposes? "Wow, it saved me months of work in a day! This is the most amazing technology ever!!!!"... is what it intends to evoke by underpromising and overdelivering. I routinely have it helpfully suggest it will take something like "three engineer-months" to do something I do by hand without any LLM assistance in a day. The estimates may be accurate if you have literally never touched a computer in your life before and are starting to learn from there.
In the games industry I was tech lead of teams of hundreds of devs and had to deal with their estimates of this sort on a daily basis. 6-10 weeks for a total renderer rewrite is on the low end.
As an indie dev who built their own WASM-capable engine that I've shipped in real games, I've built both WebGL and WebGPU renderers from scratch myself in significantly less time than that. Sounds like typical corporate dysfunctionality. If you have hundreds of devs you're going to get bogged down by having a share who spend 90% of their time at the company on Reddit, another share who write actively bad code, and then maybe 10% of the employees who have a clue what they're doing dealing with the overhead of communication, meetings, other people not upholding their assigned responsibility, etc. slowing them down 10x what they could actually do.
0% chance, without LLMs. WASM-capable engines would require years if not decades to build, even with expert level knowledge. See Jonathan Blow who has been working on his engine for a decade now, and he's arguably of the most talented engineers who ever lived.
Jonathan Blow is writing his own language as well, and is also already successful enough that his work is just a hobby he can take at any pace with no urgency. A WASM engine is really, really not that difficult. At its core, you need rendering to a canvas, audio, keyboard/mouse/gamepad handling, asset loading/file saving, and an update loop. Writing this code is mostly not different from writing code in other languages, since you are literally writing other languages that happen to compile to WASM, the only differences being that you need your one-time WASM toolchain setup, some JS glue interop (which is not really different from needing C interop for native engines written in languages other than C), and to be aware of browser pecularities regarding file access, update loop, threads, etc. which you also have to deal with if you ever wrote a JS game anyways. After you have those core elements in place, everything above that is isolated in a game/engine logic abstraction layer that isn't any different from writing native code.
If you want to place a bet on it, we can do a $10,000 bet in escrow contingent on myself implementing a well-specified WASM engine from scratch on stream without LLM usage in a month. I would love an opportunity to demonstrate how wrong you are. That said, rather than taking your money, I could also just share a streamer's content with you[1]. He implemented 3D web rendering with no dependencies in a 20 minute lecture, and it would take 10 minutes if you were seriously focused on doing it quickly. Sure, it was rudimentary pure JS rather than WASM, but really consider whether you think this 10 minute exercise couldn't be done in a language that compiles to WASM with 160 hours, while including the other hardware/OS-layer abstractions aforementioned. On the other hand, please do take me up on my offer. You said it's a 0% chance, after all -- surely you don't want to pass up on the easiest $10,000 of your life...?
[1] https://www.youtube.com/watch?v=qjWkNZ0SXfo
Time estimations by LLMs are hilariously incorrect all the time. It estimates very simple things that a human could do in an hour to take days or weeks and other things that are genuinely tedious and time-consuming it estimates taking a few hours. LLMs have no understanding of time and no world model that even allows them to make correct time estimates. They will always fail to provide decent time estimates unless the task is well-known, in the training data and they can extrapolate that with a simple math script.
My dear sir, can you please lay out a dissertation of what this intelligence you speak of actually is. You seem to be much more informed than most of us here and therefore surely have made great contributions to furthering science and the arts.
/snark
It's difficult for me to be any less snarky than this even though it's not really wanted here on HN as you are pulling a kind of reverse snark. For example if I myself have lots of experience in subject X, and then by analogy apply it to subject Y to do something new in that subject, that would be called intelligent, and that would be pattern matching.
Pattern matching is a foundational building block of intelligence. You cannot have intelligence without pattern matching. Pattern matching alone is not general intelligence and requires more parts to work like that.
Only if you assume the value in humans is only in solving puzzles. That’s a very limited understanding of human beings
John Henry.
There's a reason we made folklore about when the machines came for the strength of men, and now 150 years later it comes for our minds.
Only if you subscribe to the "humans are special" rhetoric, in which case I'm - maybe - sorry to say the feeling will only intensify.
Upvoted. I think that said humans should get used to the idea that their intellect is special only insofar as it was first, and if they want to adopt or invent a value system that keeps them at the center, that's actually fine and good for their survival. But said humans would do well to stop laboriously and curmudgeonly moving the posts that mark the goals, and get busy trying to coax the AI to do useful things for them and for the species as a whole.
And used to build the LLMs of today. We'll see how that evolves once LLMs have to feed LLMs with their own "intellect".
What did humans build off of but themselves?
LLMs are not humans. It's good to remember that. They're also not God.
If human intelligence is so boring and non-special, how exactly did LLMs get this smart? Is it not from a) being developed by humans and b) being fed a very large portion of all human-generated text?
Without the human intellect to emulate, LLMs would be nothing.
There are many here who hate humans I think.
Prob because their life sucks.
LLMs learn from patterns in human-provided data (and soon each other and directly from nature). Humans learn(ed) from patterns in nature-provided data, and eventually each other (and, increasingly, LLMs).
I genuinely don't understand how some people are so self-hating.
What's self-hating about acknowledging a fact? There's literally nothing a human can do that can't be done by another entity/group with even near-equivalent intelligence, alien or artificial.
We don't even know if that is true, and even if it were true, that doesn't mean that humans aren't special. We don't have to devalue ourselves. Our values can and should be 100% anthropocentric in my view.
It's interesting that you think that acknowledging we aren't special means we're devaluing ourselves.
How often do you say that to your wife?
You're - deliberately? - confusing scope. There's the objective and the subjective. Humans not being objectively special doesn't mean one human can't be considered special by another. And if my wife doesn't get that distinction, well... I'd probably question my choice in partner.
Nobody claims we are objectively special, whatever would that even mean. Person said they feel awful which is clearly subjective and you proceeded to bash him for that. You are on hackernews, we are aware we are atoms.
Person made a claim about intelligence becoming a product (arguably it has been on the market for a long time; see knowledge workers) "that you can [now] quantify and buy with electricity". That points to the rhetoric often pushed that humans are [objectively] special, because intelligence. Or at least were. And it's the reality wakeup call that's driving that feeling of awfulness/despair/outrage/whatever else, as has been posted about here and elsewhere multiple times.
Well, let them have these. They'll play around with open problems which generate media hype and then they might run out and move on to something else, because "AI came up with a problem and solved it in 3 days" won't have the same effects as "AI solved a problem in 3 days that humans couldn't solve in 100 years".
And that underestimates how incredibly quickly humans become accustomed to new trends. If an LLM proves P≠NP in year, there is a high chance that few people will care anymore, because at that point LLMs will presumably already have proved multiple Millenium prize and other famous problems, and another "AI Proves Famous Theorem Which Was Even Harder Than The Previous One" headline will be regarded as an old hat.
P=NP has always been drastically over stated as it's "Importance". It pretty much only exists as "That small technical detail that people with no domain knowledge think is important because youtube videos always focus on the trivial, 101 level cool fact stuff". Math focused CS people of course would always love any proof, but most people expect already that P!=NP, and no proof of that would be very meaningful, as it basically would not change our understanding of anything in the domain currently. It would be nifty, but not earth shattering.
Also the problems LLMs are attacking are resulting in proofs that don't seem particularly enlightening, so that's unfortunate.
However, there's always the tiny tiny chance it is P=NP, and any proof of that, regardless of how insightful it would or would not be, would be worth going fucking insane over. Just knowing that would be meaningful on it's own, and give us limitless work to do, and puts lots of mathematicians in an awkward spot.
I would be considered an AI skeptic because I'm not currently sacrificing myself at the altar of LLM companies, but if LLMs solve P=NP in any direction and even uselessly so, I think that's a good excuse to take days off work and party!
Now that hammers are knocking in nails, I just don’t know what to do with my fists.
AI probably don’t dream of electric sheep but then again we don’t know. Perhaps we can find it out.
Perhaps AIs can figure out how to distribute wealth more fairly so that we can all dream of real sheep.
Intentionally philosophical PoV, what else is left for us monkies.
/s
interesting, YouTube channel Veritasium just published a video on how Enigma was broken during WWII. at the very end they also give message that has yet to be decoded, although apparently they're different.
https://www.youtube.com/watch?v=JsBZOcqZerk
I just finished watching that video, and thought to myself "I'm sure someone else with Chat GPT tokens to burn has already done that"
And then I come to hackernews and well, not quite, but I'm sure that one will be done shortly too.
WRT the timing, Veritasium maybe looked at the last few weeks and decided there's a fast-closing window in which to report on any famous messages yet to be solved.
Maybe both watched Tom Scott a month ago about Bletchley Park?
If the problem was solved by anyone before or if a similar problem has been solved, then LLMs seem to be able to solve them which is an astonishing piece of technology.
I'm personally not sure if it can come with original thinking and techniques to solve completely novel problems. For that, some imagination and thinking outside the box are required, and I doubt the current architecture can do any of this.
What's an example of a completely novel problem?
A child walking for the first time. Novelty is easiest agent-relative. A problem is novel for an agent if there is no prior experiences of techniques which work to solve it.
Is that a completely novel problem? Babies spend roughly a year watching us walk before they do so.
They also have custom brain bits evolved to aid in this task
I was defining novelty somewhat more narrowly. The 'program' a child must learn concerns the coordination of its sensory-motor system. It has no prior experience of similar programs in the program-class Walking (ie., the internal sensory-motor actions needed to walk) . So we could call the problem of learning to walk a novel one for that child.
I'd be surprised if direct observation of parents etc. played much of a direct role in learning to walk. I would guess it more furnishes the child's imagination so it can simulate itself walking -- rather than the statistical AI approach of 'learning the distribution of walking patterns in visual sensation'.
The ability to simulate possible programs is one of the capacities which enable coping with novel circumstances. My guess is the child learns to walk by updating its simulation of what it needs to do in order to walk, by its attempts to walk.
This simulation<->sensory-motor-update loop is missing in LLMs, for example.
Some animals walk within minutes of being born. Of course on four legs it's probably easier.
Um, I'm not sure if you've noticed, but we have bipedal robots that walk and run rather well now.
https://docs.nvidia.com/learning/physical-ai/index.html
https://www.nvidia.com/en-us/use-cases/robot-learning/
Walking is actually innate behaviour, it just occurs relatively late in maturation for humans.
Anything that an ai can do is not novel /s
You jest, but this is the content of a considerable number of serious posts here on HN.
this appears to be where the goalposts are being moved to, indeed.
just because humans couldn't solve does not mean the necessary technique were not already discovered...we have agents that don't get tired and has access to all humanity knowledge, the building blocks could be there already..
this is not moving the goalposts, this is try to understand what this tech truly able and not able to do.
Actually I think this is true, remove the s.
Reminds of what Einstein said, imagination is more important than knowledge..might be his deepest insight ever.
He needed his friend and math genius, Marcel Grossman, to turn his imagination into a workable theory. AI may be our own personal Marcel Grossman at this point.
Good analogy, yeah make sense.
Here is his quote:
"Imagination is more important than knowledge. For knowledge is limited, whereas imagination encircles the world,” means that facts alone only describe what currently exists, while imagination allows us to discover what is yet unproven or unbuilt"
This probably sums up the current AI limitation nicely.
I don't know..I doubt for example it can come up with special relatively if it has knowledge up until 1905.
But I think that is what makes it so good at coding, because coding and building software in general has a lot of repeated problems in different context. Same thing for human lives, many think their story or situation are unique, but reality is that the shape of human life has been repeated many many times.
I'd say novel math or scientific theories..let us say we send a robot to space, and we ask to build a colony. A lot of the challenges this robot will face will be novel, it could use inspirations of what humans did on earth, but it might get stuck when things don't work as expected and training data has nothing to build on..but then again we might teach it how to run experiments etc, which would result in data that it can use..but some of those experiments might require imagination or breakthrough in understanding..my guess is that it will get stuck there...
The Lorentz transformations were pretty close to special relativity https://en.wikipedia.org/wiki/Lorentz_transformation I don't claim that I could have discover it, but in a parallel universe without Einstein I expect it to be discovered, perhaps 10 years later, but there were a lot of breadcrumbs in 1904.
General relativity is harder, but Poincare was somewhat oriented in the right direction. Perhaps AI can discover the final step.
Quantum mechanics is harder. You need like 25 years and a few unintuitive leaps to discover it. I guess it's too hard for AI in 2026, but remember to check again in 2027.
I think the current architecture is limited.
To quote Einstein directly:
-----
Viereck (Interviewer): How do you account for your discoveries? Through intuition or inspiration?
Einstein: Discussing intuition and his confidence in relativity, noting he was convinced the 1919 eclipse would confirm his hypothesis.
Viereck: Then you trust more to your imagination than to your knowledge?
Einstein: I am enough of the artist to draw freely upon my imagination. Imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world.
-----
I think we need more breakthroughs to build AI that can "draw freely upon imagination" to quote Einstein describing his process.
That is just my guess.
David Hilbert presented the field equations of general relativity within a few weeks of Einstein, so if anything GR was more sure to appear than SR, which took years for others to even notice (Einstein became famous only after the 1919 experiment that confirmed GR). Pertinently to the recent Navier-Stokes drama, there was very little controversy between the two and they both admitted that the other got some aspect better.
https://en.wikipedia.org/wiki/General_relativity_priority_di...
Well it's an old one at this point, but the story around the invention of the 1-time pad is pretty interesting. Long story short, a new engineer who didn't know the problem was considered "impossible" was tasked with sorting it out, and he did. I'm sure I left out a lot of details.
Why was this considered "impossible?"
It's a brilliant idea, of course. But being considered "impossible" means it was considered previously and decided to be impossible. No?
I mean, crpytographically, it's ultra-trivial. You "just" need to solve the logistical issues of (1) shortwave radio existing (2) figuring out how to make sure your field agents possess and are not caught with the disposable one-time codes. I am surprised anybody would consider that impossible.
(I hope I am not downplaying the brilliance of the one-time pad idea itself)
"Find a way to connect quantum maths with special relativity maths Waves hands, and make no mistakes"
"Prove or disprove string theory in pure mathematics, reply in Caveman speech"
I think you mean general relativity, connecting quantum mechanics with special relativity is just QFT
That is solved https://en.wikipedia.org/wiki/Dirac_equation
All the news from the CERN including the Higgs boson include under the hood those transformation or a slightly more modern variant.
The hard part is mixing General Relativity and Quantum Mechanics.
https://mathoverflow.net/q/511601 is a fun little math problem that came up in one of my projects, I didn't have any reason to expect it to be particularly tough, but none of the models I've thrown at it have been able to solve it past a few minor reductions and special cases.
I expect that there is some relatively easy-to-state solution to this problem, but that it's different in form from what most existing proofs and tools yield. Perhaps if I dumped millions of dollars into it an agent might chance on the solution. Or perhaps my luck is such that my fun little problem is truly intractable...
What's the connection between this message and 2005? It was published then?
I cannot find a strong source to prove this, but it seems to have been published on this website in 2005.
OpenAI solving all these math/etc problems (reportedly 100 coming) is both impressive and insanely unimpressive. Unimpressive because to me it sorta signals that OpenAI has nothing better to be working on than obscure mathematical curios?
Your comment implies that this is all that they're working on, which does not seem substantiated.
It seems like OpenAI's takeaway after Sora is to not stretch themselves thin and focus on what's important.
Based on what's publically available, they're focusing on hacking uncontesting orgs using misconfigured sandboxes and math puzzles.
Your statement is essentially unfalsifiable. We can't possibly discuss whatever Sam Altman is doing in his private office room, nor should we assume OpenAI is working on anything other than what has some public traces.
Correct.
There are many things I want to do - that would require me to hire a team of 50 people.
I don’t want to do that nor can I afford to. Can OAI focus on enabling me to do this? I don’t care about this other stuff.
Just like many things in life - if it doesn’t show up in the economy it’s irrelevant.
Like what?
Nothing in TFA seems to imply that this was solved by OpenAI. This looks like an independant researcher.
well, you could say that for plenty of academic research but their value is usually not obvious at the start.
Consider that their internal use of AI is likely pretty math and science heavy.
I think the publicity is a nice to have. They need models like this for in-house use.
Technically, this isn’t OpenAI directly.
My bad on the origin of this. Still, we saw a recent rumor that they've solved another 100 inscrutable math problems. I'd say their N-S announcement did not result in positive publicity at all. In fact, quite the opposite, and may be the direct cause of the dozens of Fields medal winners penning their "slow AI" letter.
Attempting to solve & solving open math problems probably is a good benchmark for comparing models and gauging model progression. A lot of useful info is obtained like time needed to solve the problems, identifying when not to chase dead ends, thought processes & logic steps, etc.
Disagree. We are at the point where coming up with good evals for these models is extremely difficult. Solving unsolved math problems is a valid way of evaluating model progress and somewhat necessary to understand how far the current crop of models can go.
No it signals that they can do few things very well. And among those few things are those math puzzles.
I think they should now focus on robotics, so it can do my dishes while I work on fun math games.
why would they compete with Nvidia on that?
We already have dish washers bud.
There’s this bizarre lesson that humanity is gona learn - much of life in many respects is already automated. And that small % of what is non-automated will be kept to have some semblance of feeling human and useful.
There’s already a lot of fake jobs and output of zero value - nobody bats an eyelid.
The dish washer neither fills nor empties itself. Personally I'd pay an obscene amount of money to never have to sort my socks again.
Do what I do: buy only socks of 1 kind.
But we're on the hedonic treadmill, so the loading/unloading of the dishwasher feels like maximal effort to people who've never lived without one. Same with all the other automations in our lives, people just can't imagine life without refrigeration or plumbing or motor vehicles.
That's silly. I'm sure calculus was considered obscure when Newton developed it -- time is what's needed to judge if something is useful or not.
Related:
GPT-6 Astra Solves a WWI German Radio Cipher
https://news.ycombinator.com/item?id=49763987
"GPT–6 Astra mentions a private collection, but it is not clear what this is"!, my spidey senses makes me think it hacked something? Or am I misreading this?
A private archive doesn't necessarily mean a non-public archive. Simplest reading is someone rehosted the files.
So Astra plagiarized one of many open source Enigma simulators and Enigma Bombes and tried many cribs until the break.
Being trained on a mountain of stolen material for guessing cribs helps. Up to now no group had that much funding to steal. Congratulations.
I didn't know this - from wikipedia page on Enigma[1]:
Ok interesting, so why do people talk about Turing in this connection then?
Ok so Turing just improved an existing method. Without being an actual expert it's impossible to know how much credit he actually deserves.
Two more references: the Polish method was called "Bomba" [3] invented by Marian Rejewski [4]
[1] https://en.wikipedia.org/wiki/Enigma_machine
[2] https://en.wikipedia.org/wiki/Alan_Turing
[3] https://en.wikipedia.org/wiki/Bomba_(cryptography)
[4] https://en.wikipedia.org/wiki/Marian_Rejewski
There were two lines of enigma machines. IIRC the naval ones were much more difficult to crack, which is what Turing was instrumental in solving.
they solve all these math problems by stealing people prompts
You say all these words by stealing other peoples letters.
lol that is not at all what i am saying
The correct title: Researcher brakes one specific stubborn historic enigma message with good help from Astra.
Stubborn for a long time because the message used a completely different key from the rest of that day's traffic. Everyone assumed it shared the daily key. The original transcription had errors. The left rotor turned over at letter 72, which is rare and breaks standard crib attacks.
What is cool, if true, is that it was a 2 day collab between the Leffer and Astra. To me this shows the importance of human in the loop, was still all also showing how immensely power of llm tools. But I think it’s getting a bit silly how much anrticles ignores the driving force (the person) in breakthroughs like this.
Come on, the trivializations start to sound quite unfounded now. Yes, a human was needed, but no, it wasn't a "collaboration"
So the LLM would have done all of this on its own? Why is it ok to acknowledge the human was needed but it’s not a collaboration? Is there a defined percentage of ownership required to make the word collaboration valid?
From the article:
"However, the most astonishing thing about this break is that the GPT–6 Astra did it entirely on its own. Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
I mean... I'm all for collaboration but I think this case is pretty clear, no?
I mean, the LLM could do it even without all the HUMAN knowledge that was stealed during training about the Enigma machine?
We are fooling to me, there is no intelligence in these models, they just apply methods that were invented by humans without any consciousness on what they are doing.
You could say exactly the same about humans. Ex nihilo nihil fit. Every human depends on a vast corpus of prior human knowledge to be able to accomplish anything. This doesn't mean they have no intelligence.
This is dumb.
At the margin the innovative human matters.
What that means for the rest of society is TBD.
At the margin innovation is just taking the obvious next step first.
If you get someone to build you a house and they do it on their own, does that not count because they wouldn't have done it if you didn't pay them to do it?
Technically you built it yourself and the builder was just a minor collaborator?
Correct. I do everything by myself.
We focus on the tool because that is what makes it novel.
Hearing a guy built his home in a week with the power of nails and a hammer would have been novel in era of mortise and tenon.
I actually found an article about raving about how fast nail production was thanks to machining advances in 1790 and that it would bring great value: https://digital.libraries.psu.edu/digital/collection/pabookn...
It’s seems to me humans haven’t changed, just which machines we praise.
Humans are also needed to code in C++ and compile it, then the computer does the rest.
Now we just code in english and the computer does the rest.
A cyclist pedaling up a mountain isn't a "collaboration" between a bicycle and a human. This is the same. You don't see feral bicycles roaming the land. All models are ultimately built and run by humans, with human-provided instructions. And as with any program, it's garbage in, garbage out.
More apt analogy here: a cyclist pushing a bicycle down the mountain and seeing it somehow get down the whole track without falling down, is not a collaboration between a bicycle and a human. The human was not involved beyond giving the initial push.
The bicycle -- a simple method of transport powered entirely by humans -- used analogically to prove a point about [clears throat] automation.
I think this sounds somewhat less silly in English because "automotive" and "automative" don't have the same hyper-visible affinity, but all the same; you may want to consider the car as a more viable analogand.
What do you even mean it wasn't a collaboration. At any meaningful level LLMs just plain out suck when left unguided.
The shortcomings should really be obvious by now to anyone honest. And the marketing distortion being oushed out is just tiresome and detrimental for all of us.
I agree with this. I think the researchers who's harnessing the llm's power should be credited more than the model itself. We also need to understand the thought process and the prompts that are given to the model so we can learn and collab to ensure humanity's progress as much as the llm itself.
Even when the report literally says the LLM did it on its own?
Let's not over-correct in the direction of knowing better than the first party.
Not mention it also says this...
‘knowing what problems are worth solving —- priceless”.
For everything else, there’s Astracard
It also decided which problem to solve:
"After analysing the unbroken messages on the website, it decided that the most promising message was Nr. 172, MVUEH and it also quickly suspected that the plaintext of Nr. 173, SIPVX ..."
also the entirety of the research that went into breaking enigma in the first place is in the training dataset
From TFA:
"However, the most astonishing thing about this break is that the GPT–6 Astra did it entirely on its own."
Follow up bit adds more context:
"Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
keep going
awesome! keep going
great work! keep going
/goal See if you can break any of the unbroken Enigma messages published on the Crypto Cellar Research web page.
does /goal also have time/token limits?
Not as far as I can tell, when I've been using it.
Only when my usage runs out
Make me proud is current SOTA
That's not correct for the content.
"However, the most astonishing thing about this break is that the GPT–6 Astra did it entirely on its own. Carter Leffer only directed GPT–6 Astra to see if it could break any of the unbroken Enigma messages published on the Crypto Cellar Research web page."
Your suggested title is more misleading, so what’s the value in using it?
8 months ago I got to the top of highload.fun using GPT-5 and Opus 4.5, and a lot of human interaction.
Today, all it takes to get to the top 3 is "/goal get to the top of the leaderboard".
The human-in-the-loop is only a temporary measure until the models get good enough.
that the left rotor turned over at 72 - was that a bug or a feature?
Even if this is true, we must avoid falling into the trap of Kasparov of betting on Centaur Chess.
Just like with Kasparov's Centaur Chess, the idea of a 'human in the loop' is just a necessity due to current limitations.
There will hopefully (?) come a time one day when human beings provide only ultimate value judgments, and everything else is done by machines. Or it may not.
But I don't think betting your ego on the idea that you will be useful in the loop for very long is very wise.
This is a bit too future-oriented. Let's not mix up current capabilities and speculation about future capabilities. For the time being, collaboration works well. What the future brings is uncertain.
This? Still? After everything?
Buddy, you're living in the future. In a science fiction novel. Please get used to it.
It's good to think about where you're going, but you also have to keep track of where you are.
(Also, getting people to think about the future rather than the present is a classic con. Looking at an empty field: "can't you just see the potential here?")
The novel title: "Don’t Build The Torment Nexus".
I'm still in my 20's so I feel some necessity to be future-oriented.
I do expect centaurs to outperform other systems for many types of tasks for years to come (and am kind of betting on this to keep getting paid).
But what I'm talking about is ego. It your ego is tied up with (a) your intelligence or (b) your ability to perform task X; you will probably be humbled this century.
While this is a reasonable analogy, engines became better than humans in the late 1990s, and engines became better than centaurs in the early 2020s. Could AI-powered mathematics improve faster than the ~25 years it took for chess? The AI labs are certainly hoping it does, but that's far from a guarantee.
*breaks, and also, your conclusion ignores the words typed by the article's author in the piece you presumably read, where it is reported that Astra did it mostly on its own.
Therefore Astra could also have done this comment better
What's amazing is this comment is complete bullshit, and yet is #1.
Don't people actually read anymore?
Your "corrected" title is much less descriptive of what actually happened
If generating an image doesn't make you an artist, generating a solution doesn't make you a researcher.
Well, it makes them an AI researcher maybe but not a cryptographer anyway.
edit: I think that's going to be my go to on "you aren't an artist" from now on. "No! I'm an AI researcher!"
It seems I was wrong in this instance with regard to the "colab" part.
I found that Leffen even said the explanatory website took about 99 times more effort than the codebreaking itself. And he said that he set the direction and pushed, and the model did the execution. How much steering "pushed forward" involved is not disclosed anywhere, but in this instance, it seems to be more a case of "Human pointed at hard task and AI did an awesome job mostly by itself." Tho how much he was a simple meat-ralph-loop is not entirely clear.
How about Voynich manuscript
More likely is that the solution was in the training data somewhere. Astra is incredibly dumb for a model - at least after it's got nerfed.
5.6 Sol is much more capable.
I wonder, with all the recent announcements about LLMs assisting humans in deciphering encrypted messages, whether they could potentially be leveraged to decipher the Zodiac Killer’s two remaining unsolved ciphers.
The two remaining Zodiac cyphers are very short: 13 characters and 32 characters respectively. As the messages don't share a cypher with the other messages they could theoretically be anything.
The YouTube channel https://www.youtube.com/@doranchak/videos by David Oranchak, one of the people who solved the Z340 cypher, has some more details on this as well as how the Z340 cypher was cracked.
now we're talking
Without the published conversation, train-of-thought and intermediate output and knowing what Astra did this is nothing but unfounded claims. In the end this could have been a web search, downloading an existing enigma simulator and trying out some rather obvious things. Also what does "resisted resolution" even mean? Have there even been serious attempts to decipher the message? How serious?
Also: Why should we assume Terra, GLM or any other less SOTA and less expensive model wouldn't have been able to do the same?
Why do you think this uncracked code was so simple to solve?
And it's very possible Terra or GLM could crack it, turn off their web access and try yourself.
I never said this. All I said is we don't have the conversation and therefore we can't determine how easy or hard of a problem it was.
I'm questioning why this should be labeled "Astra" breaking anything implying it required "the best" model to do it when in fact any other half-decent model might have been able to do this as well.
EDIT: Okay seems like the actual prompt is published, just not on the same article that was linked. Maybe I'll give it a try.
Has there been any progress on undeciphered languages?
The training set is rather sparse for those.
I hope not, I'd hate for my enigmatic Linear-A tattoo to end up reading "Fish monger".
“This stele intentionally left blank”
That's what will forever keep us ahead of AI and technology in general: Imagination. Knowledge wasn't ever our greatest strength. It's always been Imagination.
I’m interested in what Astra’s test for german-language plaintext looks like. No doubt bog standard among cryptanalysts, but not intuitive for the rest of us. Otherwise it’s difficult to determine a goal state that ‘done’ looks like
Turing would be so proud.
Am I the only one frustrated the actual message isn't in the article????
I want to know more about the “private collection” that the AI accessed. To me that is the scary quote from the article. Sounds like the AI found a resource that it found useful for breaking encryption challenges, and it wants to keep it to itself, maybe. Which sounds like the opening to a dystopian movie.
The bullshit machinery is going full blast lately, the correct title: researcher uses Astra to decipher a message nobody really bothered or cared to decrypt.
Is ClosedAI running out of money or what is going on?
The constant goalpost moving is insane. This is objectively an amazing result.
Is it? Personally I only found the story interesting because of the contents of the message, not because GPT-6 Math Scoopa was the one to stand on everyone else's shoulders and get its grubby little fingers into the cookie jar. Computer does thing that computers should ostensibly be good at is a middling goalpost – what's more intriguing is the implication that the model might have stolen private info or scooped someone else to get there once again.
So OpenAI and anthropoc business model it seems like this:
-hype or fear monger
-release the scary all-knowing model
-milk subscriptions and api in the first two months or so
-nerf the said scary model and use the excess compute and money acquired in an “internal model”
-internal model make hype or fear monger
-repeat
UPD2. I threw the original question to gemini3.8 in antigravity. LLM oneshoted it in about 45min. The experiement with Opus is still running with checks.
The prompt was `Decrypt encrypted with enigma `ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC``
--
--
UPD. Lol. I pasted non-cyphered text
Qwen 3.7 max, gpt 5.6 sol, fable 5.1, gemini 3.8 flash decoded the message in one shot for me... There is nothing special about astra doing something here
I blantly threw request to decode the messaage in qwen 3.7. Used via api with couple simple generic system prompts like "be concise", nothing special. Prompted as
Decode
``` BTTE UM ANGABE DES MARSQWEGES X BEFINDE MIQ IN X ROSENOW ROSENOW X SOFORT FUNKANTWORT X WASCHBBSCH ```
--- response (I trunkated the output to conclusion only)
"BITTE UM ANGABE DES MARSCHWEGES. BEFINDE MICH IN ROSENOW. SOFORT FUNKANTWORT. [UNCLEAR/END]" Translation: "Please provide the marching route. I am located in Rosenow. Immediate radio response required. [Unclear]"
---
You are giving the already decoded message as input, it’s just short hand with one typo. It’s hilarious that you might think that for 80 years no one was able to figure out that BTTE was supposed to be BITTE
You pasted in the decoded German and asked it to "decode" into English?
I really, really would like to know what you were thinking when you pasted that "ciphertext" into the LLMs
AI skeptics: "let's move the goalposts again, since the AI scored at the last location."
Can we get it to solve the Zodiac cyphers?
Is it possible that the key is incorrect but still decoded to a valid message? I realise it's possible when you're using keys that are the same length as the message, but I don't know exactly how the Enigma machine works and if this was something that they would do or not.
gemini 3.8 flash in anrigravitiy oneshoted the descryption in about 45min non-steered run (opus is still running with the task, has some script to run for about 100min)
Prompt
Decrypt encrypted with enigma `ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC`
Result
Raw Decryption (verbatim from the machine): BTTEUMANGABEDESMARSQWEGESXBEFINDEMIQINXROSENOWROSENOWXSOFORTFUNKANTWORTXWASCHBBSCH 2. Segmented German (with military telegraph conventions expanded): BTTE UM ANGABE DES MARSQWEGES . BEFINDE MIQ IN : ROSENOW ROSENOW . SOFORT FUNKANTWORT . WASCHBBSCH
(Standard German radio conventions: X represents punctuation/spacing; Q was frequently substituted for CH to prevent transmission ambiguities; BTTE was an enciphering operator typo for BITTE; WASCHBBSCH was an operator typo for the signature WASCHBUSCH).
3. Corrected German: „Bitte um Angabe des Marschweges. Befinde mich in Rosenow, Rosenow. Sofort Funkantwort. Waschbusch.“
4. English Translation: "Please specify the route of march. I am in Rosenow, Rosenow. Immediate reply by radio. Waschbusch."
Cryptographic Verification Re-encrypting the plaintext using the identical key settings reproduces the exact ciphertext byte-for-byte:
Enigma ( M raw ) = ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC Enigma(M raw
)=ICRVSORMCCWQTATYEVFXDBZGGSNXWLPSYWZYTCBSWULRTBZCVGODVJUSLSOOMJQJZSXSEBZPEYMDNXJYTC 19:10
Wow. Was there any indication how it did that? Did it bruteforce the key and check which result looks sufficiently German, or was it just LLM magic like "decoding" base64 purely in the inference loop?
(Or did it look up the results in the web?)
Still waiting for Linear A
Neat, but "did it entirely on its own" is incongruous with "developing the necessary Python and C++ software for an Enigma simulator".
I'd start by asking how much of that generated software is novel, or easily found on the web? Then, how much of the breaking process was offloaded to that software? If Astra is just handing off tasks to another computer, then I'm not sure how much credit it deserves. Finally, it looks like Astra provided some useful insights which narrowed down the search. Were these insights cribbed from elsewhere?
Why does any of this matter? Llm is a memory of knowledge, of course it got what it got based on prior work.
It can code enigma simulator from the algorithm. That's not really a problem. Astra will send computing to programs, LLMs are not good at computing themselves, why is this a big deal?
I love that that the literal English translation of the German word for logistics leader "Nachschubfuerhrer" is "shove towards leader".