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.
"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.
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.
*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
> 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."
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?
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?
"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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
> 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.
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...
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
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.
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.
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.
>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.
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.
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’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
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.
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.
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...
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.
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.
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)
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 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.
"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?
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.
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.
> 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).
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'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 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.
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.
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.
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?
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.
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.
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.
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.
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?
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
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.
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.
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]
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.
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.
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.
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.
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.
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.
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.
"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."
awesome! keep going
great work! keep going
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.
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...
> We are still analysing the GPT–6 Astra logs to see exactly how it executed the break.
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.
Therefore Astra could also have done this comment better
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."
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.
Technically you built it yourself and the builder was just a minor collaborator?
Now we just code in english and the computer does the rest.
"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?
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.
At the margin the innovative human matters.
What that means for the rest of society is TBD.
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.
Edit: Found it from here: https://mvueh-enigma-solved.carterl.chatgpt.site/
(Is it possible that this is a misreported detail? It feels like a singular ROSENOW would be an equally effective crib)
> it suspected that the plaintext of Nr. 173, SIPVX, might be related to the plaintext of the unbroken MVUEH message
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.
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.
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.
(apologies for my broken learner German, I decided not to use a translator).
https://www.youtube.com/watch?v=JsBZOcqZerk
And then I come to hackernews and well, not quite, but I'm sure that one will be done shortly too.
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.
I think the more accurate description of what's happening is that access to expertise is becoming commodified.
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".
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.
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!
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...
So not any different from right now.
>definitely not available to humanity as a whole.
[taps on forehead meme]
The whole of humanity can have it available, if there is a whole lot less humanity.
Way, way more concentration of wealth and power
Why?
> But also, whatever benefits are unlocked will be owned mostly by a small group of individuals, definitely not available to humanity as a whole.
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
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.
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.
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 subscribe to the "humans are special" rhetoric, in which case I'm - maybe - sorry to say the feeling will only intensify.
Without the human intellect to emulate, LLMs would be nothing.
Prob because their life sucks.
And used to build the LLMs of today. We'll see how that evolves once LLMs have to feed LLMs with their own "intellect".
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'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.
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...
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...
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.
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.
https://en.wikipedia.org/wiki/General_relativity_priority_di...
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.
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/
"Prove or disprove string theory in pure mathematics, reply in Caveman speech"
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.
I think you mean general relativity, connecting quantum mechanics with special relativity is just QFT
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)
this is not moving the goalposts, this is try to understand what this tech truly able and not able to do.
Reminds of what Einstein said, imagination is more important than knowledge..might be his deepest insight ever.
"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.
Being trained on a mountain of stolen material for guessing cribs helps. Up to now no group had that much funding to steal. Congratulations.
-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
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).
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.
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.
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 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?
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.
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.
I think the publicity is a nice to have. They need models like this for in-house use.
Technically, this isn’t OpenAI directly.
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.
Is ClosedAI running out of money or what is going on?
Then see if it can come up with E=mc^2
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
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.
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)
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?
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.
> 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.
> 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]
[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
GPT-6 Astra Solves a WWI German Radio Cipher
https://news.ycombinator.com/item?id=49763987
5.6 Sol is much more capable.
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.
Complete this sentence: "You can solve world hunger by..."
Intelligence is required to finish sentences. It's not just a Markov chain.
*This un actionable summary of existing discourse. The real world doesn’t produce traces or take HTTP requests.
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.
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.
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 internet was pretty important afterall even with a bubble.
I think the quote above is best as written, with a big emphasis on the "if"
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%.
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.
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?
[1] https://www.prinzai.com/p/gpt-6-astra-solves-a-wwi-german-ra...
What? Why? This has been my bar for my entire life, and I've never been bored for a single second.
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).
So like half of all useful human inventions are to you not interesting just because it happened by dumb luck?
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!"
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.
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.
> 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.
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.