Any standard of intelligence devised before LLMs is passed by LLMs relatively easily. They do things that 10 years ago people would have said are impossible for a computer to do.
I can run claude code on my laptop with an instruction like "fix the sound card on this laptop" and it will analyze what my current settings are, determine what might be wrong, devise tests to have me gather information it can't gather itself, run commands to probe hardware for it's capabilities, and finally offer a menu of solutions, give the commands to implement the solution, and finally test that the solution works perfectly. Can you do that?
1. create a skeleton clone of frontend A, named frontend B, which is meant to be the frontend for backend project B, including the oAuth configuration
2. create the kubernetes yaml and deployment.sh, it should be available under b.mydomain.com for frontend B and run it, make sure the deployment worked by checking the page on b.mydomain.com
3. in frontend B, implement the UI for controller B1 from backend B, create the necessary routing to this component and add a link to it to the main menu, there should be a page /b1 that lists the entries, /b1/xxx to display details, /b1/xxx/edit to edit an entry and /b1/new to create one
4. in frontend B, implement the UI for controller B2 from backend B, create the necessary routing to this component and add a link to it to the main menu, etc.
etc.
All of this is done in 10 minutes. Yeah I could do all of this myself, but it would take longer.
My pocket calculator is not intelligent. Nor are LLMs.
Talk to any model about deep subjects. You ll understand what I am saying. After a while it will start going around in circles.
FFS ask it to make an original joke, and be amused..
so like your average human
> FFS ask it to make an original joke, and be amused..
let's try this one on you - say an original joke
oh, right, you dont respond to strangers prompts, thus you have agency, unlike an LLM
But by some subset of definitions my calculator is intelligent. By some subset of definitions a mouse is intelligent. And, more interestingly, by some subset of definitions a mouse is far more intelligent than an LLM.
I don't think conflating intelligence with "what a computer can do" makes much sense though. I can't calculate the X digit of PI in less than Z, I'm still intelligent (or I pretend to be).
But the question is not about intelligence, it's a red herring, it's just about utility and they (LLM's) are useful.
Yes, I have worked in small enough companies in which the developers just end up becoming the default IT help desk. I never had any formal training in IT, but most of that kind of IT work can be accomplished with decent enough Google skills. In a way, it worked the same as you and the LLM. I would go poking through settings, run tests to gather info, run commands, and overall just keep trying different solutions until either one worked or it became reasonable to give up. I'm sure many people here have had similar experiences doing the same thing in their own families. I'm not too impressed with an LLM doing that. In this example, it's functionally just improving people's Googling skills.
It works because people have answered similar questions a million times on the internet and the LLMs are trained on it.
So it will work for a while. When the human generated stuff stops appearing online, then LLMs ll quickly fall in usefulness.
But that is enough time for the people who might think that it going to last for ever to make huge investments into it, and the AI companies to get away with the loot.
Actually it is the best kind of scam...
But it's clear the LLM's have some real value, even if we always need a human-in-the-loop to prevent hallucinations it can still massively reduce the amount of human labour required for many tasks.
NFT's felt like a con, and in retrospect were a con. The LLM's are clearly useful for many things.
When a con man sells you a cheap watch for an high price, what you get is still useful—a watch that tells the time—but you were also still conned, because what you paid for is not what was advertised. You overpaid because you were tricked about what you were buying.
LLMs are useful for many things, but they’re also not nearly as beneficial and powerful as they’re being sold as. Sam Altman, while entirely ignoring the societal issues raised by the technology (such as the spread of misinformation and unhealthy dependencies), repeatedly claims it will cure all cancers and other kinds of diseases, eradicate poverty, solve the housing crisis, democracy… Those are bullshit, thus the con description applies.
* LLMs are a useful tool in a variety of circumstances.
* Sam Altman is personally incentivised to spout a great deal of hyped-up rubbish about both what LLMs are capable of, and can be capable of.
Theranos on the other hand… That was a con and the founder was prosecuted.
And again, Sam Altman has a history of deceit.
https://www.technologyreview.com/2022/04/06/1048981/worldcoi...
https://www.buzzfeednews.com/article/richardnieva/worldcoin-...
The dependency here is that if Sam Altman is indeed a con man, it is reasonable to assume that he has in fact conned many people who then report an over inflated metric on the usefulness of the stuff they just bought (people don’t like to believe they were conned; cognitive dissonance).
In other words, if Sam Altman is indeed a con man, it is very likely that most metrics of the usefulness of his product is heavily biased.
There is a finite amount of incremental improvements left between the performance of today's LLMs and the limits of human performance.
This alone should give you second thoughts on "AI doomerism".
That could also apply to LLMs, that there would be a hard wall that the current approach can’t breach.
The "walls" that stopped AI decades ago stand no more. NLP and CSR were thought to be the "final bosses" of AI by many - until they fell to LLMs. There's no replacement.
The closest thing to a "hard wall" LLMs have is probably online learning? And even that isn't really a hard wall. Because LLMs are good at in-context learning, which does many of the same things, and can do things like set up fine-tuning runs on themselves using CLI.
I didn’t say that is the case, I said it could be. Do you understand the difference?
And if it is the case, it doesn’t immediately follow that we would know right now what exactly the wall would be. Often you have to hit it first. There are quite a few possible candidates.
So far, there's a distinct lack of "wall" to be seen - and a lot of the proposed "fundamental" limitations of LLMs were discovered to be bogus with interpretability techniques, or surpassed with better scaffolding and better training.
I do think though that lack of online learning is a bigger drawback than a lot of people believe, because it can often be hidden/obfuscated by training for the benchmarks, basically.
This becomes very visible when you compare performance on more specialized tasks that LLMs were not trained for specifically, e.g. playing games like Pokemon or Factorio: General purpose LLMs are lagging behind a lot in those compared to humans.
But it's only a matter of time until we solve this IMO.
I want to see some numbers before I believe this. So far my feelings is that the best case scenario is that it reduces the time it needs to do bureaucratic tasks, tasks that were not needed anyway and could have just been removed for an even grater boost in productivity. Maybe, it seems to be automating tasks from junior engineer, tasks which they need to perform in order to gain experience and develop their expertise. Although I need to see the numbers before I believe even that.
I have a suspicion that AI is not increasing productivity by any meaningful metric which couldn’t be increased by much much much cheaper and easier means.
I don't think that's of any doubt. Even beyond programming, imo especially beyond programming, there are a great many things they're useful for. The question is; is that worth the enormous cost of running them?
NFT's were cheap enough to produce and that didn't really scale depending on the "quality" of the NFT. With an LLM, if you want to produce something at the same scale as OpenAI or Anthropic the amount of money you need just to run it is staggering.
This has always been the problem, LLMs (as we currently know them) they being a "pretty useful tool" is frankly not good enough for the investment put into them
At this point the "trick" is to scare white collar knowledge workers into submission with low pay and high workload with the assumption that AI can do some of the work.
And do you know a better way to increase your output without giving OpenAI/Claude thousands of dollars? Its morale, improving morale would increase the output in a much more holistic way. Scare the workers and you end up with spaghetti of everyone merging their crappy LLM enhanced code.
The main reason being: even SOTA AIs of today are subhuman at highly agentic tasks and long-horizon tasks - which are exactly the kind of tasks the management has to handle. See: "AI plays Pokemon", AccountingBench, Vending-Bench and its "real life" test runs, etc.
The performance at long-horizon tasks keeps going up, mind - "you're just training them wrong" is in full force. But that doesn't change that the systems available today aren't there yet. They don't have the executive function to be execs.
Opus 4.5 saved me about 10 hours of debugging stupid issues in an old build system recently - by slicing through the files like a grep ninja and eventually narrowing down onto a thing I surely would have missed myself.
If I were to pay for the tokens I used at API pricing, I'd pay about $3 for that feat. Now, come up with your best estimate: what's the hourly wage of a developer capable of debugging an old build system?
For the reference: by now, the lifetime compute use of frontier models is inference-dominated, at a rate of 1:10 or more. And API costs at all major providers represent selling the model with a good profit margin.
The 'are LLMs intelligent?' discussion should be retired at this point, too. It's academic, the answer doesn't matter for businesses and consumers; it matters for philosophers (which everyone is even a little bit). 'Are LLMs useful for a great variety of tasks?' is a resounding 'yes'.
you're lumping together two very different groups of people and pointing out that their beliefs are incompatible. of course they are! the people who think there is a real threat are generally different people from the ones who want to push AI progress as fast as possible! the people who say both do so generally out of a need to compromise rather than there existing many people who simultaneously hold both views.
I feel this framing in general says more about our attitudes to nuclear weapons than it does about chatbots. The 'Peace Dividend' era which is rapidly drawing to a close has made people careless when they talk about the magnitude of effects a nuclear war would have.
AI can be misused, but it can't be misused to the point an enormously depopulated humanity is forced back into subsistence agriculture to survive, spending centuries if not millennia to get back to where we are now.
I think that's good, but the whole "AI is literally not doing anything", that it's just some mass hallucination has to die. Gamers argue it takes jobs from artists away, programmers seem to have to argue it doesn't actually do anything for some reason. Isn't that telling?
And if AI assisted products are cheaper, and are actually good, then people will have to vote with their wallets. I think we’ve learned that people aren’t very good at doing that with causes they claim to care about once they have to actually part with their money.
Or would you prefer these things be outlawed to increase employment?
It's not really hard to see... spend your whole life defining yourself around what you do that others can't or won't, then an algorithm comes along which can do a lot of the same. Directly threatens the ego, understandings around self-image and self-worth, as well as future financial prospects (perceived). Along with a heavy dose of change scary, change bad.
Personally, I think the solution is to avoid building your self-image around material things, and to welcome and embrace new tools which always bring new opportunities, but I can see why the polar opposite is a natural reaction for many.
Unless AI is used for code (which it is, surely, almost everywhere), then Gamers don't give a damn. Also, Larian didn't use it for concept art, they used it to generate the first mood board to give to the concept artist as a guideline. And then there is Ark Raiders, who uses AI for all their VO, and that game is a massive hit.
This is just a breathless bubble, the wider gaming audience couldn't give two shits if studios use AI or not.
I know LLMs won't vanish again magically, but I wish they would every time I have to deal with their output.
I'm seeing legitimate 10x gains because I'm not writing code anymore – I'm thinking about code and reading code. The AI facilitates both. For context: I'm maintaining a well-structured enterprise codebase (100k+ lines Django). The reality is my input is still critically valuable. My insights guide the LLM, my code review is the guardrail. The AI doesn't replace the engineer, it amplifies the intent.
Using Claude Code Opus 4.5 right now and it's insane. I love it. It's like being a writer after Gutenberg invented the printing press rather than the monk copying books by hand before it.
It’s like arguing that the piano in the room is out of tune and not bothering to walk over to the piano and hit its keys.
Yes, the technology is interesting and useful. No, it is not a “10x” miracle.
They don't have time to check more stuff as they are busy with their life.
People who did check the stuff don't have time in life to prove to the ones that argue "in exactly whatever the person arguing would find useful way".
Personally like a year ago I was the person who tried out some ChatGPT and didn't have time to dabble, because all the hype was off putting and of course I was finding more important and interesting things to do in my life besides chatting with some silly bot that I can trick easily with trick questions or consider it not useful because it hallucinated something I wanted in a script.
I did take a plunge for really a deep dive into AI around April last year and I saw for my own eyes ... and only that convinced me. Using API where I built my own agent loop, getting details from images, pdf files, iterating on the code, getting unstructured "human" input into structured output I can handle in my programs.
*Data classification is easy for LLM. Data transformation is a bit harder but still great. Creating new data is hard so like answering questions where it has to generate stuff from thin air it will hallucinate like a mad man.*
Data classification like "is it a cat, answer with yes or no" it will be hard for latest models to start hallucinating.
Do I now get the right to talk badly about all LLM coding, or is there another exercise I need to take?
The LLM marketing exploits fear and sympathy. It pressures people into urgency. Those things can be shown and have been shown. Whether or not the actual LLM based tools genuinely help you has nothing to do with that.
Of course it is a little more nuanced than this and I would agree that some of the marketing hype around AI is overblown, but I think it is inarguable that AI can provide concrete benefits for many people.
Yes, yes you can. As I’ve mentioned elsewhere on this thread:
> When a con man sells you a cheap watch for an high price, what you get is still useful—a watch that tells the time—but you were also still conned, because what you paid for is not what was advertised. You overpaid because you were tricked about what you were buying.
LLMs are being sold as miracle technology that does way more than it actually can.
It may be extremely dangerous to release. True. Even search engines had the potential to be deemed too dangerous in the nuclear pandoras box arguments of modern times. Then there are high-speed phishing opportunities, etc.
It may be an essential failure to miss the boat. True. If calculators were upgraded/produced and disseminated at modern Internet speeds someone who did accounting by hand would have been fired if they refused to learn for a few years.
Its communication builds an unhealthy relationship that is parasitic. True. But the Internet and the way content is critiqued is a source of this even if it is not intentionally added.
I don't like many people involved and I don't think they will be financially successful on merit alone given that anyone can create a LLM. But LLM technology is being sold by organic "con" that is how all technology such as calculators end up spreading for individuals to evaluate and adopt. A technology everyone is primarily brutally honest about is a technology that has died because no one bothers to check if the brutal honesty has anything to do with their own possible uses.
They literally are. Sam Altman has literally said multiple times this tech will cure cancer.
How do I know? Because I am testing it, and I see a lot of problems that you are not mentioning.
I don’t know if you’ve been conned or you are doing the conning. It’s at least one of those.
That's not how book printing works and I'd argue the monk can far more easy create new text and devise new interpretations. And they did in the sidelines of books. It takes a long time to prepare one print but nearly just as long as to print 100 which is where the good of the printing press comes from. It's not the ease of changing or making large sums of text, it's the ease of reproducing and since copy/paste exist it is a very poor analogue in my opinion.
I'd also argue the 10x is subject/observer bias since they are the same person. My experience at this point is that boilerplate is fine with LLMs, and if that's only what you do good for you, otherwise it will hardly speed up anything as the code is the easy part.
How do you avoid this turning into spaghetti? Do you understand/read all the output?
The line becomes a lot blurrier when you work on non trivial issues.
A Django app is not particularly hard software, it's hardly software but a conduit from database to screens and vice-versa; which is basic software since the days of terminals. I'm not judging your job, if you get paid well for doing that, all power to you.
What I'm raising though is the fact that AI is not that useful for applications that aren't solving what has been solved 100 times before. Maybe it will be, some day, reasoning that well that it will anticipate and solve problems that don't exist yet. But it will always be an inference on current problems solved.
Glad to hear you're enjoying it, personally, I enjoy solving problems, not the end result as much.
Also, almost all problems are composite problems where each part is either prior art or in itself somewhat trivial. If you can onboard the LLM onto the problem domain and help it decompose then it can tackle a whole lot more than what it has seen during pre- and post-training.
Then why is half of the big tech companies using Microsoft Teams and sending mails with .docx embedded in ?
Of course marketing matters.
And of course the hard facts also matters, and I don't think anybody is saying that AI agents are purely marketing hype. But regardless, it is still interesting to take a step back and observe what marketing pressures we are subject to.
That’s exactly what a con is: selling you something as being more than what it actually is. If you agree it’s overhyped by its sellers, you agree it’s a con.
> Current agents can do around 70% of coding stuff I do
LLMs are being sold as capable of significantly more than coding. Focusing on that singular aspect misses the point of the article.
Hm... is it wrong to think like this?
> This has, of course, not happened.
This is so incredibly shallow. I can't think of even a single doomer, who ever claimed that AI will destroy us by now. P(doom) is about the likelihood of it destroying us "eventually". And I haven't seen anything in this post or in any recent developments to make my reduce my own p(doom), which is not close to zero.
Here are some representative values: https://pauseai.info/pdoom
And that's the anthropic fallacy. In the worlds where it has happened, the author is dead.
Though I personally hope that we'll have enough of a warning to convince people that there is a problem and give us a fighting chance. I grew up on Terminator and would be really disappointed if the AI kills me in an impersonal way.
What parallel world are they living in? Every single online platform has been flooded with AI generated content and had to enact counter measures, or went the other way, embraced it and replaced humans with AI. AI use in scams has also become common place.
Everything they warned about with the release of GPT‑2 did in fact happen.
mossTechnician•1h ago
But they don't. Instead, "AI safety" organizations all appear to exclusively warn of unstoppable, apocalyptic, and unprovable harms that seem tuned exclusively to instill fear.
ltbarcly3•1h ago
Xss3•1h ago
das_keyboard•1h ago
So there will be laws because not everyone can be trusted to host and use this "dangerous", new tech.
And then you have a few "trusted" big tech firms forming an oligopoly of ai, with all of the drawbacks.
iNic•1h ago
mossTechnician•1h ago
iNic•21m ago
The problem is not that no one is trying to solve the issues that you mentioned, but that it is really hard to solve them. You will probably have to bring large class action law suits, which is expensive and risky (if it fails it will be harder to sue again). Anthropic can make their own models safe, and PauseAI can organize some protests, but neither can easily stop grok from producing endless CSAM.
[1] https://www.anthropic.com/news/protecting-well-being-of-user...
[2] https://www.anthropic.com/research/team/societal-impacts
[3] https://pauseai.info/risks
rl3•1h ago
ACCount37•57m ago
The catastrophic AI risk isn't "oh no, people can now generate pictures of women naked".
mossTechnician•42m ago
In a vacuum, I agree with you that there's probably no harm in AI-generated nudes of fictional women per se; it's the rampant use to sexually harass real women and children[0], while "causing poor air quality and decreasing life expectancy" in Tennessee[1], that bothers me.
[0]: https://arstechnica.com/tech-policy/2026/01/x-blames-users-f...
[1]: https://arstechnica.com/tech-policy/2025/04/elon-musks-xai-a...
ACCount37•6m ago
The whole thing with "AI polluting the neighborhoods" falls apart on a closer examination. Because, as it turns out, xAI put its cluster in an industrial area that already has: a defunct coal power plant, an operational steel plant, and an operational 1 GW grid-scale natural gas power plant that powers the steel plant - that one being across the road from xAI's cluster.
It's quite hard for me to imagine a world where it's the AI cluster that moves the needle on local pollution.