No they're not. They're starving, struggling to find work and lamenting AI is eating their lunch. It's quite ironic that after complaining LLMs are plagiarism machines, the author thinks using them for translation is fine.
"LLMs are evil! Except when they're useful for me" I guess.
> "They are robots. Programs. Fancy robots and big complicated programs, to be sure — but computer programs, nonetheless."
This is totally misleading to anyone with less familiarity with how LLMs work. They are only programs in as much as they perform inference from a fixed, stored, statistical model. It turns out that treating them theoretically in the same way as other computer programs gives a poor representation of their behaviour.
This distinction is important, because no, "regurgitating data" is not something that was "patched out", like a bug in a computer program. The internal representations became more differentially private as newer (subtly different) training techniques were discovered. There is an objective metric by which one can measure this "plagiarism" in the theory, and it isn't nearly as simple as "copying" vs "not copying".
It's also still an ongoing issue and an active area of research, see [1] for example. It is impossible for the models to never "plagiarize" in the sense we think of while remaining useful. But humans repeat things verbatim too in little snippets, all the time. So there is some threshold where no-one seems to care anymore; think of it like the % threshold in something like Turnitin. That's the point that researchers would like to target.
Of course, this is separate from all of the ethical issues around training on data collected without explicit consent, and I would argue that's where the real issues lie.
The larger, and I'd argue more problematic, plagiarism is when people take this composite output of LLMs and pass it off as their own.
https://arxiv.org/abs/2404.01019
At the frontier of science we have speculations, which until proper measurements become possible, are unknown to be true or false (or even unknown to be equivalent with other speculations etc. regardless of their being true or false, or truer or falser). Once settled we may call earlier but wrong speculations as "reasonable wrong guesses". In science it is important that these guesses or suspicions are communicated as it drives the design of future experiments.
I argue that more important that "eliminating hallucinations" is tracing the reason it is or was believed by some.
With source-aware training we can ask an LLM to give answers to a question (which may contradict each other), but to provide the training-source(s) justifying emission of each answer, instead of bluff it could emit multiple interpretations and go like:
> answer A: according to school of thought A the answer is that ... examples of authors and places in my training set are: author+title a1, a2, a3, ...
> answer B: according to author B: the answer to this question is ... which can be seen in articles b1, b2
> answer ...: ...
> answer F: although I can't find a single document explaining this, when I collate the observation x in x1, x2, x3; observation y in y1,y2, ... , observation z in z1, z2, ... then I conclude the following: ...
so it is clear which statements are sourced where, and which deductions are proper to the LLM.
Obviously few to none of the high profile LLM providers will do this any time soon, because when jurisdictions learn this is possible they will demand all models to be trained source-aware, so that they can remunerate the authors in their jurisdiction (and levy taxes on their income). What fraction of the income will then go to authors and what fraction to the LLM providers? If any jurisdiction would be first to enforce this, it would probably be the EU, but they don't do it yet. If models are trained in a different jurisdiction than the one levying taxes the academic in-group citation game will be extended to LLMs: a US LLM will have incentive to only cite US sources when multiple are available, and a EU trained LLM will prefer to selectively cite european sources, etc.
I can't imagine why someone would want to openly advertise that they're so closed minded. Everything after this paragraph is just anti-LLM ranting.
Like look at our brains. We know decently well how a single neuron works. We can simulate a single one with "just a computer program". But clearly with enough layers some form of complexity can emerge, and at some level that complexity becomes intelligence.
It isn’t a given that complexity begets intelligence.
The suspicion is that they are good at predicting next-token and not much else. This is still a research topic at this point, from my reading.
They're obviously intelligent in the way that we judge intelligence in humans: we pay attention to what they say. You ask them a question about an arbitrary subject, and they respond in the same way that an intelligent person would. If you don't consider that intelligence, then you have a fundamentally magical, unscientific view of what intelligence is.
Not GP, but... the author said explicitly "if you believe X you should stop reading". So I did.
The X here is "that the human mind can be reduced to token regurgitation". I don't believe that exactly, and I don't believe that LLMs are conscious, but I do believe that what the human mind does when it "generates text" (i.e. writes essays, programs, etc) may not be all that different from what an LLM does. And that means that most of humans's creations are also the "plagiarism" in the same sense the author uses here, which makes his argument meaningless. You can't escape the philosophical discussion he says that he's not interested in if you want to talk about ethics.
Edit: I'd like to add that I believe that this also ties in to the heart of the philosophy of Open Source and Open Science... if we acknowledge that our creative output is 1% creative spark and 99% standing on the shoulders of Giants, then "openness" is a fundamental good, and "intellectual property" is at best a somewhat distasteful necessity that should be as limited as possible and at worst is outright theft, the real plagiarism.
I would say the exact same about you, rejecting an absolutely accurate and factual statement like that as closed minded strikes me as the same as the people who insist that medical science is closed minded about crystals and magnets.
I can't imagine why someone would want to openly advertise they think LLMs are actual intelligence, unless they were in a position to benefit financially from the LLM hype train of course.
I am not ready to say that "LLMs are actual intelligence", and most of their publically visible uses seem to me to be somewhere between questionable and ridiculous.
Nevertheless, I retain a keen ... shall we call it anti-skepticism? ... that LLMs, by modelling language, may have accidentally modelled/created a much deeper understanding of the world than was ever anticipated.
I do not want LLMs to "succeed", I think a society in which they are common is a worse society than the one in which we lived 5 years ago (as bad as that was), but my curiosity is not abated by such feelings.
Should we consider it our equal or superior to us ? Should we give it the reigns of politics if it’s superior in decision making ? Or maybe the premise is « given all the knowledge that exists coupled with a good algorithm, you look/are/have intelligence » ? In which case intelligence is worthless in a way. It’s just a characteristic, not a quality. Which makes AI fantastic tools and never our equal ?
Come on. If you are actually entertaining the idea that LLMs can possibly be intelligent, you don't know how they work.
But to take your silly question seriously for a minute, maybe I might consider LLMs to be capable of intelligence if they were able to learn, if they were able to solve problems that they weren't explicitly trained for. For example, have an LLM read a bunch of books about the strategy of Go, then actually apply that knowledge to beat an experienced Go player who was deliberately playing unconventional, poor strategies like opening in the center. Since pretty much nobody opens their Go game in the center (the corners are far superior), the LLM's training data is NOT going to have a lot of Go openings where one player plays mostly in the center. At which point you'll see that the LLM isn't actually intelligent, because an intelligent being would have understood the concepts in the book that you should mostly play in the corners at first in order to build territory with the smallest number of moves. But when faced with unconventional moves that aren't found anywhere on the Internet, the LLM would just crash and burn.
That would be a good test of intelligence. Learning by reading books, and then being able to apply that knowledge to new situations where you can't just regurgitate the training material.
It's not being closed-minded. It's not wanting to get sea-lioned to death by obnoxious people.
Here's what sea-lioned means to me:
I say something.
You accuse me of sea-lioning.
I have two choices: attempt to refute the sea-lioning, which becomes sea-lioning, or allowing your accusation to stand unchallenged, which appears to most people as a confirmation of some kind that I was sea-lioning.
It is a nuclear weapon launched at discussion. It isn't that it doesn't describe a phenomena that actually happens in the world. However, it is a response/accusation to which there is never any way to respond to that doesn't confirm the accusation, whether it was true or not.
It is also absolutely rooted in what appears to me to be a generational distinction: it seems that a bunch of younger people consider it to be a right to speak "in public" (i.e in any kind of online context where people who do not know you can read what you wrote) and expect to avoid a certain kind of response. Should that response arise? Various things will be said about the responder, including "sea-lioning".
My experience is that people who were online in the 80s and 90s find this expectation somewhere between humorous and ridiculous, and that people who went online somewhere after about 2005 do not.
Technologically, it seems to reflect a desire among many younger people for "private-public spaces". In the absence of any such actual systems really existing (at least from their POV), they believe they ought to be able to use very non-private public spaces (facebook, insta, and everything else under the rubric of "social media") as they wish to, rather than as the systems were designed. They are communicating with their friends and the fact that their conversations are visible is not significant. Thus, when a random stranger responds to their not-private-public remarks ... sea-lioning.
We used to have more systems that were sort-of-private-public spaces - mailing lists being the most obvious. I sympathize with a generation that clearly wants more of these sorts of spaces to communicate with friends, but I am not sympathetic to their insistence that corporate creations that are not just very-much-non-private-public spaces but also essentially revenue generators should work the way they want them to.
Because humans often anthropomorphize completely inert things? E.g. a coffee machine or a bomb disposal robot.
So far whatever behavior LLMs have shown is basically fueled by Sci-Fi stories of how a robot should behave under such and such.
But I agree that it is self limiting to not bother to consider the ways that LLM inference and human thinking might be similar (or not).
To me, they seem do a pretty reasonable emulation of single- threaded thinking.
Possibly start with something like: https://transformer-circuits.pub/2025/attribution-graphs/bio...
> Pariyatti’s nonprofit mission, it should be noted, specifically incorporates a strict code of ethics, or sīla: not to kill, not to steal, not to engage in sexual misconduct, not to lie, and not to take intoxicants.
Not a whole lot of Pali in most LLM editorials.
I must remember to add this quality guarantee to my own software projects.
My software projects are also uranium-free.
are you being serious with this one
And there will be more compute for the rest of us :)
40 years?
Virtually nobody cares about this already... today.
(I'm not refuting the author's claim that LLMs are built on plagiarism, just noting how the world has collectively decided to turn a blind eye to it)
I can bang smooth rocks to get sharper rocks; that doesn't make sharper rocks more intelligent. Makes them sharper, though.
Which is to say, novel behavior != intelligence.
We're talking about LLMs that you can talk to, and which for the most part respond more intelligently than perhaps 90% of HN users (or 90% of people anywhere).
Announcing that one line of the piece made you mad without providing any other thought is not very constructive.