Machine translations are often brought up as a gotcha whenever I criticize LLMs. It's worth pointing out two things: Machine translations existed decades before LLMs, and yes, machine translations are useful. However: I would never in my life read a machine translated book. Understanding what a social media post is talking about in rough terms? Sure. Literature? Absolutely not. Hell, have you ever seen machine translated subtitles? It's absolute garbage.
I have the impression that primarily anglophone people don't read as much translated literature, because so much good literature already exists in their language, so this issue may not be as familiar within that demographic. As someone who did not grow up anglophone, I can tell you there is a world of difference between a good and a bad translation even when done by humans. Machine translations are not even on the scale.
From what I've observed, people who claim that LLMs can replace artists don't understand art, people who claim that they can replace musicians don't understand music, people who claim that they can replace writers don't understand literature, and people who claim they can replace translators don't rely on translations. If I had a button that would erase LLMs from the world but it would take machine translations away (which is a false dichotomy anyway), I would absolutely still press it.
Technology is not inevitable. We've decided not to have asbestos in our walls, lead in our pipes, or carginogenic chemicals in our food. (If you're going to argue that it's not everywhere, where would you rather live?) We could just not do LLMs. It's allowed.
@Gargron It is a technology that humanity has been seeking for a long time. At least since the 1950s, with Turing and his colleagues.
@df No, this is marketing. OpenAI, Google, Anthropic &co want you to believe that what they're doing is artificial intelligence. My professional opinion is that LLMs are a dead end technology to creating actual intelligence. And if any of those companies did create actual intelligence for the purposes they pursue, it would be slavery, for which I cannot advocate.
@Gargron LLMs are not exclusively a product of large corporations or just marketing. Much of the research and development also takes place in open source and academic communities. The codes for these LLMs are public and can be audited or run locally. Furthermore, I argue that serious ethical reflection is necessary, but prohibition is not the way forward.
@df
Consciously not using something ≠ prohibition
Edit: Also, who cares who worked/ envisioned or works on this now? If you think about LLMs enough, you will likely see enough good arguments about the resource waste, centralization of power and multiplication of slop which describe LLMs. We lived without it before and we can live without it in future times.
@df @Gargron Academics may study LLMs out in the open, but I don't think academia has been able to produce LLMs whose outputs are sufficiently marketable compared to the current commercially available ones. Because the first "L" ("large") is - in our current, limited understanding - crucial for the verisimilitude of the synthetic text, and only corporations (and governments, but they mostly haven't gotten to this yet) have the scale to get large enough for that so far.

@joshuagrochow and the lack of moral compass or publicly stated ethicals standards that would allow university employees to steal large enough sets. small sets of text are read and understood by humans who can, far more efficiently, apply appropriate prior written and other formats of source material to a specific use case.

programming a calculator only makes reasonable sense if the computation requires enough repetition to warrant the resources used in building it, or it's a closed set without novelty... like, for example, a numerical calculator. ; )

edited for typos and clarity: it was killing me, apologies for the notification disruption.

@df @Gargron

@df @Gargron

The code for the LLM interpreter is relatively simple, and bears the same relationship to the actual LLM as the C compiler does to an operating system. The models are the real software and the ones big and complex enough to be useful are the product of large corporations and mass copyright violation.

@Gargron they'll never create intelligence because intelligence requires will and they do not understand will. they dont even posses one of their own: their own behaviour is driven by feelings and shaped by a commercial playbook. there is zero chance they will ever create intelligence.

@Gargron @df

> My professional opinion is that LLMs are a dead end technology to creating actual intelligence.

Also they're sucking all the oxygen out of the room and choking off any research that might NOT be a dead end.

@Gargron @df
Yes. The flowchart has three boxes:

1. Create LLM
2. Then a miracle occurs
3. Profit from AGI !!!

The companies pushing so-called "AI" have completed step 1. Some of them try to tell us that they've nearly got a handle on step 2, but that's just an attempt to swindle more investors. There is literally NOTHING that fits in the hole of step 2.

@df @Gargron

Transformers are neural networks.

LLMs are transformers wrapped in some Python scripting.

Every neural network can be accurately represented as an Excel sheet, even if it ends up having billions of cells.

Since it's just addition and multiplication, the model is fully deterministic. Same input, same output. Not intelligent.

It's Python code that does probabilistic sampling of the output. It's just a few lines of well-understood math plus a dice roll. Again, not intelligent.

@df @Gargron To be clear, “Python” is a placeholder language, it can be Rust, or it can be a GPU shader, and it changes nothing.

@patrys @df @Gargron does determinism imply non-intelligence?
If you hooked up the computer to a Geiger counter for true random noise and used that to modulate the output, would that have any bearing on its intelligence?

Or from the other side, what makes you think our brains are non deterministic, and why does that make us more intelligent than if the exact same history and sense-data always produced the same response?

@FishFace @df @Gargron If it’s deterministic, it can be unrolled into a giant lookup table. Did we kill phone books because they were on the verge of achieving AGI?

To me, intelligence implies a lot of things, like being able to form higher-order abstractions, learn, and thus remember things (no, being passed your “memories” as part of every prompt does not count). It also implies being curious.

@patrys @df @Gargron given that the lookup table would generally be infinite, I don't even see what that would have to do with anything. What about the Geiger counter?

I don't think those things are really needed for human-like intelligence, and something like curiosity can easily be simulated by a rules-based system.

@FishFace @df @Gargron No, you got it wrong. The model itself can be unrolled into a finite lookup table. The only random part is which word you take from the few options in the resulting row.
@patrys a computable function can generally produce infinitely many different outputs. You're still not saying why a non-deterministic part affects intelligence.
@FishFace It generates one token at a time, which makes it impossible to formulate higher-order abstractions that are not already baked into the weight matrix. I said it in another answer, not being able to learn disqualifies it as intelligence.

@patrys LLMs are intelligent only in the sense of pattern recognition; that is, they possess logical intelligence. However, some psychologists argue that there are multiple intelligences that cannot be reduced to logic, nor are LLMs capable of possessing them. See psychologist Howard Gardner.

@FishFace @Gargron

@df @FishFace @Gargron This pattern recognition is an artifact of the training process, not something that occurs at inference time. It’s like having termites dig some tunnels in an earth mound, then removing the termites, pouring aluminum into the mound, and attributing the resulting intricate shapes to the intelligence of the mound. The patterns it carries are from human artifacts used as input for the model before its weights settled.

@patrys Undoubtedly, LLMs in this regard end up being mirrors of who we are, reflecting our biases, our prejudices, and our worldviews. That is why they are not innocuous tools and why #ethics and regulation of #AI are necessary.

@FishFace @Gargron

@FishFace @patrys @df @Gargron

"Or from the other side, what makes you think our brains are non deterministic"

Us having free will/being non-deterministic is pretty much the base assumption we all operate on to even be able to function as humans. That of course doesn't mean that it's automatically true, but it makes the question of why do you think your brain is non-deterministic a no-brainer to answer: because we can't help but perceive ourselves as such.

@frog_reborn @FishFace @df @Gargron The very fact that you can read and mid-sentence learn something that changes your perception of the world means that you have brain plasticity that no neural network possesses. It’s deterministic AND rigid because training and inference happen separately.
@patrys you're talking about differences between brains and neural networks that exist, but still not arguing the philosophical point about why that is relevant to intelligence.

@Gargron

LLMs are Shannon 1948 as far as the theory goes (building on Markov, but adding computer technology). With some compression techniques.

But I think you're talking about something else entirely, not purely syntactical.

@df @Gargron No, it is a fake, an emulation of what we have been seeking but not the real thing.
@Gargron while all your examples are 100% valid, I seriously question whether we would be able to manage to do that today. With the utter shambles most democracies are in currently, multi-national Corporations can run roughshod on environmental protection, worker safety, child protection and just about everything that past generations fought hard for.

@DJGummikuh

imagine for a moment, the billionaires have been beheaded and the yachts sunk into the sea. the value in the output of workers 100% reinvested into local communities. all of it. none for colonial masters far away. the 20 hour work weeks and all human workers hands full of the satisfaction their efforts are meaningful... no more busy work for shareholders to skim value out of. only meaningful work. custom artisanal everything. housewares repaired by local handicrafters. clothes sewn and tailored to each body. homes and townhomes and communal living spaces built and maintained by cooperative owners. neighboring towns and regions and nations translating with loving care between the communities of meaning... interconnected with care. 💜

@Gargron

@melioristicmarie

And that lasts 1-2 generations before new people who don't understand the problems that lead their parents to create the paradise chafe under their constraints and begin changing the system to something its originators wouldn't like, this creating conflict, diversity of thought, and continuing the cycle of history.

See: reality.

@DJGummikuh @Gargron I'm sure the oldschool labor activism methods would still work.
@DJGummikuh @Gargron I would argue that LLMs shouldn’t require special regulation, just no exemptions from ordinary regulation. A lawyer who files a specious brief full of fake citations should be sanctioned the same regardless of whether an LLM wrote it.

@Gargron

Machine vs. Human translation of fiction is an excellent analogy. Good translation involves an understanding of complicated material in an intuitive and nuanced way, and conveying those subtleties cleverly using equally complex forms in the target language while retaining the beauty of the writing. It involves much higher level thought than what LLMs do.

Likewise software engineering is much more complex and involves higher level thinking than prompted LLM code generation.

@Gargron You sound like me arguing against the inevitability of mass use of the cell phone.

I never understood why we gave up crystal clear audio, a two way simultaneous connection (yes, both parties could talk at the same time and hear wha5 the other had to say), and phone books for unintelligible garbled speak, dropped calls, delays, and no way to look up the damn phone number.

@HappytoBe @Gargron You had crystal clear audio on your landlines?

We never had that (I'm vaguely jealous, it was memorably trash). Even early cellphones were very comparable (current ones are much better, the most early ones I never got exposed to, too expensive).

and no way to look up the damn phone number.

I'm not sure if the harassment potential is why no one was interested in reimplementing it or if it was some manner of walled garden plans.

@Gargron we also had Concorde but it wasn’t economically viable. I mention that because I find that economic arguments seem to be heard more readily than moral arguments. (I often find that moral arguments induce temporary deafness in pro-AI people.)

@benedictc @Gargron imagine the cost of the subscription if all of those companies worked with real money and had to turn a profit from the start.

Imagine that they had to pay real copyright fees for all the content used in training the models.

Imagine that any of the illegal uses of the training data and the people that died using their products had meaningful consequences in court.

Imagine that they had to pay the full tax, the full price of the services that they use.

@benedictc @Gargron Concorde wasn't morally viable either, both in terms of passenger safety and damage to the environment.

@Gargron if asbestos was invented last year it would be inevitable, I'm afraid.

When almost all legislative power has been captured by corporatism there's not much hope we could outlaw such poisons.

@qwazix @Gargron Well, the world's no better for having you in it, is it? You comletely missed the message of the top post.
@khleedril it's not. But it seems it is a little worse for having you. And you missed the message of my post.

@Gargron It's hard to put the brakes on advances, like the Ghost Shirt Society finds out at the end of Vonnegut's Player Piano.

I heard an interview with a professor yesterday who wrote a book on the benefits of keeping cash alive and not relying completely on digital payment systems. He suggested using cash at least once a week. Maybe people will be able to do that with AI - limit their use and rely on their own brains at least some of the time. https://blogs.bu.edu/zagorsky/

Prof. Jay Zagorsky | Economist Advocating for Using Cash

@KerryMitchell @Gargron I'm still waiting on my bank letting me do withdrawals & deposits by post/mail (this was a thing in some places, a long time ago).

I'm not setting foot in their COVID-loving plaguebearer environment if I can help it.
@KerryMitchell @Gargron Saying that it's hard is not the same as saying that it's impossible.
@Gargron  I could not agree more

@Gargron

failed technologies, like Zeppelin

@Gargron The problem is that the pieces of shit peddling LLMs have convinced the political class that it's a race to technological supremacy and that any nation that bans them will be left behind. When in reality they're more like opium.
@Gargron to be fair, those in power would like to normalize lead and asbestos and so forth, because capitalism never likes to lose a business model
@Gargron Much like lead, it makes people dumber. Which might be what certain people want.
@Gargron The only people I hear saying it will replace artists are salespeople and the fearful. Beethoven broke fortepianos because they couldn't keep up with what he heard in his head. The purists called it fake. He didn't care, he kept composing and making. Every generation has this fight. The tools change, the argument doesn't. AI won't replace artists any more than the piano replaced composers. See doomscroll.fm, this is my "AI art" running on local inference. This ain't replacing anyone...
@[email protected] Als Blei und Asbest eingeführt wurden, war er deren Giftigkeit nicht bekannt. Insofern war es also keine Entscheidung. Bei LLMs wissen wir, dass sie giftig sind.

@Gargron yes. That's truth. But there is something over the good/health reason, this is: big-business earning money. Fossil fuels seems to be not the best, but it earns money for the biggest.
So i't a bit like disarmament - ok... ALL we will have AtomBombs, but we are not going to use them...
This same will be with LLM? This is actually a new weapon.

Stop producing weapons! They kill us all.

Am I being overly optimistic? Well, perhaps.

The US’s asbestos U-turn: why the Environmental Protection Agency is reconsidering its ban

Why asbestos was banned and why the US is reconsidering the ban.

The Conversation
@Gargron it has always been possible to make some money with bad translations (or bad code, etc.) long before LLMs. Now, it is possible to make much more money with them thanks to LLMs. So of course LLMs are here to stay.
@Gargron Regulations stop a regular person from buying asbestos, or lead pipes, or tainted food, sure. But any regular person can use the ubiquitous availability of computing to train an LLM. How do you stop that? How do you ban LLMs while still allowing machine learning, which is used in so many areas? It would be as easy as piracy is today to get around.

@astra @Gargron
> any regular person can use the ubiquitous availability of computing to train an LLM.

Nnnnnoooooo?
Like, why do you think AI companies build these huge data centers that consume this much electricity?

@art_codesmith @Gargron
yes, here's a random example of consumer hardware used to train an LLM at home
sabareesh.com/posts/llm-rig/
plenty more if you search
All You Need is 4x 4090 GPUs to Train Your Own Model

How I built an ML rig for training LLMs locally, exploring hardware choices, setup tricks, and lessons learned along the way.

Life and AI
@astra @Gargron
Let me get this straight.
This is a rig that requires four high-powered GPUs and server hardware to train 500M to 1B tokens models.
This blog doesn't even go into how and where they acquired data. It has no evaluation of the resulting model.
This is a toy.
@astra @Gargron Also the article reads like it was written by ChatGPT so I'm not inclined to actually believe the author.