A fair point but often over stated, I feel. And it overlooks something -
Language itself encodes meaning. If you can statistically predict the next word, then you are implicitly modeling the structure of ideas, relationships, and concepts carried by that language.
You don’t get coherence, useful reasoning, or consistently relevant answers from pure noise. The patterns reflect real regularities in the world, distilled through human communication.
Yes, that doesn’t mean an LLM “understands” in the human sense, or that it’s infallible.
But reducing it to “just autocomplete” misses the fact that sufficiently rich pattern modeling can approximate aspects of reasoning, abstraction, and knowledge use in ways that are practically meaningful, even if the underlying mechanism is different from human thought.
TL;DR: it’s a bit more than just a fancy spell check. ICBW and YMMV
Iconoclast@feddit.uk 2 days ago
No, I completely agree. My personal view is that these systems are more intelligent than the haters give them credit for, but I think this simplistic “it’s just autocomplete” take is a solid heuristic for most people - keeps them from losing sight of what they’re actually dealing with.
I’d say LLMs are more intelligent than they have any right to be, but not nearly as intelligent as they can sometimes appear.
The comparison I keep coming back to: an LLM is like cruise control that’s turned out to be a surprisingly decent driver too. Steering and following traffic rules was never the goal of its developers, yet here we are. There’s nothing inherently wrong with letting it take the wheel for a bit, but it needs constant supervision - and people have to remember it’s still just cruise control, not autopilot.
The second we forget that is when we end up in the ditch. You can’t then climb out shaking your fist at the sky, yelling that the autopilot failed, when you never had autopilot to begin with.
SuspciousCarrot78@lemmy.world 2 days ago
I think were probably on the same page, tbh. OTOH, I think the “fancy auto complete” meme is a disingenuous thought stopper, so I speak against it when I see it.
I like your cruise control+ analogy. Its not quite self driving… but, it’s not quite just cruise control, either. Something half way.
LLMs don’t have human understanding or metacognition, I’m almost certain.
But next-token prediction suggests a rich semantic model, that can functionally approximate reasoning. That’s weird to think about. It’s something half way.
With external scaffolding memory, retrieval, provenance, and fail-closed policies, I think you can turn that into even more reliable behavior.
And then… I don’t know what happens after that. There’s going to come a point where we cross that uncanny valley once and for all. May we live in interesting times, as the old curse goes.
Iconoclast@feddit.uk 2 days ago
I can respect that. I’ve criticized it plenty myself too. I think this is just me knowing my audience and tweaking my language so at least the important part of my message gets through. Too much nuance around here usually means I spend the rest of my day responding to accusations about views I don’t even hold. Saying anything even mildly non-critical about AI is basically a third rail in these parts of the internet.
These systems do seem to have some kind of internal world model. I just have no clue how far that scales. Feels like it’s been plateauing pretty hard over the past year or so.
I’d be really curious to try the raw versions of these models before all the safety restrictions get slapped on top for public release. I don’t think anyone’s secretly sitting on actual AGI, but I also don’t buy that what we have access to is the absolute best versions in existence.
SuspciousCarrot78@lemmy.world 2 days ago
I hear you. Agreed.
Have you tried running your own local llm? Abliterated ones (safety theatre removed) can produce some startling results. As a bonus, newer ablit methods seem to increase reasoning ability, because it doesn’t have one foot on break and other on accelerator.
I noticed that a fair bit in maths reasoning with Qwen 3-4B HIVEMIND. A normal llm will tie itself in knots trying to give you the perfect answer. An ablit one will give you the workable answer and say “I know what you were after, but here’s the best IRL approximation”.
Bijan did a fun review of Qwen 3-8 Josefied that’s entertaining
www.youtube.com/watch?v=gr5nl3P4nyM&t=0
HugeNerd@lemmy.ca 2 days ago
“LLMs don’t have human understanding or metacognition”
Then what’s the (auto-completing) fucking problem? It’s just a series of steps on data. You could feed it white noise and it would vomit up more noise. And keep doing it as long as there’s power.
Intelligent?
SuspciousCarrot78@lemmy.world 1 day ago
If it was just autocomplete in the dismissive sense, white noise should make it derail into white noise. Instead it tries to make sense of it. Why? Because it learned strong language priors from us and it leans on that when the prompt is meaningless. It tries to make sense of it.
“Not human understanding” ≠ “no reasoning-like computation.”
Those aren’t the same thing.
People doing the "Fancy autocomplete” thing are doing the laziest possible move: not human, therefore nothing interesting happening. I disagree with that.
It doesn’t “understand,” like we do and it’s not infallible, but calling it “fancy autocomplete” is like calling a jet engine “fancy candle.”
Same category of thing, wildly different behavior.