Thank you Captain Obvious! Only those who think LLMs are like “little people in the computer” didn’t knew this already.
Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all.
Submitted 11 hours ago by Allah@lemm.ee to technology@lemmy.world
Comments
ZILtoid1991@lemmy.world 1 hour ago
BlaueHeiligenBlume@feddit.org 1 hour ago
Of course, that is obvious to all having basic knowledge of neural networks, no?
Nanook@lemm.ee 10 hours ago
lol is this news? I mean we call it AI, but it’s just LLM and variants it doesn’t think.
Clent@lemmy.dbzer0.com 27 minutes ago
Proving it matters. Science is constantly proving any other thing that people believe is obvious because people have an uncanning ability to believe things that are false. Some people will believe things long after science has proven them false.
MNByChoice@midwest.social 9 hours ago
The “Apple” part. CEOs only care what companies say.
kadup@lemmy.world 8 hours ago
Apple is significantly behind and arrived late to the whole AI hype, so of course it’s in their absolute best interest to keep showing how LLMs aren’t special or amazingly revolutionary.
They’re not wrong, but the motivation is also pretty clear.
JohnEdwa@sopuli.xyz 9 hours ago
"It’s part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, ‘that’s not thinking’." -Pamela McCorduck´. It’s called the AI Effect.
vala@lemmy.world 3 hours ago
Yesterday I asked an LLM “how much energy is stored in a grand piano?” It responded with saying there is no energy stored in a grad piano because it doesn’t have a battery.
Any reasoning human would have understood that question to be referring to the tension in the strings.
Another example is asking “does line cause kidney stones?”. It didn’t assume I mean lime the mineral and went with lime the citrus fruit instead.
Once again a reasoning human would assume the question is about the mineral.
Ask these questions again in a slightly different way and you might get a correct answer, but it won’t be because the LLM was thinking.
technocrit@lemmy.dbzer0.com 7 hours ago
There’s nothing more pseudo-scientific than “intelligence” maximization. I’m going to write a program to play tic-tac-toe. If y’all don’t think it’s “AI”, then you’re just haters. Nothing will ever be good enough for y’all. You want scientific evidence of intelligence?!?! I can’t even define intelligence so there! \s
kadup@lemmy.world 8 hours ago
That entire paragraph is much better at supporting the precise opposite argument. Computers can beat Kasparov at chess, but they’re clearly not thinking when making a move - even if we use the most open biological definitions for thinking.
Melvin_Ferd@lemmy.world 9 hours ago
This is why I say these articles are so similar to how right wing media covers issues about immigrants.
There’s some weird media push to convince the left to hate AI. Think of all the headlines for these issues. There are so many similarities. They’re taking jobs. They are a threat to our way of life. The headlines talk about how they will sexual assault your wife, your children, you. Threats to the environment. There’s articles like this where they take something known as twist it to make it sound nefarious to keep the story alive and avoid decay of interest.
Then when they pass laws, we’re all primed to accept them removing whatever it is that advantageous them and disadvantageous us.
hansolo@lemmy.today 9 hours ago
Because it’s a fear-mongering angle that still sells. AI has been a vehicle for scifi for so long that trying to convince Boomers that of won’t kill us all is the hard part.
I’m a moderate user for code and skeptic of LLM abilities, but 5 years from now when we are leveraging ML models for groundbreaking science and haven’t been nuked by SkyNet, all of this will look quaint and silly.
technocrit@lemmy.dbzer0.com 7 hours ago
Then when they pass laws, we’re all primed to accept them removing whatever it is that advantageous them and disadvantageous us.
You mean laws like this? jfc.
surph_ninja@lemmy.world 3 hours ago
You assume humans do the opposite? We literally institutionalize humans who not follow set patterns.
petrol_sniff_king@lemmy.blahaj.zone 2 hours ago
Maybe you failed all your high school classes, but that ain’t got none to do with me.
surph_ninja@lemmy.world 59 minutes ago
Funny how triggering it is for some people when anyone acknowledges humans are just evolved primates doing the same pattern matching.
LemmyIsReddit2Point0@lemmy.world 3 hours ago
We also reward people who can memorize and regurgitate even if they don’t understand what they are doing.
silasmariner@programming.dev 1 hour ago
Some of them, sometimes. But some are adulated and free and contribute vast swathes to our culture and understanding.
vala@lemmy.world 3 hours ago
No shit
bjoern_tantau@swg-empire.de 5 hours ago
crystalmerchant@lemmy.world 1 hour ago
I mean… Is that not reasoning, I guess? It’s what my brain does-- recognizes patterns and makes split second decisions.
mavu@discuss.tchncs.de 1 hour ago
Yes, this comment seems to indicate that your brain does work that way.
Jhex@lemmy.world 6 hours ago
this is so Apple, claiming to invent or discover something “first” 3 years later than the rest of the market
postmateDumbass@lemmy.world 2 hours ago
Trust Apple. Everyone else who were in the space first are lying.
LonstedBrowryBased@lemm.ee 5 hours ago
Yah of course they do they’re computers
finitebanjo@lemmy.world 5 hours ago
That’s not really a valid argument for why, but yes the models which use training data to assemble statistical models are all bullshitting. TBH idk how people can convince themselves otherwise.
EncryptKeeper@lemmy.world 4 hours ago
TBH idk how people can convince themselves otherwise.
They don’t convince themselves. They’re convinced by the multi billion dollar corporations pouring unholy amounts of money into not only the development of AI, but its marketing. Marketing designed to not only convince them that AI is something it’s not, but also that that anyone who says otherwise (like you) are just luddites who are going to be “left behind”.
turmacar@lemmy.world 4 hours ago
I think because it’s language.
There’s a famous quote from Charles Babbage when he presented his difference engine (gear based calculator) and someone asking “if you put in the wrong figures, will the correct ones be output” and Babbage not understanding how someone can so thoroughly misunderstand that the machine is, just a machine.
People are people, the main thing that’s changed since the Cuneiform copper customer complaint is our materials science and networking ability. Most of things people interact with every day, most people just assume work like it appears to on the surface.
And nothing other than a person can do math problems or talk back to you. So people assume that means intelligence.
technocrit@lemmy.dbzer0.com 7 hours ago
Why would they “prove” something that’s completely obvious?
thinking processes
The abstract of their paper is completely pseudo-scientific from the first sentence.
tauonite@lemmy.world 2 hours ago
That’s called science
TheRealKuni@midwest.social 5 hours ago
Why would they “prove” something that’s completely obvious?
I don’t want to be critical, but I think if you step back a bit and look and what you’re saying, you’re asking why we would bother to experiment and prove what we think we know.
That’s a perfectly normal and reasonable scientific pursuit. Yes, in a rational society the burden of proof would be on the grifters, but that’s never how it actually works. It’s always the doctors disproving the cure-all, not the snake oil salesmen failing to prove their own prove their own product.
There is value in this research, even if it fits what you already believe on the subject. I would think you would be thrilled to have your hypothesis confirmed.
postmateDumbass@lemmy.world 2 hours ago
The sticky wicket is the proof that humans (functioning ‘normally’) do more than pattern.
yeahiknow3@lemmings.world 7 hours ago
They’re just using the terminology that’s widespread in the field. The paper’s purpose is to prove that this terminology is unsuitable.
technocrit@lemmy.dbzer0.com 7 hours ago
I understand that people in this field regularly use pseudo-scientific language. But the terminology has never been suitable so it shouldn’t be used in the first place. They’re just feeding into the grift. That’s how they get paid.
Mbourgon@lemmy.world 5 hours ago
Not when large swaths of people are being told to use it everyday. Upper management has bought in on it.
SplashJackson@lemmy.ca 6 hours ago
Just like me
alexdeathway@programming.dev 6 hours ago
python code for reversing the linked list.
sev@nullterra.org 9 hours ago
Just fancy Markov chains with the ability to link bigger and bigger token sets. It can only ever kick off processing as a response and can never initiate any line of reasoning. This, along with the fact that its working set of data can never be updated moment-to-moment, means that it would be a physical impossibility for any LLM to achieve any real "reasoning" processes.
kescusay@lemmy.world 9 hours ago
I can envision a system where an LLM becomes one part of a reasoning AI, acting as a kind of fuzzy “dataset” that a proper neural network incorporates and reasons with, and the LLM could be kept real-time updated (sort of) with MCP servers that incorporate anything new it learns.
But I don’t think we’re anywhere near there yet.
homura1650@lemm.ee 12 minutes ago
LLMs (at least in their current form) are proper neural networks.
riskable@programming.dev 6 hours ago
The only reason we’re not there yet is memory limitations.
Eventually some company will come out with AI hardware that lets you link up a petabyte of ultra fast memory to chips that contain a million parallel matrix math processors. Then we’ll have an entirely new problem: AI that trains itself incorrectly too quickly.
Just you watch: The next big breakthrough in AI tech will come around 2032-2035 (when the hardware is available) and everyone will be bitching that “chain reasoning” (or whatever the term turns out to be) isn’t as smart as everyone thinks it is.
auraithx@lemmy.dbzer0.com 8 hours ago
Unlike Markov models, modern LLMs use transformers that attend to full contexts, enabling them to simulate structured, multi-step reasoning (albeit imperfectly). While they don’t initiate reasoning like humans, they can generate and refine internal chains of thought when prompted, and emerging frameworks (like ReAct or Toolformer) allow them to update working memory via external tools. Reasoning is limited, but not physically impossible, it’s evolving beyond simple pattern-matching toward more dynamic and compositional processing.
vrighter@discuss.tchncs.de 3 hours ago
previous input goes in. Completely static, prebuilt model processes it and comes up with a probability distribution.
There is no “unlike markov chains”. They are markov chains. Ones with a long context (a markov chain also kakes use of all the context provided to it, so I don’t know what you’re on about there). LLMs are just a (very) lossy compression scheme for the state transition table. Computed once, applied blindly to any context fed in.
spankmonkey@lemmy.world 8 hours ago
Reasoning is limited
Most people wouldn’t call zero of something ‘limited’.
riskable@programming.dev 6 hours ago
I’m not convinced that humans don’t reason in a similar fashion. When I’m asked to produce pointless bullshit at work my brain puts in a similar level of reasoning to an LLM.
Think about “normal” programming: An experienced developer (that’s self-trained on dozens of enterprise code bases) doesn’t have to think much at all about 90% of what they’re coding. It’s all bog standard bullshit so they end up copying and pasting from previous work, Stack Overflow, etc because it’s nothing special.
The remaining 10% is “the hard stuff”. They have to read documentation, search the Internet, and then—after all that effort to avoid having to think—they sigh and start actually start thinking in order to program the thing they need.
LLMs go through similar motions behind the scenes! Probably because they were created by software developers but they still fail at that last 90%: The stuff that requires actual thinking.
Eventually someone is going to figure out how to auto-generate LoRAs based on test cases combined with trial and error that then get used by the AI model to improve itself and that is when people are going to be like, “Oh shit! Maybe AGI really is imminent!” But again, they’ll be wrong.
AGI won’t happen until AI models get good at retraining themselves with something better than basic reinforcement learning. In order for that to happen you need the working memory of the model to be nearly as big as the hardware that was used to train it. That, and loads and loads of spare matrix math processors ready to go for handing that retraining.
brsrklf@jlai.lu 9 hours ago
You know, despite not really believing LLM “intelligence” works anywhere like real intelligence, I kind of thought maybe being good at recognizing patterns was a way to emulate it to a point…
But that study seems to prove they’re still not even good at that. At first I was wondering how hard the puzzles must have been, and then there’s a bit about LLM finishing 100 move towers of Hanoï (on which they were trained) and failing 4 move river crossings. Logically, those problems are very similar… Also, failing to apply a step-by-step solution they were given.
auraithx@lemmy.dbzer0.com 8 hours ago
This paper doesn’t prove that LLMs aren’t good at pattern recognition, it demonstrates the limits of what pattern recognition alone can achieve, especially for compositional, symbolic reasoning.
technocrit@lemmy.dbzer0.com 7 hours ago
Computers are awesome at “recognizing patterns” as long as the pattern is a statistical average of some possible worthless data set.
reksas@sopuli.xyz 10 hours ago
does ANY model reason at all?
4am@lemm.ee 9 hours ago
No, and to make that work using the current structures we use for creating AI models we’d probably need all the collective computing power on earth at once.
SARGE@startrek.website 8 hours ago
… So you’re saying there’s a chance?
MrLLM@ani.social 2 hours ago
I think I do. Might be an illusion, though.
auraithx@lemmy.dbzer0.com 8 hours ago
Define reason.
Like humans? Of course not. models lack intent, awareness, and grounded meaning. They don’t “understand” problems, they generate token sequences.
reksas@sopuli.xyz 6 hours ago
as it is defined in the article
Grizzlyboy@lemmy.zip 3 hours ago
What a dumb title. I proved it by asking a series of questions. It’s not AI, stop calling it AI, it’s a dumb af language model. Can you get a ton of help from it, as a tool? Yes! Can it reason? NO! It never could and for the foreseeable future, it will not.
It’s phenomenal at patterns, much much better than us meat peeps. That’s why they’re accurate as hell when it comes to analyzing medical scans.
sp3ctr4l@lemmy.dbzer0.com 9 hours ago
This has been known for years, this is the default assumption of how these models work.
You would have to prove that some kind of actual reasoning has arisen as some kind of emergent conplexity phenomenon… not the other way around.
Corpos have just marketed/gaslit us/themselves so hard that they apparently forgot this.
riskable@programming.dev 6 hours ago
Define, “reasoning”. For decades software developers have been writing code with conditionals. That’s “reasoning.”
LLMs are “reasoning”… They’re just not doing human-like reasoning.
sp3ctr4l@lemmy.dbzer0.com 6 hours ago
Howabout uh…
The ability to take a previously given set of knowledge, experiences and concepts, and combine then in a consistent, non contradictory manner, to generate hitherto unrealized knowledge, or concepts, and then also be able to verify that those new knowledge and concepts are actually new, and actually valid, or at least be able to propose how one could test whether or not they are valid.
Arguably this is or involves meta-cognition, but that is what I would say… is the difference between what we typically think of as ‘machine reasoning’, and ‘human reasoning’.
mfed1122@discuss.tchncs.de 9 hours ago
This sort of thing has been published a lot for awhile now, but why is it assumed that this isn’t what human reasoning consists of? Isn’t all our reasoning ultimately a form of pattern memorization? I sure feel like it is. So to me all these studies that prove they’re “just” memorizing patterns don’t prove anything, unless coupled with research on the human brain to prove we do something different.
technocrit@lemmy.dbzer0.com 6 hours ago
why is it assumed that this isn’t what human reasoning consists of?
Because science doesn’t work work like that. Nobody should assume wild hypotheses without any evidence whatsoever.
mfed1122@discuss.tchncs.de 6 hours ago
Sorry, I can see why my original post was confusing, but I think you’ve misunderstood me. I’m not claiming that I know the way humans reason. In fact you and I are on total agreement that it is unscientific to assume hypotheses without evidence. This is exactly what I am saying is the mistake in the statement “AI doesn’t actually reason, it just follows patterns”. That is unscientific if we don’t know whether or “actually reasoning” consists of following patterns, or something else. As far as I know, the jury is out on the fundamental nature of how human reasoning works. It’s my personal, subjective feeling that human reasoning works by following patterns. But I’m not saying “AI does actually reason like humans because it follows patterns like we do”. Again, I see how what I said could have come off that way. What I mean more precisely is:
It’s not clear whether AI’s pattern-following techniques are the same as human reasoning, because we aren’t clear on how human reasoning works. My intuition tells me that humans doing pattern following seems equally as valid of an initial guess as humans not doing pattern following, so shouldn’t we have studies to back up the direction we lean in one way or the other?
I think you and I are in agreement, we’re upholding the same principle but in different directions.
LesserAbe@lemmy.world 8 hours ago
Agreed. We don’t seem to have a very cohesive idea of what human consciousness is or how it works.
technocrit@lemmy.dbzer0.com 6 hours ago
… And so we should call machines intelligent? That’s not how science works.
Endmaker@ani.social 8 hours ago
You’ve hit the nail on the head.
Personally, I wish that there’s more progress in our understanding of human intelligence.
technocrit@lemmy.dbzer0.com 6 hours ago
Their argument is that we don’t understand human intelligence so we should call computers intelligent.
That’s not hitting any nail on the head.
count_dongulus@lemmy.world 8 hours ago
Humans apply judgment, because they have emotion. LLMs do not possess emotion. Mimicking emotion without ever actually having the capability of experiencing it is sociopathy. An LLM would at best apply patterns like a sociopath.
mfed1122@discuss.tchncs.de 7 hours ago
But for something like solving a Towers of Hanoi puzzle, which is what this study is about, we’re not looking for emotional judgements - we’re trying to evaluate the logical reasoning capabilities. A sociopath would be equally capable of solving logic puzzles compared to a non-sociopath. In fact, simple computer programs do a great job of solving these puzzles, and they certainly have nothing like emotions. So I’m not sure that emotions have any relevance to the topic of AI or human reasoning and problem solving.
As for analogizing LLMs to sociopaths, I think that’s a bit odd too. The reason why we (stereotypically) find sociopathy concerning is that a person has their own desires which, in combination with a disinterest in others’ feelings, incentivizes them to be deceitful or harmful in some scenarios. But LLMs are largely designed specifically as servile, having no will or desires of their own. If people find it concerning that LLMs imitate emotions, then I think we’re giving them far too much credit as sentient autonomous beings - and this is coming from someone who thinks they think in the same way we do! The think like we do, IMO, but they lack a lot of the other subsystems that are necessary for an entity to function in a way that can be considered as autonomous/having free will/desires of its own choosing, etc.
riskable@programming.dev 6 hours ago
That just means they’d be great CEOs!
flandish@lemmy.world 10 hours ago
stochastic parrots. all of them. just upgraded “soundex” models.
this should be no surprise, of course!
WorldsDumbestMan@lemmy.today 2 hours ago
It has so much data, it might as well be reasoning. As it helped me with my problem.
atlien51@lemm.ee 8 hours ago
Employers who are foaming at the mouth at the thought of replacing their workers with cheap AI:
🫢
monkeyslikebananas2@lemmy.world 6 hours ago
Can’t really replace. At best, this tech will make employees more productive at the cost of the rainforests.
atlien51@lemm.ee 2 hours ago
Yes but asshole employers haven’t realized this yet
SattaRIP@lemmy.blahaj.zone 11 hours ago
Why tf are you spamming rape stories?
hybridep@lemmy.wtf 10 hours ago
And this is relevant to this post in what regard?
90% of Lemmy comments lately are not subject related and only about how OP is not leftist, not pro-israel, pro-palestine, pro-sjw enough. Is this what Lemmy aims to be?
Allah@lemm.ee 9 hours ago
thanks alot kind person for taking my side
Melvin_Ferd@lemmy.world 9 hours ago
It’s not relevant to the post… But what the fuck
pulsewidth@lemmy.world 11 hours ago
Thanks for highlighting this. Blocked em. I know these horrible things happen, but if they’re happening on the other side of the world and there is literally nothing i can do to help all they do is spread sadness and despair, and at worst provoke racism (as all the stories being shared are the same country, yet these incidents happen worldwide).
Allah@lemm.ee 10 hours ago
did i do it here? also that’s where i live, if i can’t talk about womens struggle then i appologize
catloaf@lemm.ee 10 hours ago
Racism
Allah@lemm.ee 10 hours ago
i am racist for speaking about my own culture problem?
Blaster_M@lemmy.world 9 hours ago
Would like a link to the original research paper, instead of a link of a screenshot of screenshot
hornedfiend@sopuli.xyz 8 hours ago
While I hate LLMs with passion and my opinion of them boiling down to them being glorified search engines and data scrapers, I would ask Apple: how sour are the grapes, eh?
1rre@discuss.tchncs.de 9 hours ago
The difference between reasoning models and normal models is reasoning models are two steps, to oversimplify it a little they prompt “how would you go about responding to this” then prompt “write the response”
It’s still predicting the most likely thing to come next, but the difference is that it gives the chance for the model to write the most likely instructions to follow for the task, then the most likely result of following the instructions - both of which are much more conformant to patterns than a single jump from prompt to response.
MuskyMelon@lemmy.world 10 hours ago
I use LLMs as advanced search engines. Much less ads and sponsored results.
Naich@lemmings.world 9 hours ago
So they have worked out that LLMs do what they were programmed to do in the way that they were programmed? Shocking.
mavu@discuss.tchncs.de 1 hour ago
No way!
Statistical Language models don’t reason?
But OpenAI, robots taking over!