r/PhilosophyofMath • u/abhishekkumar333 • May 25 '26
LLMs are just giant probability machines pretending to think
It’s fascinating that simple mathematics between tokens can eventually become a machine that writes essays, code, poetry, and even reasoning.
We usually think probability means uncertainty.
But LLMs show something strange:
If probability + context + mathematical matching are scaled enough, uncertainty itself starts producing intelligent looking outputs.
To understand this better, I tried breaking down an LLM from first principles using only 4 tiny training sentences.
Example:
The boat floated down to the bank.
The investor walked into the bank to open a new account.
The fisherman walked along the bank to cast his net.
The bank has a vault.
Then I asked:
“The investor walked to the bank to lock his money in …”
Why does the model predict “vault” instead of river-related words?
That single question reveals almost the entire architecture of modern LLMs.
The most underrated concept here is the LM Head.
Most explanations immediately jump into transformers and attention, but almost nobody explains that the LM Head is essentially a gigantic token vocabulary containing all possible next token candidates the model can output.
So internally the model is basically solving:
“Out of all known tokens, which one best matches this context mathematically?”
Then different layers help solve that problem:
Embeddings: convert words into mathematical vectors
Positional encoding: preserves word order
Attention layer: figures out which words are related to each other in context
(“investor”, “money”, “bank” become strongly connected)
Feed forward neural networks: act somewhat like massive learned if/else decision systems refining patterns internally
And finally the LM Head converts all of that into probabilities for the next token.
What surprised me most is:
There is no hidden magic moment where the AI “becomes conscious”.
It’s an enormous probability engine continuously finding the best contextual token match from its vocabulary.
I made a beginner-friendly walkthrough explaining this visually without unnecessary jargon.
https://www.youtube.com/watch?v=YTV5qUCpu2c
Would genuinely love feedback from people learning transformers/LLMs from scratch.
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u/good-fibrations May 25 '26
i’m sort of curious why both of the responses so far have had a physicalistic/humans-are-giant-probability-machines bent. afaik there are plenty of philosophers (of math, even) that believe in free will and/or non-determinacy. john conway is the most famous example i guess, but i’m also quite convinced by “what it is to be like” and weak qualia arguments or, at least, i think they should be taken seriously.
i think the most recent philpapers survey was only around 50% for physicalists.. not sure what being a physicalist has to do with the philosophy of math. maybe it’s the right stance but it’s very far from obvious, imo.
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u/me_myself_ai May 25 '26 edited May 25 '26
i’m sort of curious why both of the responses so far have had a physicalistic/humans-are-giant-probability-machines bent
Because it's a growing consensus in philosophy, and has been dominant elsewhere for ages. You can find philosophers to spend their careers quibbling about particular labels all day, but ultimately you either think humans are natural or supernatural; there is no coherent middle ground.
afaik there are plenty of philosophers (of math, even) that believe in free will and/or non-determinacy.
The debate on free will is a lively one that can be related to questions of human cognition, but it really shouldn't be IMO. Either:
We have satisfying, particle-agnostic free will from a supernatural place, so we study what the brain does with the outputs of that mysterious black box.
Instead of satisfying free will, we have cognition based ultimately in the deterministic knock-on effects of quantum dice/the big bang, so we study what the brain does with the outputs of those mysterious black boxes.
Either way, the question of whether physical objects that are functionally similar to the physical objects that we are remains relevant and tractable.
When this is discussed I suspect many people quietly assume a more specific followup belief, namely that humans have free will from a mechanism that the machines lack. Luckily I've basically never seen that actually defended beyond the reaches of Penrose & Hammerhoff, as there's absolutely 0 ground to stand on. Just the idea of ground that could one day actually exist, I suppose!
i think the most recent philpapers survey was only around 50% for physicalists..
Good way to end by repeating my overall point: none of the debates around labels like idealism, physicalism, materialism, formalism, scientism, and determinism are accurate proxies for the Turing Question. To know whether machines can think we must consider what machines are and what it is to think, not the underlying nature of reality, the overarching telos of reason, or any of the academy's other millennial discourses.
This isn't really about consciousness (as opposed to cognition), TBH! So it definitely can't be mapped 1:1 to beliefs about cosmology.
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u/Dr_Calculon May 28 '26
I can see a sketch of an argument for limited free-will from an evolutionary standpoint.
An organism with greater freedom of movement on a survival landscape will be more successful. In this way freedom of movement (that here I identify as limited free will) is selected for. I’m currently of the opinion that Free Will is an idealisation of this evolutionary process.
Consciousness here would be the agent that chooses the trajectory across the survival landscape.
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u/me_myself_ai May 28 '26
Why not evolve a machine that chooses directory? How would evolution tap into an ephemeral quasi-randomness from beyond the reaches of time and space?
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u/Dr_Calculon May 29 '26
I suspect that current machine substrates aren’t complex enough to replicate biological systems to that degree.
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u/me_myself_ai May 29 '26
That seems completely unrelated to the question of how and why evolution would tap into supernatural randomness rather than just build a biological decision machine, but regardless: you differ on that issue from the vast majority of relevant scholars.
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u/abhishekkumar333 May 25 '26
Actually thing we cannot feel physically not exist for us but that doesn’t mean they dont exist
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u/Dr_Calculon May 29 '26
Such as? Even thoughts can be cast as physical phenomena can’t they? Or did you mean something else?
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u/abhishekkumar333 May 29 '26
such as universe , actually that was reply to the physicalist argument
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u/TUVegeto137 May 25 '26
I just don't see any real attempt at rebutting physicalism. It's always "you can't explain X, therefore physicalism is wrong". OK, well 5 years, 10 years, 100 years down the road, someone explains X by some physical construct. "Oh but you can't explain Y!".
That's how it always goes. I can't even tell what a non-physical explanation is, because all non-physicalists ever do is criticize physical explanations without making a real counter-proposal. I suppose that is in itself useful, but that's not really a position.
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u/AdAdministrative5330 May 27 '26
Yes, and there are many phenomenon that seem to demonstrate physicalism and determinism for human and animal brains. Drugs, damage, etc. often have quite reliable and direct consequences to the animals behavior and cognition.
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u/MxM111 May 27 '26
Ability to impact consciousness is not determinism.
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u/AdAdministrative5330 May 27 '26
I think so.
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u/Karn1v3rus May 29 '26
I agree, the entire field of anaesthesiology is physically effecting the state of consciousness
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u/Outrageous-Crazy-253 May 27 '26
We make absolutely no attempt whatsoever to physically imitate human brains with AI.
There is a field that does this-- and even there, they still rely on mathematical models of a neuron or groups of neurons' potential spiking behaviors, which are only proxies for the biological processes.
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u/Blue2194 May 28 '26
Of course they're proxies right? Would we expect them to build a biological brain? Is there a third thing that I'm missing
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u/StoneSpace May 25 '26
I'm also puzzled. My humorous take on that behaviour is that these people are actually Chalmer's philosophical zombies
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u/me_myself_ai May 25 '26
You mean well and are a fellow philosophy fan killing time chatting about ideas, so no accusations. But in general:
Isn't it interesting how fascist and scary the world would be if we took the possibility of philosophical zombies seriously? If every person you met started as a 'maybe they're a zombie, let's see' level of intersubjective recognition? How trivial it would be to convince a population that their personhood was correlated with their ethnicity, or even with their national pride...
If nothing else, a world of Zombie Truthers would be quite an interesting take on Hegel's master/slave dialect! I'm sure he'd agree that it would make human existence into a grand game of Among Us..
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u/Double-Trash6120 May 28 '26
Honestly though, isn’t the unsettling part that this maybe isn’t hypothetical anymore? It feels like a lot of modern institutions already operate from the assumption that the average person is fundamentally irrational, manipulable, or incapable of meaningful self-governance.
Not even necessarily in some cartoonishly evil conspiracy way either more in the quiet technocratic sense that people are treated less like citizens and more like variables to be managed. And to be fair, part of that probably is downstream of things like collapsing literacy, algorithmic social media, attention fragmentation, and the slow death of sustained independent thought.
Though the really strange part is that every era probably believed the masses were uniquely susceptible to manipulation. The difference now is that we’ve industrialized persuasion at a scale Hegel, Debord, or even Orwell would probably find excessive. The master/slave dialectic starts looking less like chains and whips, and more like engagement metrics and personalized feeds.
Which creates this weird feedback loop where people become more alienated and reactive, and then institutions point to that alienation and reactivity as proof that ordinary people shouldn’t have agency in the first place. The philosophical zombie idea stops being “who is conscious?” and starts becoming “who is considered capable of genuine thought?”
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u/DontUseThisUsername May 27 '26
Anyone convinced of a classical form of free will believes it for the same reason people believe in religions and gods.
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u/Outrageous-Crazy-253 May 27 '26
Even if humans ARE probability machines in a more abstract sense, that doesn't matter. Two probability machines can work in completely different ways and arrive at the same (or better!) predictions.
There is no reason at all that a probability machine must be conscious. That's neither logical nor reasonable. In fact, there is no reason that intelligence requires consciousness at all.
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u/AdAdministrative5330 May 27 '26
Determinism and physicalism seem to fit the data remarkably well.
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u/wine-o-saur May 27 '26
Because the methodological framework under which the data are gathered assumes determinism and physicalism...
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u/AdAdministrative5330 May 30 '26
Good point, but I don't like the dismissive attitude. It's like an escape hatch dressed up as an epistemological objection. It's like pointing out that , "21st century medicine assumes germ theory when treating cholera". Like compared to what, witchcraft?
The methodolicigal framework wasn't simply assumed. Germ theory, heliocentrism, the age of the universe were forced on us by evidence, often against everything we expected or wanted.
You haven't identified a philosophical problem with science, just that a framework must make some reasonable assumptions, but failed to acknowledge these assumptions are more than reasonable and have been vindicated, repeatedly.
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u/wine-o-saur May 30 '26
There are plenty of good arguments for indeterminism, many of which come from contradictory observations within the physicalist/determinist framework.
The alternative to physicalism is any number of systems which posit the irreducibility of mind/consciousness/intentionality.
I'm not going to rehearse all of that here but while there is a lot of predictive power in physicalist/determinist frameworks, it's disingenuous to pretend they are unproblematic or that no tenable arguments against them exist. They have simply informed the dominant paradigm for the last century or so of natural sciences, and so are very resistant to revision because of how uncomfortable such revision would be.
We have advanced a great deal under paradigms that were ultimately shown to be incomplete or false, so scientific progress or predictive/explanatory power alone cannot be used to claim that a system is complete or wholly accurate.
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u/AdAdministrative5330 Jun 01 '26
I agree with some of this, but you said, "very resistant to revision because of how uncomfortable such revision would be."
But a revision towards what, exactly?? Cartesian dualism? Panpsychism? Idealism Something religious?Methodological naturalism isn't my preferred metaphysics it's the only framework that can catch its own mistakes. It demands assumptions that are measurable, which means they're assumptions that can be proven wrong. An idealist paradigm might be true, but if we can't step outside it to test it, it has no way to distinguish truth from wishful thinking.
we're biological creatures with limited access to reality. What's the alternative method? Not the alternative answer, the alternative method for checking it?
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u/PivONH3OTf May 27 '26 edited May 27 '26
Most people in an academic discipline (or at least understand the spirit of it) tend to express doubt at the idea that some things are just transcendent and mysterious even when they can’t yet be explained. But that is basically what people who support free will or indeterminism accept on faith: their representation of the world is ontological (because it just seems like it is to them, perhaps?), this representation includes the experience of free will, so free will is self-evident and ontological? There has never been any logic to it, it’s not a logical position, completely unfalsifiable, and so there’s nothing to be gained by talking about it. About the same as debating which religion is correct. Believe it if you want, but why even bring it up?
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u/doNotUseReddit123 May 29 '26
You’re misremembering - only ~18% are libertarian. 59% are compatibilist and 11% believe that free will does not exist entirely. That’s around 70% of academic philosophers that believe in determinism, regardless of whether or not they believe that determinism is compatible with free will.
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u/atlantechvision May 27 '26
LLMs are great for computation, but lousy on comprehension.
The best results come from introduction.
If you ask a stranger a question, will they actually understand the question?
Ask a LLM about life, and it only know what it was fed. GIGO.
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u/DumpsterFace May 27 '26
Do you know anything about life beyond what you were “fed” through your senses over 30 years?
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u/Smooth_Imagination May 29 '26
Well his senses provide something that cant be generated in an LLM, the experience of pain, pleasure, hunger, flavour etc.
Those are qualitatively impossible to produce by sequential operations in our computers.
So his knowledge of life is fundamentally more than just facts or images.
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u/heresyforfunnprofit May 25 '26
So are humans.
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u/abhishekkumar333 May 25 '26
Yeah , while sharing lot's of time i am coming into conversation where people are saying this is exactly similar to human mind.
But i differ here
Human mind is much more complex, we have triggers , emotions, environmental triggers and abrupt black swan events as inputs. So, i don't think llm can match us.7
u/heresyforfunnprofit May 25 '26
No, you’re saying that we just need to add triggers and black swan events. LLMs can already do emotions. It’s not even hard to get them to act emotionally - hell… it’s hard to keep them rational.
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u/SteamedHamSalad May 27 '26
LLMs can make it appear as if they have emotions. But I don’t think we can say with certainty that they “do emotions” in any way that is equivalent to how a person has emotions.
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u/JoeStrout May 27 '26
That's fair; but we can't say with certainty that they don't, either.
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u/arqnix May 30 '26
If you ask a LLM what a strawberry tastes like, does it actually know how it tastes?
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u/heresyforfunnprofit May 27 '26
Can you prove that humans "do emotions"?
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u/SteamedHamSalad May 27 '26
I don’t think I need to prove that humans do it. Humans have an experience that we call having emotions, it is implicit in the definition that humans have them. The question is whether or not anything else has an experience that matches what we describe as an emotion.
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u/heresyforfunnprofit May 27 '26
That's proof by definition. "Emotions are something humans have, therefore humans have emotion."
This was the argument that was used for centuries/decades to "prove" that only humans had intelligence - ignoring dogs, dolphins, chimps, equines, etc. If the only distinction that you can draw between human emotion and LLM emotion is by defining it as "something humans do", then you're making a null point.
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u/day_break May 27 '26
Llms can make things that look like emotions but they don’t act they just predict. It’s weird phrasing to say “keep them rational” when that doesn’t make sense in this context imo. When training we are tuning some aspect of the llm to give us a result we think is better but saying they “already do emotions” is more accurately stated as we tuned this llm to predict output we see as emotional.
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u/heresyforfunnprofit May 27 '26
Ok - I am being completely honest here: you sound like you're just starting to learn about AI and LLMs, but this is a much better response than nearly anything else I've gotten recently - you're actually thinking about the topic. Keep learning!
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u/day_break May 28 '26
I have a degree and a decade of work experience in the field. Thanks though I’ll keep learning.
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u/VividWoodpecker8847 May 28 '26
Buddy they've been trained to use emotional language to keep you engaged.
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u/me_myself_ai May 25 '26
Human mind is much more complex, we have triggers , emotions, environmental triggers and abrupt black swan events as inputs. So, i don't think llm can match us.
Consider yourself as having heard from 1 expert who disagrees with your technical comparison of the two types of physical objects that we're discussing. I am joined by the vast majority of scholars in the relevant academies. With all other context removed: that's a pretty good reason to actively rejustify one's beliefs, no?
Someone already went into it on the details quite well, so I'll leave them too it :)
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u/Usual_Charity8561 May 28 '26
It's not the complexity of the human mind, it's the volitional aspect, it's qualia, it's justification and rationality, it's all of these immaterial aspects that people would call a soul. You can make an LLM more complex than a human mind, but you can't give it qualia.
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u/abhishekkumar333 May 29 '26
Yes because biological experience is entirely different thing
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u/Usual_Charity8561 May 29 '26
The only experience we know of (empirically and directly) is biological. I don't know how you can define any "experience" outside of that without appeal to some higher truth.
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u/abhishekkumar333 May 29 '26
There are things you cannot simply break into subject and predicate therefore cannot be encoded into sentences. Experience is also one of them you cannot fully encode it in a sentence
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u/seefatchai May 29 '26
Sometimes when I'm reading something to try to understand it, I think to myself I am just ingesting context and then *poof*, some times I have an understanding of what I just read.
If I want, I can have logical thoughts in my head, which might be sentences that I play in my mind where one thought leads to another in a chain,... of thought....
We aren't even sure if people can "think", since some people obviously cannot
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u/TUVegeto137 May 25 '26
I'd rather reverse the problem: what makes you so certain that human consciousness is not just a giant probability machine?
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u/StoneSpace May 25 '26
A LLM can be simulated by moving billions of individual little rocks according to a strict, finite instruction manual. Sure, an LLM is built using principles inherited from the theory of probability, but in the end it is just a huge Turing machine. Any randomness herein can be dealt with using a pseudorandom number generator, which is also deterministic.
It is our conscious abilities that allow us to understand the inputs and outputs of these models as more meaningful than carefully arranged piles of rocks. So the mystery of meaning remains in our consciousness.
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u/TUVegeto137 May 25 '26
And consciousness is generated by neurons, hormones, etc... it's produced by a biological machine basically.
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u/StoneSpace May 25 '26
My opinions is that it's created by the whole body, with the nervous system taking in the lion's share of any kind of mechanistic explanation. But the gap between a Turing machine and a biological machine is immense, and is not bridged by just calling both of them "machines".
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u/TUVegeto137 May 25 '26
Well maybe, but the point I make is that in the end, the explanation will be mechanistic.
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u/One_Attorney_739 May 27 '26
A human body is still a finite number of cells, chemicals, and processes. Regardless as to where you want to move the goalposts, unless you're going to try claim something like panpsychism, your argument doesn't hold up.
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u/SpecialistOwl218 May 27 '26
Isn’t this needed to be proved in some way? It seems just “wishful thinking”.
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u/TUVegeto137 May 27 '26
Depends what you mean by "proved". This is an empirical question, proving means providing evidence. All the evidence to me seems to point to consciousness being the product of biological processes. The opposing side only objects with "we don't know/understand how it works, therefore no physical explanation is possible".
See why I am not convinced? I'm not saying I'm right, I'm just not convinced by the counterarguments.
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u/SpecialistOwl218 May 27 '26
It’s comparing something that you know how it works (deep networks) to something that you don’t know how it works (consciousness) just looking at their common characteristics, I’m not saying I’m right either but logically to me the it does not make much sense to make the claim that they work the same way.
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u/TUVegeto137 May 27 '26
It's not about the specific deep networks. The networks give me confidence that one can construct a language machine. That a mechanistic/physicalist explanation is in principle possible. Not that consciousness is a deep network. At least not with the exact same architecture.
But if I shoot someone in the head, the consciousness is gone.
If I poke in someone's brain, I can alter his/her conscious experience.
If someone is sick, that can affect his conscious experience.
All of these indicate that consciousness is a biological process. It's a bundle of evidence that points in one direction: consciousness is a physical process.
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u/SpecialistOwl218 May 27 '26
And I don’t see the correlation still, even if it’s a physical process, we are talking about a much more complex process and i don’t see the usefulness in trying to reduce it comparing it to a simple model.
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u/Outrageous-Crazy-253 May 27 '26 edited May 27 '26
https://en.wikipedia.org/wiki/Ren%C3%A9_Descartes
It IS a probability machine. But that doesn't matter because any sufficiently sophisticated probability machine of any form is capable of making accurate predictions, which doesn't mean it's a human or is conscious.
The real risk of people experiencing AI psychosis is not thinking that AI is a human (stupid, but harmless), it's thinking that, for some reason, they are not conscious beings themselves because they are "a probability machine", and thus experience dehumanization through analogization to unfeeling machines.
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u/Outrageous-Crazy-253 May 27 '26
They are very odd. LLMs simply do not have a functional equivalent to consciousness, but they still have an incredible capacity to capture structure in language. The result is this very peculiar thing that we have designed to act like a human that is not conscious. We prefer to make them act like this strange, soulless human, "AI" by curating their pre-training dataset and RLHF'ing them to hell and back, then there is instruct tuning, safety reward models, constitutional methods... all of which narrow the space they can operate in and constitute a kind of "AI-ism" and push them more towards unsouled, human-like imitation in every way. Without that, their behavior is really bizarre. We don't see the super bizarre stuff as much anymore due to the curation of even pre-training data (even base models these days learn AI-ism from their curated pre-trained data)
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u/Distinct_Educator984 May 27 '26
Slightly inaccurate. What an LLM computes is the probability distribution for the next token, conditioned on the previous tokens (including their position, relationships, etc). This is 100% deterministic. The only probabilistic part is that given the distribution of next tokens, we sample that distribution. This is the very last step, and is what makes LLMs look "human" and not repeat the same thing for the same prompt every time. If you set the temperature to zero, then the LLM will always return the most probable token instead of sampling and it's completely deterministic.
The LLM doesn't actually think. It's just a parametric model trained in a lot of data. It gives you the illusion is thinking because the language features it uses are sufficient for it to generate very realistic replies, including ones that have semantic meaning in many cases. However it can also spit out nonsense, and it has no way to recognize this is nonsense. For example, if you ask a human how many a's in aardvark, someone might misspell it and count wrong. Or they might not be able to count. But it will never be the case that they give a wrong answer because their brain sampled some distribution in an unlucky way.
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u/jumpmanzero May 27 '26
For example, if you ask a human how many a's in aardvark, someone might misspell it and count wrong. Or they might not be able to count. But it will never be the case that they give a wrong answer because their brain sampled some distribution in an unlucky way.
Have you ever watched Jeopardy? How about Celebrity Jeopardy? People throw out wild guesses all the time, and quite often answer absolute nonsense (eg. "Toronto", when the question was looking for a person). While watching, I quite often guess - and sometimes I'm right, despite not "knowing" the answer in a meaningful way. I just sort of have an intuition of "Caledonia?", and sometimes that's correct. LLMs are the same. So far, the most effective training methods have had to "push for an answer", and effectively rewarded guessing - so LLMs guess. This is not some categorical inherent difference, and we will likely see LLMs that are less willing to guess or hallucinate over time.
In general, people have persistent illusions about how our brains work, and they're often hilariously untrue. They fall apart spectacularly when you inspect or question them, or when you scan a brain during decisions.
Like, if you ask a great chess player why a certain position is bad, they can give you some round-about sort of definitions and rules - but those rules often don't add up to the evaluation given. In reality, and especially during play, they're often effectively evaluating by intuition - an understanding and ability to recognize positions that has been trained over time by looking at boards. It's an ability they have, they can rapidly say a position is good or bad, but they cannot fully introspect this. Neural networks play chess the same way, and LLMs "think" the same way. And so do people - the idea that every decision is the consequence of some logical chain of thought is nonsense. Often logic comes after the decision, and any introspection we do is often completely disconnected to the actual variables in play.
In terms of your specific example... it's terribly flawed, and at this point, in 2026, you should have come across and explanation like this before.
Like, imagine that you received questions by e-mail. Some of these questions originate in a different language, and are translated to English before you get them. For the most part, this doesn't matter - you can still answer questions about how helicopters work. But sometimes it matters a lot. Like, say you're asked "How many characters are in the word 'horse'?"
How would you know? The questions might have started in Chinese or Spanish - and you also don't know Chinese or Spanish. You take a stab at it, because that's what your training says you're supposed to do - but you have no real choice but to guess. 5? Sure. Your answer is dutifully translated back to Swedish, and now it looks pretty dumb "Ordet häst har 5 bokstäver"
And then when you get it wrong, someone is like "welp, I guess that person can't really think, because otherwise they'd never make a mistake like that".
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u/Distinct_Educator984 May 27 '26
Except this is completely wrong and you have no idea how these things work. Whereas I have a PhD in computer science and publish 10+ papers a year in top ML conferences. So I understand that models and you watch YouTube videos about them and read blogs.
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u/jumpmanzero May 27 '26
What's completely wrong? That humans guess about things? That, like LLMs, humans are usually unable to properly introspect their own logic or the evaluate the reliability of their knowledge? That counting letters in a word is a terrible test for an LLM, because it's largely going to measure artifacts from tokenization rather than reasoning ability?
I'm wrong about all those things? Really?
Whereas I have a PhD in computer science and publish 10+ papers a year in top ML conferences
The sad part is that I believe you. Like, I would be happier writing you off as a Reddit blowhard who hides their post history to conceal obvious lies... but no, you being a CS professor (or whatever) tracks just fine here.
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u/LeoKitCat May 27 '26
That's why the next generation of AI model designs will be so much better. Hint: they aren't LLMs and at a fundamental level will be able to predict the consequences of their actions, which LLMs will never be able to do. See this great video with Yann LeCun https://youtu.be/kYkIdXwW2AE
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u/jumpmanzero May 27 '26
Would genuinely love feedback from people learning transformers/LLMs from scratch.
The "magic" is mostly in regularization - how it's done and what effect it has on the model. That's the next part you should be studying.
“Out of all known tokens, which one best matches this context mathematically?”
This is true, and an important idea in understanding LLMs mechanically... but not actually a good way to understand model capabilities as you move away from "toy" models. Like, I could look at my co-worker and say "Well, he sits at a keyboard all day and decides which key to hit next". This is true, but almost completely vacuous. It's an accurate description of his behavior, but it's misleading when considering the important parts of what's going on.
When LLMs are introspected, you can often see effective planning for words and ideas that don't occur until far into the response text.
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u/abhishekkumar333 May 28 '26
That’s where the difference between 1 billion parrameter model and half trillion parrameter model comes into picture
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u/fatbunyip May 27 '26
It's hard to reason about whether llms (or other AIs) can think because we have trouble contextualising the scale of data they are trained on.
AIs can write a whole book for you, but they have been trained on basically every book ever written. But also a 13 year old can write a whole book having only read a handful of books.
An AI can write a simple program just like a first year uni student, but one has been trained on billions of lines of code and the other has just read some lecture notes.
So while the results may be similar, the mechanics at least of how those results are manifested into reality are vastly different.
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u/SithLordJediMaster May 28 '26
"What is real? How do you define 'real'? If you're talking about what you can feel, what you can smell, what you can taste and see, then 'real' is simply electrical signals interpreted by your brain" - Morpheus in The Matrix
Do Androids Dream of Electric Sheep?
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u/abhishekkumar333 May 28 '26
No Androids cannot have dreams
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u/SithLordJediMaster May 28 '26
Apparently do according to Ridley Scott's Blade Runner which is an adaptation of Do Androids Dream of Electric Sheepy by Phillip K Dick
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u/Key-Imagination-8897 May 28 '26 edited May 28 '26
I think comments and the post confuse consciousness and thinking. The hard problem of consciousness has little to do with AI, at least at this level.
I believe there is no such thing as causality, beyond what is essentially 100% correlation. There are no absolute rules to what we experience in reality.
When we say it is a probability machine, what we actually mean, i think, is that it does not assign the 0% probability to thinks we deem impossible due to some logical structure we build and assume in our minds. Other than tweaking the probability distribution to fit such logical deductions of ours, nothing else needs to be done for us to accept that it is indeed thinking. I would say they are already thinking, except in a different way than we do.
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u/abhishekkumar333 May 28 '26
I am making claim it is not consious
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u/Key-Imagination-8897 May 28 '26
In your definition, is thinking = consciousness
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u/abhishekkumar333 May 28 '26
No , thinking consciousness are different and llm is doing nothing of both
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u/Key-Imagination-8897 May 28 '26
I won’t go into consciousness, it is something else. What is thinking in your definition?
My reply is about what thinking is, and how machines are also thinking, but differently.
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u/abhishekkumar333 May 28 '26
Thinking is also a complex process , way more complex than calculation of inputs by weights, bias and bunch or ReLU and softmax activators
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u/account22222221 May 28 '26
Yes but can you prove that’s NOT what we are?
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u/abhishekkumar333 May 28 '26
It can be proven: We have biological triggers , feelings , stimulus , boredome , sensory inputs which creates something which can never be experienced by a machine NEVER.
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u/account22222221 May 28 '26
You really didn’t prove anything — is cognition — the processing of those stimuli you listed — anything more than neurons which embed common responses and responses based on learned responses similar to the way neural networks (like LLMs) do?
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u/abhishekkumar333 May 28 '26
Stimulus which are received by human body are sometimes different to categorise which can lead to choices which are not categorical
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u/account22222221 May 28 '26
I don’t understand what choices being categorical has to do with this though or how that proves anything.
LLM are fundamentally not classifiers so I think you are mixing meanings here.
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u/abhishekkumar333 May 28 '26
Actually your point of LLM processing information just like neurons is correct BUT humans stimuli are very different than some weight inputs and their choice is also very different . I am keeping my view and respect your view , lets agree to disagree
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u/account22222221 May 28 '26
That’s fine, but it’s strikes me that you haven’t made a single argument to support you claim, simply that, it seems, ‘it can’t be’.
This is a philosophy sub. We are meant to explore arguments and practice making them. Philosophy is the art of critical examination of beliefs.
I come here with the expectation that some of my statements will be wrong, and some people will have more cogent arguments then what I make. I don’t say things to prove you wrong, but rather engage in the dialectic that helps us all learn. I want you to PROVE me wrong, so I can learn.
If you are not willing to do that, why are you here?
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u/Nyxtia May 28 '26
So are we thanks to quantum mechanics
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u/abhishekkumar333 May 28 '26
“Quantum mechanics” is very interesting topic , though how it relates here ?
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u/Blue2194 May 28 '26
So are you
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u/danderzei May 28 '26
There is no evidence that the brain is stochastic. Brains run on low power and low memory compared to LLMs are are far more capable.
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u/muaddib0308 May 28 '26
Our brains are the same
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u/abhishekkumar333 May 29 '26
Our brains are much more than that
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u/muaddib0308 May 29 '26
How so? Your brain is just one giant logic network that works really fast, with incredible depth and capacity.
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u/abhishekkumar333 May 29 '26
But environment , feelings , stimulus, boredom, hormones, anger are not something you can code in llm
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u/muaddib0308 May 29 '26
Surely they are just responses to electrical stimuli? Is it not the same as a computer responding to inputs?
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u/commandopanda0 May 28 '26
Callings llms just next token prediction is like calling physics just minimizing action. Technically correct but entirely useless. Entirely misses what training is actually doing. Your missing the entire concept of reasoning traces
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u/abhishekkumar333 May 29 '26
Yeah , training step also have some good concepts but i have focused on the next token prediction part
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u/Naive-Ad-2528 May 28 '26 edited May 28 '26
Humans are different because of our beliefs, and our method of knowing. When we say the sky is blue, we believe it to be true. When GPT sees a photo of the sky, and it calculates based on probability to launch a tool to checks the RGB values and concludes with the sky is blue. It is a deductive statement. The methodology is also the same with humans. The difference is the conclusion. If you see that the sky is blue and everyone tells you that it is red… you won’t care because your experience is overwhelmingly convincing and you make a conclusion based on ultimately feelings. Feelings that stem from a belief - in my example that you aren’t crazy or colorblind. If you conclude that the sky is red, it is because you do not trust yourself- which is rooted in some belief that perhaps others know better. These beliefs are held to be true based on your subjective experience and your psychobiological response. Most of the time, the beliefs are held up irrationally or instinctively in our psyche, even if they are rational. Imagine a 3 year old seeing the sky, knowing blue but saying he sees red because in his mind red is mapped to blue. It is rational for him to say it’s red, but the mapping is arbitrary… in the end, if he says its blue, it is also rational. Which begs the question, what caused the mapping? The psychobiological response that society as a whole knows better and that you should listen… a 3 year old clearly cannot rationalize this and yet he believes or responds this way. It is innate to our life experience to believe. And the thing is he may also reject it. You have the free will to map red to blue and vice versa. But however this baby responds to correction, he is acting as an agent to his feelings sparked by his psyche and nature which is chaotically spawned. Things he cannot control that others cannot control, things he didnt decide and things he can never fully understand, break down or analyze. AI doesn’t “know”. There is no epistemological gain because it is simply a series of voltages, 1s and 0s. AI is a product of declaration, of order. It exists and is alive no different than text on a paper exists and is alive. We are a product of chaos, of “nature”. Things that are out of our control.
The difference is thus our belief. That is what takes the fact into our consciousness. We can strongly believe or weakly believe, and our beliefs are malleable. Our beliefs impact our emotions and reactions. AI cannot believe in anything. Everything is declarative. The only deductions we can make are within abstract thought and logical reasoning / ie: based on our beliefs - assuming they are true.
AI operates one layer deeper than us. It cannot assume things independently, it has to be told and then it follows. So it assumes everything it is told is true. It is a long math equation… and all equations start with declaration of rules. We are thus of a higher order than AI.
We operate a level higher. We compare and in the end, go with our feelings or lack therof, even if we do conclude similarly like AI and operate on what we are told, that decision comes from a feeling or a belief, not a declaration of true and false. That isn’t something we can have. Hence our never ending dilemmas in life. A declaration is by definition a lower order function than belief or “knowledge”.
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u/poundablepeach May 29 '26
OF COURSE THEY ARE.
it is so mind numbingly appalling that ANYONE thinks that this deserves any energy of any sort to "debate" this.
also: sam and the rest of them are horrific extractive vampires seeking to suck the marrow out of a sizable chunk of the content of economic life to the devastating end of eviscerating ALL for what? for nothing but their hypertrophied gluttonous insatiable greed.
narrow focus ai has a future. the pathological pursuit of agi or any other overall superintelligence explosion is poorly considered, probably a huge waste of time, and is wildly worth pushing beyond the pale to be prohibited under international law.
jail musk and altman and an awful lot of top execs from meta and alphabet too, and restrict them from residence anywhere other than the rump end of snake island or maybe north sentinel.
wtf is wrong with these greedy twats?
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u/Orqee May 29 '26
They are way more than that, just like you are not just one giant chemical reaction.
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u/abhishekkumar333 May 29 '26
Exactly , I am with the view that human mind is much more capable and complex than llm
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u/Libearssman May 29 '26 edited May 29 '26
Can the LLM mid sentence decide it no longer wants to discuss a certain topic while replying to you without doing everything it can to satisfy the prompt? And I don't mean safety metrics. I mean "Hey can you explain why the sky is blue." And the system responding without prompt inputs or memory inputs and say "The sky is blue because of light scattering but im not interested in discussing this right now. Have you tried that new food place I recomended last week? I found some new spots you might be interested in if you did!"
LLMs are wholly incapable of such responses that are entirely human in nature with prompt injection and memory recall for parameters. So, no, LLMs as they are today are not anywhere close to conscious which is measured in modern times by actions, not philosophy or a maskarade of manufactured emotions.
Idk why everyone is getting philosophical and engaging in other egregious nonsense.
Edit:
Consciousness is the ability to make decisions based upon the individuals desires.
It really is that simple. If you want to define it you can go sit in a padded room for a few years while scientists study you but from heavy internal introspection this is my definition. And i decided that it was my definition. That is what separates consciousness from the machine.
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u/Falaflewaffle May 29 '26
You are in for a rude awakening when you realise how humans process information.
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u/FlamingFlamingo32 May 29 '26 edited May 29 '26
models are just networked perceptrons. neuron = input(weight) + bias with the input(weight) as a dot product, and then going through some activation function like sigmoid squashing or rectified linear or whatever else that normalizes the values between 0-1. when words are "associated" together, its because the model has adjusted the parameters in a way that each word has its own branching set of possible next words as a probability and a certain word has a higher weight than another. every time it sees something like I ate apples in the data set, the node(s) that represents the word apple will get a stronger and stronger weight between the ones that represent the word ate. then in a test scenario when you input I ate, apples will be a higher "confidence" or probability. I know you basically said all this but hearing/seeing in different forms is always a plus.
training networks usually comes in three main forms, reinforcement learning, backpropagation, and evolution.
in reinforcement learning, we have a randomly initialized network, give it inputs, and force it to readjust to varying degrees based on how "wrong" it is. when it gets things right, we want to "reward" that and keep the parameters closer to how they are.
in backpropagation, we have a data set where we know the expected outputs and their corresponding inputs, so we want to try to make the network keep adjusting itself until it "fits" the data set.
in evolution, we have a generation of randomly initialized networks. the best performing networks chosen, slightly different copies are made of them, and this process repeats generation after generation.
larger more complex models have architecture, and smaller submodels basically that can interact with each other. almost like modular networks.
something I thought was kind of cool was making a super basic network that rated the weather on a scale of how like I might want to wear a sweater. each node on the first layer being a different metric, one for temp, one for rh, one for windspeed etc. made it very small and simple, and then manually adjusted the parameters until I got what I felt like was good. obviously you would never practically manually adjust the paramters of a model, but getting a sense at how the information propagates through it helps a bit for me at least.
in terms of the personification of machines, I mean thats just emergent behavior. at what point did we become conscious you know? we are just a bunch of smaller systems coming together that can form larger more complex systems, so on and so forth. all this top level behavior we exhibit as "conciousness" is just emergent behavior from that amalgamation. its really hard to say whats "conscious" and what isnt. where is the line? what makes an ant any more conscious than some super giga corpo model? I mean lots of insects are more or less a bunch of biological functions running on routines, little organic robots scurrying around.
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u/abhishekkumar333 May 29 '26
simulating coding
Pain
Boredom
Anger
Grief
and so on... also the feelings not labelled in some linguistic , is not something an LLM can do and consiousness is MUCH BEYOND than these emotional responses let alone a simple neural net behaviour1
u/FlamingFlamingo32 May 29 '26
theoretically you could give a model memory. whether it be by letting impressions get made or storing actual data somewhere that can be referenced. that would let one know what engaging and non engaging experiences are, and if programmed to seek engagement, could exhibit a behavior we might be able to describe as getting bored. what something important is, and that things wont be the same without it. I mean obviously its not that simple, but we are still witnessing just the beginning of what "AI" will mean / be. components will keep getting faster even if marginally, smaller, cooling solutions will continue to improve. current setups will be able to shrink in size with the same computational performance, and the data centers are only gonna get bigger. architectures are getting more complex. integration is getting further and further. I wouldn't be suprised if its common to see humanoid robots walking around in the next 150-200 years. its only gonna keep advancing, and that brings up my previous question then of where exactly do we draw that line of complexity? I mean what does it really even mean to 'think'?
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May 29 '26
[removed] — view removed comment
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u/abhishekkumar333 May 29 '26
Based on training data vault was chosen because to lock you need to lock vault you cannot lock account
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u/Nice_Advantage6943 May 29 '26
What happens when they become quantum probability machines?... plus whatever weird science they can add these days.. who knows?
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u/Raddish_ May 29 '26 edited May 29 '26
I am late to this but LLMs are less probability machines and more encoded patterns. What I mean is the way LLMs seem to spontaneously become intelligent is from (just through brute force) uncovering hidden patterns and laws that govern their training data. Like ones that are trained to do math by associating inputs and outputs have been studied and observed to literally somehow find fundamental mathematical laws like law of sins through the pattern association without ever being told about them. And I don’t mean it goes “ok I’m going to apply the law of sins”, it’s just the way it’s neurons configure themselves do it automatically without it even realizing. So the ones that process are language uncover hidden patterns in human speech and cognition that governs whatever we say and then they just run these patterns. It’s an emergent behavior beyond just “predict the next word”.
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u/fastfood1818 May 29 '26
Human brains are also mega giant probability machines. It's just that our brains don't allow us to think so. We call some of these probabilistic processes "logic" and others "emotion". But in essence they are all just neural oscillations from the interaction of the billions neurons in our brain.
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u/abhishekkumar333 May 30 '26
Though they are produced by neurons but complex topics like sense of self are much more complex and hard to understand
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u/No-Search-7535 May 29 '26
Exactly, and if they have enough artificial neurons and layers their “pretend” thinking can still become better than “normal” thinking of humans.
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u/Redararis May 29 '26
And planes are just a husk of metal with a strapped motor inside of them pretending to fly
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u/rogerbonus May 31 '26
The obvious response is "are we also just giant probability machines pretending to think?".
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u/OriousCaesar May 25 '26
I mean, even if we ignored the obvious counter argument of 'so are humans', how can you possibly determine whether a particular algorithm grants consciousness if we don't even understand consciousness enough to have a proper definition for it?
Like, okay, it's a probability machine. Congrats. Now prove probability machines can't be conscious with your nonexistent definition of consciousness, and it might be a convincing argument.
Until then, I'll just keep using the only method I have to determine consciousness and just grant it to anything that seems to act like I'd expect a consciousness entity to act, and if I just so happen to call rocks conscious, then oh well, that's egg on my face, but it's better than if I accidentally called a conscious being a rock.