[codeflo]

> These theories are flawed in the sense that they cannot account for subjective experience and agency, amongst other things.

On the contrary, it's precisely this assumption, that there is a "subjective experience" that requires explanation beyond the material, that is axiomatically assumed without evidence. It falls apart quickly, any "subjective experience" is completely tied to neurons, knock out the neurons and the subjective experience disappears, or stimulate the neurons to cause the experience.

[SlinkyOnStairs]

There's two meanings to "the body is a complex machine" and I think you're missing the forest for the trees here.

1) The abstract "dictionary" version: It'd be technically correct to say that the body is a machine under the definition of "A machine is a thermodynamic system that uses power to apply forces and control movement to perform an action.".

2) But there's also the less abstract/technical: "The body is alike the complex machines we have built", and this is much less true. Especially for the brain. The "neuron" analogy in machine learning is effective, but entirely wrong; We do not fully know how even a single neuron works, nevermind any complex system made out of multiple of them.

With regard to AI, there's a lot of people extrapolating "There is no magical animating spirit, the brain is just a pile of stochastic molecules following the laws of physics" into "The brain is an inert pile of matter, computers are an inert pile of matter, ergo AI/LLMs are like the brain!"

Especially so by people who have a financial/legal interest in doing so. "AI is just like a brain, fire your employees and buy our LLM now!", "AI is just like a brain, so it's totally not copyright infringement!"

[aspenmartin]

> With regard to AI, there's a lot of people extrapolating "There is no magical animating spirit, the brain is just a pile of stochastic molecules following the laws of physics" into "The brain is an inert pile of matter, computers are an inert pile of matter, ergo AI/LLMs are like the brain!"

Why do you need a specific organization of molecules for a phenomenon similar to consciousness to arise? Does anyone seriously consider a brain to be something other than “a pile of molecules following the laws of physics”? If so that’s not science or philosophy, that’s religion. You have a virtually complete phenomenological model of the universe for all intents and purposes and yet somehow the onus is on the person being like “hey no laws of physics are being broken ==> the brain is simply following the laws of physics”

How is it possible that people think of subjective experience and get rabbit holed into some mystical world where subjective experience is this special exception to everything else that is simply an emergent property of complex physical systems? “AI/LLMs are just like the brain” is a strawman, why does this claim need to be true for LLMs or any artificial system to be considered to have something akin to the thing you think of as consciousness? It’s more: consciousness is not some mystical or religious thing outside of the realm of physics, it’s an emergent property of a complex system. AI is a relatively complex system. We don’t really know or understand the relationship between the raw physics and again what we consider consciousness, so it’s simply a statement of “we can’t refute that these systems exhibit something similar” because we don’t know enough to refute that

[SlinkyOnStairs]

> Why do you need a specific organization of molecules for a phenomenon similar to consciousness to arise?

They would have to be similar because the argument is that they are similar; "AI is like the human brain" only holds true if it actually is like the human brain, not merely a superficial resemblance.

What I'm describing in that prior comment is how a lot of people drastically simplify the resemblance in order to make it feel true; That the lack of a Jesus Christ coming down from the heavens to tell everyone they have immaterial souls that the computers don't makes the comparison more true.

> We don’t really know or understand the relationship between the raw physics and again what we consider consciousness, so it’s simply a statement of “we can’t refute that these systems exhibit something similar” because we don’t know enough to refute that

Therein lies the conflict: "You can't prove it's not conscious" is an unfalsifiable statement. You can't engage with the argument because it's proponents will always claim victory, often with their own interests at play. All concerns about "superintelligence" or the long term ethics of "when do our robots become sufficiently intelligent that they'd be slaves?" have been subsumed into the AI marketing machine. However sincere one might try to address the issue, they look like a Sam Altman stooge by association.

It's like claiming the quantum fluctuations inside a pet rock as a "consciousness", even if observed directly any measurement of random noise can still be dismissed as "nuh-uh it just takes billions of years to have a thought".

More practically with current AI systems, we can look inside them pretty well and there genuinely is nothing there. Standalone LLMs are purely feed-forward systems. Their failure modes show that they perform no meaningful thought or world modelling during inference. They're just language models.

The reasoning and agentic systems are even easier to introspect. We know how they work, we can look at the full prompts & context they operate on. There is nothing there.

This is what sets AI apart from animals, which are given the benefit of the doubt on their intelligence.

[wredcoll]

> “AI/LLMs are just like the brain” is a strawman, why does this claim need to be true for LLMs or any artificial system to be considered to have something akin to the thing you think of as consciousness?

It doesn't need to be true but a lot of people make it/assume it.

There's a lot of, perhaps casual and uninformed, conversations that strongly imply a deeper understanding of the "physics" of brain chemistry than we actually have, mostly by comparing it to machines we've constructed.

(I believe) We don't need to replicate human neurons and dendrites and whatever else is in there in order to create a sapient "machine", but whether or not we've actually done that isn't being helped by arguing that what we currently have is all that similar to a human brain.

[calepayson]

I think the point of the commentator above is that there are two extreme narratives that start each start with an uncontroversial assumption and then taking it to a pretty wild place. One narrative takes the assumption that brains are just matter so it should be possible to engineer consciousness and then argues that LLMs are conscious. The other takes the assumption that LLMs aren't conscious but then argues that because they aren't we won't ever be able to make anything conscious.

I don't actually think the commentator you responded to is arguing for either of these narratives and I thought it was a pretty useful way to look at some of these arguments.

[sixeyes]

oh yeah! i recall a paper linked here not so long ago, where it was shown that the dendrites of a neuron do computations themselves. The "weight per neuron" is very simplistic then. At the very least, each actual neuron is a network of weights.

https://www.quantamagazine.org/neural-dendrites-reveal-their...

[ACCount37]

I'm partial to "modern ML weights are much closer to 1:1 capacity mapping to synapse count than to neuron count". A single biological neuron is closer to 100 or even 1000 weights worth of ANN than to 1 weight worth of ANN.

In which case: modern LLMs are still running in a capacity-starved regime!

Even Mythos 5, the 10-trillion monster LLM, the scaling law boogeyman, the harbinger of Vera Rubin NVL72, doesn't quite rise to 100T-to-1000T of synapses. Anything the light of today's AI touches still lives in the shadow of what evolution has managed to cram into a single human skull.

We're arguing about the limitations of AI while our best AIs are still very subhuman in the scale dimension. The one dimension we know how to push. And it's already this tight.

[SlinkyOnStairs]

> A single biological neuron is closer to 100 or even 1000 weights worth of ANN than to 1 weight worth of ANN.

Even those comparisons need to be cautioned. The complexity of biology is enormous, and more importantly yet, it's simply not comparable. And doing so invited a bunch of bad assumptions.

An ANN could quite probably model a single in vitro neuron with reasonable accuracy. Whether that requires a hundred or a hundred million nodes isn't terribly relevant.

But the way neurons combine in vivo is completely unlike the way machine learning systems are built. Both "locally" in how neurons interface which is vastly more complex than a weighted sum of inputs, and the macro scale interactions of hormones and other chemicals.

It's not even a given that large numbers of neurons will create the emergent behaviour of human intelligence; Elephants have significantly more neurons, but they're not the triple galaxy brains writing all our science papers. Other animal intelligence similarly is only loosely correlated with brain complexity. (Heck, not to be forgotten is the other end of the scale. Plenty of microscopic life that manages shockingly complex behaviour without any dedicated neurons)

This also applies to ANNs. There's no reason to expect that stuffing enough matrix multiplications into a program will make it intelligent or turn out conscious.

Really, the history of machine learning suggests the opposite; That the big gains are primarily had in architectural changes.

In this regard, I find the talk of the "limits of AI" quite credible. LLMs have already hit the diminishing returns on their growth, and even reasoning/agentic models display failure modes that confirm they're not "thinking" in the ways that humans do.

This is not to say that we've hit the final limits of what AI in the broad sense can do, it's just that the next advancement won't be "LLM but even bigger"

[ACCount37]

Not really. The history of "big gains" of machine learning is: put together a simple architecture that makes few assumptions but scales well. Then up the data and compute by 2 OOMs. By itself, the new architecture underperforms. Paired with the bitter lesson, however?

Don't make assumptions. Make a setup where the gradient descent can make them for you.

Empirically? LLMs are nowhere near "the wall". We've been hearing "the wall is nigh" since 2020. Six years in, we're still scaling LLMs, and the graveyards are full of "LLM killers". The system that kills the LLM is always a bigger, badder LLM, and never a new revolutionary architecture. The scaling doesn't just keep working - it works so well that it's seen as the only viable path forward at the frontier of reasoning and agentic work. Or even outside it. ChatGPT Images 2.0 is an image model with an agentic LLM at its core - generational gains in compositional capability.

For just about every "failure mode that confirms they're not thinking", you see one of two things. The first is that a new LLM releases a few months after and the "fundamental" issue abruptly goes away. The second is that we take a good, long look at a human, and find that the human also fails like this - and thus, "not thinking". Often both! Always funny when it's both.

One thing that's very biologically distinct is: local connectivity. In a GPU, global connectivity is cheap. In a brain, it's prohibitively expensive. The brain has no true backpropagation because it has no true global connectivity, and has to make do with local rules. A GPU is a strictly more expressive substrate connectivity-wise. So any point in the design of a computational substrate where you could remove complexity or increase performance by adding more connectivity? Silicon advantage. The brain isn't a "strictly better computational substrate" - it makes different tradeoffs. Which tradeoffs are better for attaining intelligence is an open question.

And, sure. Having a substrate with a capacity for intelligence doesn't mean having intelligence. No elephant has ever learned to code. The problem is: LLMs already did! LLMs already compete with humans on just about every task that was once thought to "require human intelligence". They don't always win - but they perform significantly above chance, and often above an average non-expert human.

So, my bet is on "LLM but even bigger". If there's a point where LLMs begin to lag behind and novel architectures get a sharp advantage, we are yet to hit it.

[f_klem]

> For just about every "failure mode that confirms they're not thinking", you see one of two things. The first is that a new LLM releases a few months after and the "fundamental" issue abruptly goes away. The second is that we take a good, long look at a human, and find that the human also fails like this - and thus, "not thinking". Often both! Always funny when it's both. The way machines 'don't think' or 'fail' is fundamentally different from the way humans don't think or fail. In any case, the way LLMs learn and human beings learn is completely different. There is no actual clue that we are approaching any inflection point in machine 'learning'.

> So, my bet is on "LLM but even bigger". If there's a point where LLMs begin to lag behind and novel architectures get a sharp advantage, we are yet to hit it. We are already hearing this 'we are about to hit it' since the late 60s. The difference now is that the market is willingly investing insane amounts of money to make it possible. But again, there is no philosophical, theoretical, epistemological or biological clue that we are getting any closer to human intelligence level. What we did observe in the last decade though, is that we can build enormous machines that can statistically mimic statistical human outputs. Language and images being some of them. But that is not thinking.

[galangalalgol]

10T is about a crows worth. The mythos count doesn't include any diffusion model. But the crows count includes all its visual processing. And tactile. Touch uses up enough that they use skin surface area to normalize across animals when doing comparisons. It is one of the reasons suggested to explain how crows exhibit tool use and language with only 10T. We have a lot more skin than crows, and indeed far more than mythos.

[f_klem]

I agree, we can miss the forest for the trees.

1) This definition could actually be expanded (for example, with definitions from Mumford or Reuleaux). But still this definition cannot be applied directly to living organisms. 2) This is in my opinion one of the sources of misunderstanding. We mainly operate on analogies and metaphors, so we have build this 'analogy space' around the idea that living organisms are machines. But it is only when we say 'alike' that we can truly gather some meaning out of it all, going beyond the 'behaves like' or 'is conceptualized as' when it gets messy.

> With regard to AI, there's a lot of people extrapolating "There is no magical animating spirit, the brain is just a pile of stochastic molecules following the laws of physics" into "The brain is an inert pile of matter, computers are an inert pile of matter, ergo AI/LLMs are like the brain!"

This is exactly my point. There is a fallacy operating from "A is not B" to "A is C". And this fallacy is pervasive in the AI research field, the book from Dreyfus (What Computers can't still do) explains that in much detail.

[calepayson]

> 1) This definition could actually be expanded (for example, with definitions from Mumford or Reuleaux). But still this definition cannot be applied directly to living organisms.

I'm not sure I understand this. Why not?

[f_klem]

It has to do with words and how we evolve words throughout history and across geographic boundaries. The term 'machine' comes, after some modifications, from the greek word mekhanos, which was used to describe something ingenious or a device made in some clever way or operating in a clever way. From there it went on to describe things like devices, to end up being the actual definition of what we might call 'a device' (a machine). The idea of 'mechanistic' is also related.

Traditionally, things that are alive were described with different words and assigned a different set of properties and characteristics. Machine can break, living things die. And we still have those two semantic frames separated: A living thing: can be harmed, it breathes, it nourishes, it reproduces, etc A machine: can break, can be fixed, can be repurposed, etc.

But because of a specific tradition in western philosophy, we started applying and analogy between 'inner mechanism (clever thing), that moves or provides a function, and seems to work in a causal way' and living things.

So when we say 'a living cell is a wonderful, complex machine', we are not actually saying it is a machine, we are operating through an analogy. That's how far we can go.

[JulianChastain]

I find the claim subjective experience may be illusory absolutely baffling. I can only speak for myself with certainty, but I am entirely sure I have subjective experience. All the other propositions I believe could be false but I don't see how I can be wrong about experiencing something. I could be a brain in a vat (or weights on a GPU) and be specifically programmed to only come to false beliefs and still I can be sure that there is an experience I am the subject of. I cannot provide empirical evidence for my experience, that is why it is subjective. I cannot be entirely sure you are experiencing anything, and when I encounter people who don't share the same baseline intuition here I do begin to wonder if this is truly a universal across humanity. But I can't think of any other assumption which I would be more comfortable as a foundational axiom other than, "I am experiencing something." I do not require additional evidence for it because I experience the truth of it directly

[Self-Perfection]

My current understand that "subjective experience" is a post effect of memory forming in the process. "I experience X" ≈ "I remember that I just recently received [external stimulus / interpreted my current state as] X".

And I am as well baffled why people make such a big deal out of "subjective experience" and "consciousness".

I was joking that maybe I miss this properties, but now starting to really wonder if it might be the case. What if these phenomenons are present in humans to various extent? Check aphantasia. Only in XIX we discovered, that ability to visualize mental images is not universal, available to different people to various degree and some people completely miss it. My ability to visualize is weak. What if "consciousness" and "subjective experience" are similar?

And I am slightly worried when I am writing this that it might turn to be truth and in ~20 years I will be treated as "inferior human" without complete set of human rights.

[edbaskerville]

Indeed. Even positing an illusion seems like a contradiction. If it's illusory, doesn't there need to be a subjective entity experiencing the illusion?

[MichaelZuo]

This proves too much. As it would imply parrots have sapiencee.

[jazzypants]

Why do you think that parrots do not have sapience? How would one even measure such a thing?

[beering]

Because by definition, sapience is something only humans have. Ergo, parrots are not sapient.

More meta, all of the threads on this page are just people playing games with definitions. Eg, “qualia is something I have as a human but machines don’t have it. Therefore, LLMs do not have qualia.”

[jazzypants]

You're confused about the etymology. Homo Sapiens was coined in the 1800s. People have been saying "sapient" since the 1300s, and it is rooted from the Latin word "sapientem" which simply means "sensible; shrewd, knowing, discrete". Homo Sapiens just means "wise human", and we humbly bestowed the name upon ourselves.

https://www.etymonline.com/word/sapient

https://en.wikipedia.org/wiki/Human#Etymology_and_definition

[f_klem]

> More meta, all of the threads on this page are just people playing games with definitions. Eg, “qualia is something I have as a human but machines don’t have it. Therefore, LLMs do not have qualia.” True. For me, the actual interesting debate is not if LLMs are intelligent or not (easy to dismiss) but to what extent LLMs embed into our socio-techno-economic reality.

[kristov]

I think the truth lies somewhere between these two extremes. An LLM is not a human brain, and does not try to emulate one. It should not be a surprise that an LLM does not behave like a human brain. So we can not infer things either way. The best we can say is that an LLM appears to exhibit very similar behavior to a human brain, under certain constraints. So maybe we can infer that the human brain has something in it that operates in a similar way to an LLM (like the human "unconscious", or "intuition" maybe). It seems obvious to me that a human brain and an LLM are not comparable things, for many reasons. So we can not make inferrences one way or the other.

[dnautics]

> An LLM is not a human brain,

true

> and does not try to emulate one

citation please.

something like the universal approximation theory comes to mind, transformer architecture clearly has the shape of a universal algorithm approximator

[calepayson]

I think you're right in that it has the shape but I think it's missing a pretty key piece. We still haven't been able to solve catastrophic forgetting, yet everything with a brain has. Basically LLMs seem good at approximating intelligence on a moment-to-moment basis, but feel quite far away when you chat with one over time.

Like at some level, yes, transformers are trying to emulate a human brain but the second you ask folks if they do a good job of it, I think most rationale people would say no.

[cootsnuck]

> something like the universal approximation theory comes to mind, transformer architecture clearly has the shape of a universal algorithm approximator

That says nothing about emulating a human brain.

[dnautics]

is human cognition not an algorithm? is it just woo? or vibes?

[kristov]

But what is the shape of the algorithm of the human brain? It has a complex physical structure. We know the folds on the surface are important, but why is that shape specifically important? The brain is made up of two hemispheres - why, what does that do? There are different "types" of brain inside the human skull. There are physical areas that perform specific tasks. There are different types of neurons. Then there chemicals that interact with the brain, changing how it function depending on things happening to the body. All that stuff and more is the "algorithm" of the human brain. It's not the same algorithm as an LLM.

[llmssuck]

Interesting, so you would say that your experience is .. illusory? In what medium exactly? Illusion requires a substrate of some kind. "Awareness"? What's that?

Neurons are themselves things we experience (indirectly). Once seen through a microscope or known about in some fashion the only way they "exist" is by you having the experience of knowing them. It's not the other way around. One thing is more fundamental here. What is this experience? What are the atoms of this? "Atomic particles"? How would you even approach an answer if your building blocks are themselves part of what needs to be explained?

The hard problem cannot even be touched if you start out like this.

[jimbokun]

It’s the opposite.

Descartes made clear that subjective experience is the ONLY thing we know. Everything else is theories to explain the phenomena we subjectively experience.

We theorize that there is a physical world and other beings like us having similar subjective experiences, because that seems the best explanation for our subjective experiences. But we might be living in the Matrix, with all the people we think we are interacting with and just sophisticated simulations.

[aspenmartin]

And this has some bearing on the debate about whether these systems do or could in the future exhibit something similar?

[bogdanoff_2]

If we go along with the though that our own subjective experience is the only thing we truly know, and that we cannot really know if any other humans are having the same experience (and any belief of that sorts is purely extrapolation), then there isn't a fundamental difference between LLMs and "other humans" in terms of whether or not they're "conscious". Sure, it appears more likely that "other humans" are real conscious beings, but there's no fundamental difference.

>whether these systems do or could in the future exhibit something similar?

I think the whole discussion is based on the idea that consciousness isn't something you can "exhibit". (Tell me, how can you "exhibit consciousness"?)

[f_klem]

Refuting the "subjective experience" axiom does not lead to 'any "subjective experience" is completely tied to neurons', you also need to explain why the subjective experience is tied to neurons. And that's precisely what computational theories of mind do not account for: the link between subjective experience and neurons. I am not arguing that neurons (or the brain) are not a necessary condition for subjective experience.

[stonogo]

"that is axiomatically assumed"

passive voice doing a hell of a lot of work in this phrase

[tuyiown]

> at requires explanation beyond the material, that is axiomatically assumed without evidence

Nobody talked about anything out of neurons. The question is still open.