From an external point of view, cognition is private and indirect. From an internal point of view, cognition is public and direct. So Husserl and Descartes can be both semantically correct, provided that we don't mix their postulates and apply them in different contexts. — sime

Husserl’s point is that the external , third person point of view is a derived abstraction constituted within first person subjectivity.

That bothers me since it contradicts physicalism since there can be physical things that cannot be known, even in principle. Science cannot render to a non-bat, even in principle, what it's like to be a bat. So I would prefer a different definition. — noAxioms

OK. So what is 'physical' in your view? IIRC you also agree that physical properties are relational, i.e. they describe how a given physical object relate to/interact with other physical objects.
'Scientistic physicalism' is also inconsistent IMO because, after all, that there is a physical world is not something we discover by doing science.

Other than 'consciousness' I also believe in the existence of other things that are 'real' but not 'physical'. I am thinking, for instance, of mathematical truths. But this is perhaps OT.

Materialism typically carries a premise that material is fundamental, hence my reluctance to use the term. — noAxioms

Ok, yes. But it does sometimes clarify at least a meaning that 'physical' can have. For instance, if by matter one means "whatever object exists in a given location of space in a given time", would you agree that this is also what you mean by 'physical'? Note that this would also include radiation not just 'matter' as the word is used by physicists.

Has consciousness a 'definite location' in space, for instance?

People have also questioned about how eyes came into being, as perhaps an argument for ID. ID, like dualism, posits magic for the gaps, but different magic, where 'magic is anything outside of naturalism. Problem is, anytime some new magic is accepted, it becomes by definition part of naturalism. Hypnosis is about as good an example as I can come up with. Meteorites is another. Science for a long time rejected the possibility of rocks falling from the sky. They're part of naturalism now. — noAxioms

OK. But IMHO you're thinking in excessively rigid categories. Either one is a 'physicalist/naturalist' or one accepts 'magic'. Maybe there is something that is not 'natural'. Again, mathematical truths seem to me exactly an example of something that is not natural and yet real. One would stretch too much the meaning of 'natural/physical' to also include mathematical truths in it.

So, I guess that my response here can be summarized in one question for you: what do you mean by 'physical' (or 'natural') and why you think that consciousness is 'physical'?

Agree. — noAxioms

:up:

Yes, I guess it depends on how easily convinced you are about this being case. For me, without further reason to believe otherwise, it seems like the biggest roadblocks in modelling something like the brain is intractable complexity. There is no indication that in principle we cannot someday model all our own behaviors and reports through computer models. I think even just looking at AI now indicates that there isn't really a conceivable limit on what they can do given enough power and the right inputs, which is what you might expect from something which is Turing complete: i.e. they can compute anything in principle.

There is no indication that in principle we cannot someday model all our own behaviors and reports through computer models. I think even just looking at AI now indicates that there isn't really a conceivable limit on what they can do given enough power and the right inputs, which is what you might expect from something which is Turing complete: i.e. they can compute anything in principle. — Apustimelogist

The results of modeling the brain on today’s computers, using today’s forms of computer logic, are precisely as you describe. And they will colossally miss what philosophers and psychologists are coming to appreciate is the central feature of brains; that they are embodied and enactive. So,no, it won’t be today’s generation of A.I. that can express this understanding, and it has nothing to do with power and inputs. In about 10 to 20 years, we will likely see the emergence of a different kind of A.I. operating according to a different logic, that of complex dynamical systems ( cds).

Ultimately, CDS-based AI chips may blur the line between computation and physical processes, resembling intelligent materials more than traditional silicon. As Stephen Wolfram notes: “The most powerful AI might not be programmed; it might be cultivated, like a garden of interacting dynamical systems.”

When AI chips fully integrate complex dynamical systems (CDS) models, they will likely diverge radically from today’s parallel architectures (e.g., GPUs, TPUs) by embodying principles like self-organization, adaptive topology, and physics-inspired computation. Here’s a speculative breakdown of their potential design and function:

Architectural Shifts: From Fixed to Fluid.

Current A.I. Chips:

Fixed parallel cores (e.g., NVIDIA GPU clusters)
Deterministic von Neumann logic
Digital (binary) operations
Centralized memory (RAM)

Future CDS AI Chips:

Reconfigurable networks of nano-scale nodes that dynamically form/break connections (like neural synapses).
Nonlinear, chaotic circuit exploiting emergent stability (e.g., strange attractors).
Analog/quantum-hybrid systems leveraging continuous dynamics (e.g., oscillatory phases).
Distributed memory where computation and storage merge (like biological systems).

Sure we do. Q3 is easy. The ball-catching robot was one. A fly evading a swat is another. If one is searching for a model, you start simple and work your way up to something as complex as how our experience works. — noAxioms

But I reject the breakdown into those three questions, if you're going to insist that neuroscience cannot ask Q2.

The hard problem is Q2 and it is legitimate for science to want to know how a neural net can have experiences.

It seems a bit pointless to me to keep deflecting from the hard problem to declare that there is no hard problem.

I mean, none of this has any relevance to any points I am making. Obviously, to artificially recreate a human brain to acceptable approximation, you need to construct this computational system with the kinds of inputs, kinds of architectures, capabilities, whatever, that a human does. I am not making any arguments based on specific assumptions about specific computing systems, just on what is in principle possible.

↪Joshs
I mean, none of this has any relevance to any points I am making. Obviously, to artificially recreate a human brain to acceptable approximation, you need to construct this computational system with the kinds of inputs, kinds of architectures, capabilities, whatever, that a human does. I am not making any arguments based on specific assumptions about specific computing systems, just on what is in principle possible. — Apustimelogist

I will say bluntly that no machine we invent will do what we do, which is to think. As Evan Thompson wrote:

LLMs do not perform any tasks of their own, they perform our tasks. It would be better to say that they do not really do anything at all. Thus, we should not treat LLMs as agents. And since LLMs are not agents, let alone epistemic ones, they are in no position to do or know anything.

The map does not know the way home, and the abacus is not clever at arithmetic. It takes knowledge to devise and use such models, but the models themselves have no knowledge. Not because they are ignorant, but because they are models: that is to say, tools. They do not navi-gate or calculate, and neither do they have destinations to reach or debts to pay. Humans use them for these epistemic pur-poses. LLMs have more in common with the map or abacus than with the people who design and use them as instruments. It is the tool creator and user, not the tool, who has knowledge.

I think what he wrote about LLM’s applies to all of the devices we build. They are not separate thinking systems from us, they are and always will be our appendages, like the nest to the bird or the web to the spider.

:up: yeah, I often compare computers to highly sofisticated mechanical calculators. At the end of the day all LLMs are very complex computers and they operate according to algorithms (programmed by us) just like mechanical calculators.

I don't think that many people would think that mechanical calculators or a windmill or mechanical clocks etc have 'awareness' or 'agency'. And computers just like them perform operations without being agents.

In order to have consciousness, computers IMO would have to be aware of what they are doing. There is no evidence that have such of an awareness. All their activities can be explained by saying that they just do what they are programmed for.

I will say bluntly that no machine we invent will do what we do, which is to think. — Joshs

I don't see the grounds for such a statement. A brain is just a certain kind of machine, and it thinks. If brains exist, then in principle you can build one. LLMs don't have a lot of things humans have, but doesn't mean that in principle you could build machines that do.

and they operate according to algorithms (programmed by us) just like mechanical calculators. — boundless

And you don't think we do? Our brains are bundles of neurons which all work in very similar ways. You could easily make an argument that we operate in accordance with some very basic kind or family of algorithms recapitulated in many different ways across the brain.

All their activities can be explained by saying that they just do what they are programmed for. — boundless

As can a human brain.

The hard problem is Q2 and it is legitimate for science to want to know how a neural net can have experiences. — Mijin

I can accept that.'

OK. So what is 'physical' in your view? IIRC you also agree that physical properties are relational, i.e. they describe how a given physical object relate to/interact with other physical objects. — boundless

It means that all energy and particles and whatnot obey physical law, which yes, pretty much describes relations. That's circular, and thus poor. It asserts that this description is closed, not interfered with by entities not considered physical. That's also a weak statement since if it was ever shown that matter had mental properties, those properties would become natural properties, and thus part of physicalism.
So I guess 'things interact according to the standard model' is about as close as I can get. This whole first/third person thing seems a classical problem, not requiring anything fancy like quantum or relativity theory, even if say chemistry would never work without the underlying mechanisms. A classical simulation of a neural network (with chemistry) would be enough. No need to simulate down to the molecular or even quantum precision.

'Scientistic physicalism' is also inconsistent IMO because, after all, that there is a physical world is not something we discover by doing science.

That's a philosophical stance, I agree.

Other than 'consciousness' I also believe in the existence of other things that are 'real' but not 'physical'. I am thinking, for instance, of mathematical truths.

OK. Not being a realist, I would query what you might mean by that. I suspect (proof would be nice) that mathematical truths are objectively true, and the structure that includes our universe supervenes on those truths. It being true implying that it's real depends on one's definition of 'real', and I find it easier not to worry about that arbitrary designation.

But it does sometimes clarify at least a meaning that 'physical' can have. For instance, if by matter one means "whatever object exists in a given location of space in a given time", would you agree that this is also what you mean by 'physical'?

Is space and time not physical then? Neither meets your criteria of 'object', but I think I would include them under 'physicalism'. Not all universes have them, and those might have very different definitions of what is physical or material.

Has consciousness a 'definite location' in space, for instance? — boundless

Me considering that to be a process of material that has a location, it seems reasonably contained thus, yes. Not a point mind you, but similarly a rock occupies a region of space and time.

IMHO you're thinking in rigid categories. Either one is a 'physicalist/naturalist' or one accepts 'magic'.

Right.' Science cannot make progress with an attitude like that. Most magic is replaced by natural explanations, but occasionally 'magic' explanations are adopted as part of naturalism. I gave a couple examples of that.
By magic, I mean an explanation that just says something unknown accounts for the observation, never an actual theory about how this alternate explanation might work. To my knowledge, there is no theory anywhere of matter having mental properties, and how it interacts with physical matter in any way. The lack of that is what puts it in the magic category.

Maybe there is something that is not 'natural'. Again, mathematical truths seem to me exactly an example of something that is not natural and yet real.

That seems to be like saying atoms are not real because they're not made of rocks.

One would stretch too much the meaning of 'natural/physical' to also include mathematical truths in it. — boundless

I agree, since those truths hold hopefully in any universe, but our natural laws only work in this one (and similar ones).

why you think that consciousness is 'physical'?

I've seen no evidence from anybody that physical interactions cannot account for it. Sure, it's complex and we don't know how it works. But that it cannot work? That's never been demonstrated.

At the end of the day all LLMs are very complex computers and they operate according to algorithms (programmed by us) just like mechanical calculators. — boundless

I can argue that people also are this, programmed by ancestors and the natural selection that chose them. The best thinking machines use similar mechanisms to find their own best algorithms, not any algorithm the programmer put there. LLM is indeed not an example of this.

I can see how electrons moving from atom to atom is electricity.
I can see how the movement of air molecules is heat and pressure.
I can see how the movement of an object is force: F=ma.
I can see how a fluid, whether liquid or gas, flowing around an object creates lift, which is a factor in flight.

All of those examples are physical activities
I don't see how self-awareness is a physical activity — Patterner

You understand the former because those are quite trivial interactions. Then you jump to something with complexity beyond the current state of science. But not understanding how something works is not any sort of evidence that it isn't still a physical process.

The game playing machine beats everybody at Go. Nobody, not even its creators, know how it works. It wasn't taught any strategy, only the rules. It essentially uses unnatural selection to evolve an algorithm that beats all opponents. That evolved (hard deterministic) algorithm is what nobody understands, even if they look at the entire data map. But nobody concludes that it suddenly gets access to magic. Such a conclusion comes with an obvious falsification test.

Descartes asks "What can I know with certainty?" while Husserl asks "How does anything come to be given to consciousness at all?"​​​​​​​​​​​​​​​​ — Joshs

Not only am I not certain about what Descartes knows with certainty, but I actually find the conclusion unlikely. Of course I have access to science that he doesn't.
As for 'come to be given to ...", that seems the conclusion is already drawn, and he's trying to rationalize how that might work.

from something which is Turing complete: i.e. they can compute anything in principle. — Apustimelogist

Something Turing complete can compute anything a Turing machine can, which is a lot, but not anything. Technically nothing is Turing complete since a Turing machine has infinite data on which to operate.
Such machines are a model of capability, but not in any way a model of efficiency. Nobody makes one to get any actual work done, but it's wicked interesting to make one utilizing nonstandard components like train tracks.

As Stephen Wolfram notes: “The most powerful AI might not be programmed; it might be cultivated, like a garden of interacting dynamical systems.”​​​​​​​​​​​​​​​​ — Joshs

I like that quote.

Obviously, to artificially recreate a human brain to acceptable approximation, you need to construct this computational system with the kinds of inputs, kinds of architectures, capabilities, whatever, that a human does. — Apustimelogist

Were I to simulate a human, I'd probably not give it inputs at all. Almost all simulations I've run do it stand-alone with no input at all. Logged output for later analysis, but that doesn't affect the simulation. Of course this means your simulated person needs to be in a small environment, also simulated.

I will say bluntly that no machine we invent will do what we do, which is to think.​​​​​​​​​​​​​​​​ — Joshs

Noted. How very well justified. Your quote is about LLMs which are mildly pimped out search engines. Compare that do devices which actually appear to think and to innovate. What do you call it if you refuse to apply the term 'think' to what it's doing?

The quote goes on to label the devices as tools. True now, but not true for long. I am arguably a tool since I spent years as a tool to make money for my employer. Am I just a model then?

Postmodern philosophy has become like Big Pharma, in that the latter creates ailments to sustain medicinal inventions while the former creates scenarios bordering on superfluous overreach — Mww

Nice analogy. It explains Chalmers' motivation for creating a problem where there really isn't one.

And you don't think we do? Our brains are bundles of neurons which all work in very similar ways. You could easily make an argument that we operate in accordance with some very basic kind or family of algorithms recapitulated in many different ways across the brain. — Apustimelogist

No, I don't and you don't here provided sufficient evidence to convince me of your view. Rather, it seems to me that, given the impressive results we have obtained with computers you are concluding that our congition is also algorithmic.

I believe that there is a difference between conscious - and in general living - beings and algorithmic devices. All living beings seem to have a 'sense' of unity, that there is a distinction between 'self' and 'not self' and so on. They do not just 'do' things.

Regardless, I don't think there is any consensus on this topic among scientists. So, after all in a way both our positions are speculative.

As can a human brain. — Apustimelogist

Says you. To me there is a clear difference between how human cognition works and how, say, a mechanical calculator works. And I am open to the idea that, perhaps, our cognition can't even be wholly comprehended by mathematical models, let alone only algorithms.

t means that all energy and particles and whatnot obey physical law, which yes, pretty much describes relations. That's circular, and thus poor. It asserts that this description is closed, not interfered with by entities not considered physical. That's also a weak statement since if it was ever shown that matter had mental properties, those properties would become natural properties, and thus part of physicalism.So I guess 'things interact according to the standard model' is about as close as I can get. This whole first/third person thing seems a classical problem, not requiring anything fancy like quantum or relativity theory, even if say chemistry would never work without the underlying mechanisms. A classical simulation of a neural network (with chemistry) would be enough. No need to simulate down to the molecular or even quantum precision. — noAxioms

Ok for the definition! Yes, and GR seems to imply that both spacetime and 'what is inside of it' are 'physical/natural'. i disagree with your view that mathematical truths are 'natural', though. They seem to be independent of space and time. That our minds are not 'natural' (in this broad sense) is perhaps more controversial. But the fact that we can know mathematical truths is quite interesting if we are 'wholly natural' (I do not know...). It seems to me that however it is better to reframe the 'hard problem' in a different way: can consciousness arise from what is completely inanimate?

The confidence you have in the power of algorithms seems to arise from anunderlying assumption that every natural process is 'algorithmic'. Of course, I am not denying the enormous success of algorithmic models and simulations but I am not sure that they can ever be able to give us a completely accurate model/simulation of all processes.

I admit that I can't give you a scientific argument against your assumption. But for me my phenomenological experience strongly suggests otherwise (self-awareness, the ability to choose and so on do not seem to be easily explainable in terms of algorithms).

OK. Not being a realist, I would query what you might mean by that. I suspect (proof would be nice) that mathematical truths are objectively true, and the structure that includes our universe supervenes on those truths. It being true implying that it's real depends on one's definition of 'real', and I find it easier not to worry about that arbitrary designation. — noAxioms

I lean towards a form of platonism where mathematical truths are concepts and yet are timeless and indipendent of space. it seems the only position that makes sense considering the following: the fact that we know them as concepts, the incredible success that mathematical laws have in describing the behaviour of physical processes, the apparently evident 'eternity' of mathematical truths (that there are infinite prime numbers seems to me indipendent from any human discovery of such a fact for instance) and so on.

Of course, I am under no illusion that I can give an absolutely convincing argument of my view (as often happens in philosophy) but it seems to me the best view after weighing the aguments in favour and against it.

Me considering that to be a process of material that has a location, it seems reasonably contained thus, yes. Not a point mind you, but similarly a rock occupies a region of space and time. — noAxioms

Ok. In a general sense, yeah I perhaps can agree with you that mind is natural or even 'physical'. But it has quite peculiar attributes that it is difficult to explain as arising from 'inanimate' matter. And, as I said before, it seems to have the capacity to understand/know 'something' that is not 'natural'.

By magic, I mean an explanation that just says something unknown accounts for the observation, never an actual theory about how this alternate explanation might work. To my knowledge, there is no theory anywhere of matter having mental properties, and how it interacts with physical matter in any way. The lack of that is what puts it in the magic category. — noAxioms

Ok, I see. But consider that under this definition you risk to include inside 'magic' many partial or unclear explanations that I would not include into that word. In other words, your category of 'magic' seems excessively broad.

For instance, if we were talking in the 14th century and you claimed that 'atoms' exist and 'somehow' interact with forces that we do not know to form the visible objects, would be this 'magic' (of course, you have to imagine yourself as having the scientific knowledge of the time)?

I can argue that people also are this, programmed by ancestors and the natural selection that chose them. The best thinking machines use similar mechanisms to find their own best algorithms, not any algorithm the programmer put there. LLM is indeed not an example of this. — noAxioms

Am I wrong to say that, however, that the operations of these 'thinking machines' are completely explainable in terms of algorithms?
As I said in my previous post, I can't neglect the fact that my own self-awareness, the experience of self-agency and so on seem to point that we are not like that.

A fly evading a swat is another. — noAxioms

Is there something it's like to be a fly evading a swat? How do we know? How could we ever find out? Isn't the inability to answer those questions a "hard problem"?

No, I don't and you don't here provided sufficient evidence to convince me of your view. Rather, it seems to me that, given the impressive results we have obtained with computers you are concluding that our congition is also algorithmic. — boundless

How would you interpret the fact that our brain (or at least the component that seems involved in processing information and long distance message-passing) is almost entirely composed of the same kind of cell with the same fundamental underlying physiological and anatomical structures and mechanism in terms of membrane potentials that induce action potentials.

We don't have a deep understanding in which we can build detailed realistic functioning models of exactly what human brains are doing and why but we have a reasonably good basis for understanding the kind of information processing principles that underlie what neurons do such as in terms of efficient, sparse, predictive coding using recurrent connectivity. And really, LLM architectures work under very similar basic principles to what neurons do which is just prediction. You can fidn studies that the same kind of models used for LLMs are actually really very good at predicting neural responses to things like language processing because fundamentally they are doing the same thing, prediction.

All living beings seem to have a 'sense' of unity, that there is a distinction between 'self' and 'not self' and so on. They do not just 'do' things. — boundless

There is no reason to think that these things can't be achieved with the same fundamental processes that transformers already use... why? Because they work in the same way brains do. The difference is that all LLMs are trained to do is predict words. Human brains don't just predict but act and control themselves; not just that, but these things are clearly biased, in terms of the evolutionarily-conserved structure of the brain itself, for very biologically specific control (i.e. what you would call homeostatic and allostatic). But the point is that there is no reason to think these things cannot be performed by the same processes that fundamentally underlie what transformers and LLMs do if you just structure them or design them in a way that allows them to do that. It would be surprising if they didn't imo because that seems to be what brains do. Neurons share the same core fundamental physiological, anatomical, functional properties, and there is the same kinds of interplay between excitation and inhibition, that are used for everything from homeostatic regulatory responses from the hypothalamus and midbrain to visual processing, motor control, language, executive functions, emotion, etc. There is of course a great variety in neurons and structures across the brain but they all share fundamental commonalities with some shared core which is virtually ubiquitious.

The primary disconnect seems to be that no third-person description can convey knowledge of a first-person experience — noAxioms

Without reading the full post, this misses the problem.

The problem is, no third person explanation can arrive at first person experience. There is an 'explanatory gap'. Not only do we not know the specific series of explanations that start at neural facts and ends at first person experience, conceptually, it doesn't seem possible that any such series can exist.

But not understanding how something works is not any sort of evidence that it isn't still a physical process. — noAxioms

Maybe so. But not understanding how it works is certainly not any sort of evidence that it is a physical process.


I'm wondering if you can tell me how this works. Or tell me what's wrong with my understanding.

This is what Google AI says about the release of neurotransmitters:

1. Arrival of Action Potential:
The action potential travels down the axon of the presynaptic neuron and reaches the axon terminal.

2. Calcium Influx:
The arrival of the action potential opens voltage-gated calcium channels at the axon terminal.
Calcium ions (Ca2+) flow into the neuron.

3. Fusion of Synaptic Vesicles:
Ca2+ binds to proteins on the synaptic vesicles, which are small membrane-bound structures containing neurotransmitters.
This binding triggers the fusion of the synaptic vesicles with the presynaptic membrane.

4. Neurotransmitter Release:
As the vesicles fuse, the neurotransmitters are released into the synaptic cleft, the space between the presynaptic and postsynaptic neurons.

5. Diffusion and Binding:
The released neurotransmitters diffuse across the synaptic cleft and bind to receptors on the postsynaptic neuron.

6. Termination of Neurotransmitter Action:
Neurotransmitters are eventually removed from the synaptic cleft by reuptake into the presynaptic neuron, enzymatic breakdown, or diffusion away from the receptors.

Here's what it says about the first step - Action Potential:

Resting Membrane Potential: In a resting neuron, the inside of the cell is more negative than the outside, establishing a resting membrane potential (around -70 mV).

Threshold: A stimulus, often in the form of chemical signals from other neurons (neurotransmitters), causes the membrane to depolarize (become less negative). If this depolarization reaches a critical "threshold" level (e.g., -55 mV), it triggers an action potential.

Depolarization: At threshold, voltage-gated sodium channels open rapidly, allowing a large influx of positively charged sodium ions into the cell. This makes the inside of the neuron rapidly more positive.

Repolarization: Sodium channels then inactivate, and voltage-gated potassium channels open, allowing positively charged potassium ions to flow out of the cell. This efflux of potassium ions causes the membrane potential to become more negative again, moving it back towards the resting potential.

Hyperpolarization: The potassium channels may remain open a bit longer than needed, causing the membrane potential to dip below the resting potential before they close.

Return to Rest: Finally, ion pumps (like the sodium-potassium pump) restore the resting membrane potential, preparing the neuron for another action potential.

You say all of this, along with whatever other processes are taking place, is a description of not only things like receiving sensory input and distinguishing wavelengths of the electromagnetic spectrum, and receptors on my tongue distinguishing molecules that have made contact, but also seeing the color red, and tasting the sweetness of sugar. More than that, it's a description of my thoughts.

My thoughts is what I'm really wondering about at the moment. That kind of activity is why I'm thinking of the number 7. And, over the next several seconds, due to the laws of physics working on what was there, the arrangements of all the particles of my brain change from X to Y to X. And those arrangements just happen to mean "+ 18 = 25".

The same could be said for any thoughts I ever have, mathematical or otherwise.

Of course, it's not simply one chain of neurons involved in a thought. I wouldn't care to guess how many are involved in any given thought. Or how many are involved multiple times in a single thought. There's probably all kinds of back tracking and looping.

How does all that work??? In particular:

-How do progressions of arrangements of all the particles in my brain mean all the things they mean?

-How do all the action potentials and releasings of neurotransmitters coordinate throughout the brain, or an area of the brain, so that X , Y, and a million others happen at the same time in order to bring about the needed thought? (I could understand if one specific neuron initiated it all, so that the timing would be assured. But that would mean the single neuron already had the thought, and initiated all the activity to, shall we say, actualize(?) the thought. But that whole idea is a bit silly.)

You say all of this, along with whatever other processes are taking place, is a description of not only things like receiving sensory input and distinguishing wavelengths of the electromagnetic spectrum, and receptors on my tongue distinguishing molecules that have made contact, but also seeing the color red, and tasting the sweetness of sugar. More than that, it's a description of my thoughts. — Patterner

You can initiate a fight or flight response by deciding to think of something scary. Maybe that would be an argument that a description of how neurons communicate isn't a description of thought.

You can also get a dose of adrenaline by making yourself hyperventilate. Don't do it in the middle of the night though, because you won't be able to sleep afterwards.

I will say bluntly that no machine we invent will do what we do, which is to think.​​​​​​​​​​​​​​​​
— Joshs
Noted. How very well justified. Your quote is about LLMs which are mildly pimped out search engines. Compare that do devices which actually appear to think and to innovate. What do you call it if you refuse to apply the term 'think' to what it's doing?

The quote goes on to label the devices as tools. True now, but not true for long. I am arguably a tool since I spent years as a tool to make money for my employer. Am I just a model then? — noAxioms

When we build a machine it has a time stamp on it. No matter how apparently flexible its behavior , that flexibility will always be framed and limited to the model of thinking that dates to the time that the product is released to the market. As soon as it is released, it already is on the way to obsolescence, because the humans who designed it are changing the overarching frame of their thinking in subtle ways every moment of life. 20 years from now this same device which was originally praised for its remarkable ability to learn and change “just like us” will be considered just as much a relic as a typewriter or vcr. But the engineers who invented it will have continued to modify their ways of thinking such as to produce a continuous series of new generations of machines, each of which will be praised for their remarkable ability to ‘think and innovate’, just like us. This is the difference between a human appendage ( our machines) and a human cognizer.

You might argue that biological evolution designs us, so that we also have a time stamp on us framing and limiting our ability to innovate. But I disagree. Human thought isn’t bound by a frame. It emerged through evolutionary processes but has no limits to the directions in which thinking can reinvent itself. This is because it isn’t just a product of those processes, but carries forward those processes.Evolution isn’t designed, it is self-designing. And as the carrying forward of evolution, human culture is also self-designing. Machines don’t carry forward the basis of their design. They are nothing but their design, and have to wait for their engineers to upgrade them. Can we teach them to upgrade and modify themselves? Sure, based on contingent, human-generated concepts of upgrading and modification that have a time stamp on them.

The problem is, no third person explanation can arrive at first person experience. — hypericin

I guess I didn't see much difference between a description and an explanation. My point was that no anything will arrive at the 'experience' part of it.
Chalmers' explanation certainly doesn't arrive at first person experience. "A sauce is needed" is no more an explanation than it not being needed.

And I disagree. First person (the PoV part, not the human qualia associated with 'experience') is trivial. The experience part (qualia and such) is 'what it is like', and that part cannot be known about something else, especially even when it's not even complex. The first person part seems trivial, and entire articles are nevertheless written suggesting otherwise, but seemingly without identifying exactly what's problematic about it.

The title of this topic is about the first/third person divide, which Chalmers asserts to be fundamental to said 'hard problem', but it isn't. The qualia is what's hard. I can't know what it's like to be a bat, but even a rock has a first person PoV, even if it utterly lacks the ability to actually view anything.

The confidence you have in the power of algorithms seems to arise from anunderlying assumption that every natural process is 'algorithmic'. — boundless

Not sure what you mean by that, but I can perhaps say that every natural process can in principle be simulated via an algorithmic device that has sufficient time and memory. (Speed/power is not one of the requirements). This assumes a form of physicalism, yes, and the statement would likely be false if that was not assumed.

I am not sure that they can ever be able to give us a completely accurate model/simulation of all processes.

I don't think a classical simulation can be done of something not classical, such as a quantum computer. Heck, even grass has been shown to be utilizing quantum computation, so what does that do to my claim that grass can be simulated?

But for me my ... ability to choose ... [does] not seem to be easily explainable in terms of algorithms — boundless

You must have an incredibly different notion of 'choice' when there's some many trivial devices that make them every second. It's not hard at all.
But his seems illustrative of my point. You finding something as trivial as choice to be physically inexplicable is likely due to very related reasons why you might find something as trivial as a first person point of view similarly inexplicable. You're already presuming something other than physicalism under which these things are trivial.

For instance, if we were talking in the 14th century and you claimed that 'atoms' exist and 'somehow' interact with forces that we do not know to form the visible objects, would be this 'magic' (of course, you have to imagine yourself as having the scientific knowledge of the time)?

Yes, that would qualify as magic. It's a guess, and a lucky one. Elements as distinct from compounds was still hundreds of years away, so 'atom' meant just 'tiny indivisible bit' and there were no known examples of one, even if some substances known at the time happened to be pure elements. BTW, 'atom' no longer implies 'tiny indivisible bit'. The word unfortunately stuck to a quanta of a specific element and not to whatever is currently considered to be an indivisible component of matter.

Am I wrong to say that, however, that the operations of these 'thinking machines' are completely explainable in terms of algorithms? — boundless

Probably not so. The algorithms developed by say alphaZero have defied explanation. Nobody knows how they work. That isn't an assertion that the operations are not the result of deterministic processes. All the same things can be said of humans.

Is there something it's like to be a fly evading a swat? How do we know? How could we ever find out? Isn't the inability to answer those questions a "hard problem"? — RogueAI

From observation, the answer to that question is yes or no depending on if it supports my personal conclusions on the matter. Hence assertions of there perhaps being something it is like to be the fly, but not something it is like to be an autonymous drone doing somewhat the same things and more.

This is what Google AI says about the release of neurotransmitters: — Patterner

Cool level of detail. I notice no influence from say chemicals in the blood stream. It sounds all very like logic gates. A similar breakdown of transistor operation could be made, which are sometimes more binary and less analog, but still either could be implemented via the components of the other. The chemical influences would be harder to mimic with transistors and would likely play a role only at higher levels.

I also notice nowhere in those 6 steps any kind of mental properties of matter playing any sort of role that they somehow are forbidden from doing in transistors. Were that the case, then my claim of either being capable of being implemented by the components of the other would be false. This lack of external mental influence (or at least the lack of a theory suggesting such) is strong evidence for the physicalist stance.

You say all of this, along with whatever other processes are taking place, is a description of not only things like receiving sensory input and distinguishing wavelengths of the electromagnetic spectrum, and receptors on my tongue distinguishing molecules that have made contact, but also seeing the color red, and tasting the sweetness of sugar. More than that, it's a description of my thoughts.

No, I cannot describe thoughts in terms of neurons any more than I can describe a network file server in terms of electrons tunneling through the base potential of transistors. It's about 12 levels of detail removed from where it should be. Your incredulity is showing.

No matter how apparently flexible its behavior , that flexibility will always be framed and and limited to the model of thinking that dates to the time that the product is released to the market. — Joshs

No so for devices that find their own models of thinking.

As soon as it is released, it already is on the way to obsolescence

So similar to almost every creature. Name a multicelled creature they have a fossil of that exists today. I can't think of one. They're all obsolete. A rare fossil might have some living descendants today (I can think of no examples), but the descendant is a newer model, not the same species.

The singularity is defined as the point at which human engineers play little role in the evolution of machine thinking. Humans will also cease being necessary in their manufacturing process, and I suspect the trend of humans handing more and more of their tasks to machines will continue to the point that the singularity will be welcomed.

It will be interesting to see what role evolution plays in that context, where changes are deliberate, but selection is still natural. Also, it may not necessarily be many machines in competition for resources instead of meany ideas competing for being 'the machine'.

No, I cannot describe thoughts in terms of neurons any more than I can describe a network file server in terms of electrons tunneling through the base potential of transistors. It's about 12 levels of detail removed from where it should be. — noAxioms

Ok, wrong word. You agreed they are the same thing. But they can't be described as the same thing.

Your incredulity is showing. — noAxioms

I am trying to understand your position. Can you give me any detail, or direction? My incredulity is a given. But if you're right, I'd like to understand.

No matter how apparently flexible its behavior , that flexibility will always be framed and and limited to the model of thinking that dates to the time that the product is released to the market.
— Joshs
No so for devices that find their own models of thinking.

As soon as it is released, it already is on the way to obsolescence
So similar to almost every creature. Name a multicelled creature they have a fossil of that exists today. I can't think of one. They're all obsolete. A rare fossil might have some living descendants today (I can think of no examples), but the descendant is a newer model, not the same species. — noAxioms

You’re missing the point. Even taking into account all of the biological lineages which become extinct, what it means to be a living system is to be self-organizing, and this self-organization is dynamic. This means that to continue existing as that creature from moment to moment is to make changes in itself that maintain the normative self-consistency of its functioning in its environment while at the same time adapting and accommodating itself to the always new features of its environment. This is as true of dinosaurs and do-do birds as it is of us.

While organisms without linguistic culture rely on inherited ‘design’ to frame their possibilities of adaptation to the world, this isnt just a one-way street. The organism’s own novel capabilities shape and modify the underlying genetic design, so behavior affects and modifies future genetic design just as genetic design frames behavior. This is what makes all living systems self-designing in a way that our machines can never be. A designer can’t ‘teach’ its product to be self-designing because all the tools the machine will have at its disposal will have been preset in advance by the designer. There is no reciprocal back and forth between machine and designer when the designer chooses a a plan for the machine.

In that the the engineers have the opportunity to observe how their machine operates out in the world, there is then a reciprocity between machine behavior and desiger. But this is true of our artistic and philosophical creations well. We create them , they ‘talk back to us’ and then we modify our thinking as a result.

I really don't understand what you are going on about. A brain is a physical object. In principal, you can build a brain that does all the things brains do from scratch if you had the technological capabilities.

In principal, you can build a brain that does all the things brains do from scratch if you had the technological capabilities. — Apustimelogist

"One could do the impossible, if only it were possible" becomes a bit less profound when said aloud more than once.

There is absolutely nothing of any substance in Josh's post that refutes the idea that one could build a self-organizing machine.

The title of this topic is about the first/third person divide, which Chalmers asserts to be fundamental to said 'hard problem', but it isn't. The qualia is what's hard. — noAxioms

This feels like a strange misunderstanding. Qualia are intrinsically first person. When people talk about first person experience being mysterious, they are talking about qualia, not mere geometric POV.

This especially raises my eyebrows, because I remember a time you thought you were a p zombie!

↪Joshs

I really don't understand what you are going on about. A brain is a physical object. In principal, you can build a brain that does all the things brains do from scratch if you had the technological capabilities — Apustimelogist

And can we also create life from scratch if we had all the technological capabilities? What I am going on about are the important differences between the cognizing of a living organism and the thinking of a human-designed machine.

And can we also create life from scratch if we had all the technological capabilities? What I am going on about are the important differences between the cognizing of a living organism and the thinking of a human-designed machine. — Joshs

It seems to me you are going on about differences between living organisms and our current machines. But there is no refutation here that in principle one can build machines which are as complex as living organisms. You haven't set out any reason why those differences wouldn't be breachable. You just say that living organisms are like this and machines we have built are like that. You don't seem to think that in principle we can understand the principles of self-organization and use that to build self-organizing machines when people have been doing that for decades. The learning that A.I. does isn't even all that different to self-organization in the sense that in modern A.I. we don't hardcode the capabilities and things these systems are actually doing; usually people don't even really know how the A.I. they have designed does what it does on a mechanical level. What is being hardcoded, effectively, is the ability for a system to learn to do things by itself without explicit supervision, which is self-organization.

What is being hardcoded, effectively, is the ability for a system to learn to do things by itself without explicit supervision, which is self-organization. — Apustimelogist

What does hardcoded mean? What are the technological concepts involved? It is not difficult to answer this question for any given a.i.architectural blueprint. One can put together a list of such grounding concepts. At the top of this list should be concepts like ‘hard’, ‘code’ and what these do together in the form ‘hardcode’, but it also includes our current understanding of concepts like memory, speed, symbol, computation, and many others. If I were to suggest that today’s computer architectures and their grounding concepts are based on older philosophical ideas that have been surpassed, would you respond that this simply proves your point that just because today’s technological know-how is inadequate to model human thinking, this doesn’t mean that tomorrow’s technological understanding can’t do the job?

If I am claiming that there is a more adequate way of understanding how humans think, what stands in the way of our applying this more adequate approach to the development of products which think like us? My answer is that nothing stands in the way of it. I would just add that such an approach would recognize that the very concept of a device humans design and build from the ground up belongs to the old way of thinking about what thinking is.

So if I’m not talking about a machine that we invent, what am I talking about? What alternatives are there? Writers like Kurzweil treat human and machine intelligence in an ahistorical manner, as if the current notions of knowledge , cognition, intelligence and memory were cast in stone rather than socially constructed concepts that will make way for new ways of thinking about what intelligence means. In other words, they treat the archival snapshot of technological cultural knowledge that current AI represents as if it were the creative evolution of intelligence that only human ecological semio-linguistic development is capable of. Only when we engineer already living systems will we be dealing with intelligent, that is, non-archival entities, beings that dynamically create and move through frames of cognition.

When we create dna-based computers in a test tube and embed them within an organic ecological system, or when we breed, domesticate and genetically engineer animals, we are adding human invention on top of what is already an autonomous, intelligent life-based ecological system , or ecological subsystem. The modifications we make to such systems will allow us to communicate with them and shape their behavior, but what will constitute true thinking in those living systems is not what we attempt to ‘lock in’ through ‘hardcoding’ but what feeds back into, surpasses and transforms that hardcoding through no planned action of our own. The difference here with devices that we design from the ground up is that the latter can never truly surprise us. Their seeming creativity will always express variations on a theme that we ‘hardcode’ into it, even when we try to hardcode creative surprise and innovation.

When we achieve that transition from inventing machines to modifying living systems, that organic wetware will never surpass us for the same reason that the animals we interact with will never surpass us in spite of the fact that they are subtly changing their ‘hardcoded’ nature all the time. As our own intelligence evolves, we understand other animals in more and more complex ways. In a similar way, the intelligence of our engineered wetware will evolve in parallel with ours.

What does hardcoded mean? — Joshs

Pre-programmed, in contrast to self-organization. Its not some technical concept. For instance, you could say pain or hunger is in some sense hard-coded into us.

You have then seemed to base the rest of the post on latching onto thia use of the word "hardcoded" even though I initially brought that word up in the post to say that "hardcode" is exactly not what characterizes self-organization or what A.I. do.

Pre-programmed, in contrast to self-organization. Its not some technical concept. For instance, you could say pain or hunger is in some sense hard-coded into us — Apustimelogist

Whether technical or non-technical, it is a concept, and all concepts belong to cultural understandings, which are contingent and historically changing And the machines we invent are stuck with whatever grounding concept we use to build their remarkable powers to innovate. Given that the thinking of our best engineers doesn’t even represent the leading edge of thinking of our era, it’s kind of hard to imagine how their slightly moldy concepts instantiated in a self-learning a.i., will lead to the singularity.

You have then seemed to base the rest of the post on latching onto this use of the word "hardcoded" even though I initially brought that word up in the post to say that "hardcode" is exactly not what characterizes self-organization or what A.I. — Apustimelogist

The fact that the architectures of our most self-organizing machines depend on locking in certain grounding concepts to define the parameters and properties of self-organization ( properties which will change along with the concepts in a few years as the engineers come up with better machines) means that these concepts are in fact forms of hardcoding.