Its a two pronged problem. First there are just too many elements with a lot of complex dynamics at the molecular level. Our hardware is just not good at that type of task, especially when you scale it to trillions of cells, and then the environment around them at the molecular level because that is a huge factor as well.

The second problem is that we also do not even know all of the dynamics, so we don't exactly have all the data necessary for running the simulation in the first place. We don't have a full account of all the metabolic and signal transduction pathways and various other processes, and how they intersect each other. We can't exactly get a real-time view into a living organisms cells at molecular resolution.

I really don’t understand how you guys are getting mysticism out of this. Probably because I used the word experience but I’m talking about the physical cellular activity here. Some of you just arent grasping the true scope of the hardware mismatch Im trying to describe here

>I think you're overselling the computational complexity of things like immune cells. They're not exactly navigating the body on a self determined path to find pathogens. There is no 'thinking' involved beyond reacting to a stimulus.

I never said they were thinking. This is why people get so hung up on the brain as a necessity for complex action and "behavior." Come take a walk with me. I'm going to describe Chemotaxis for you.

Chemotaxis is an important part of the movement of bacterial cells. Its how they swim toward food and away from danger/noxious components. In the long pill shape form of E.coli, usually at one tip there will be some transmembrane proteins. These proteins are receptors. Small molecules bind to these receptors, with things like amino acids and sugars being food and nickel ions and acids being noxious. About 4 kinds of receptor will be surveying the surroundings. When the right molecule binds to the receptor, it triggers a signal transduction cascade. Upon binding to the receptor, the chain reaction leads to a protein binding to another that is connected to the flagella. The binding turns it like a rotor, moving the flagella and the bacteria will tumble in one direction or another.

No thinking involved. But see how it didn't really need computation or anything either? It was purely a mechanical process at the molecular level. Molecule binds, chain link chemical reactions, different protein binds to another to become a spinning motor. Our immune cells are very much doing something similar, only more of it. It has the option of more receptor types, more space for those receptors, and more internal space and material for very many chain link reactions. Natural selection iterated and created enough of the "wiring" needed for an immune cell to carry out its wet work or support duties.

When you examine pathways like this with more types of cells, and think about all that is going on in the body when you scale this up, it is easier to imagine that it is entirely possible for us to operate without any abstract computation going on. You might say "thats so simple and limited, and that would make us no more than automatons," but you would be wrong. Because of the scale. There are trillions of cells in our bodies with a large enough genome to create an absurd variety of protein complexes. The "computing" power of this is IMMENSE. And its chemical soup, so its all a gigantic, fuzzy impossibly huge finite state machine diagram. There isn't any determinism to worry about because it's too many molecules, the combinatorial explosion is too intense.

Sequences of direct action and reaction that change "behavior" based on the current conditions of cell and its surrounding environment.

THIS is why I say there are no models in the brain. Based on what? Theres no need.

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>Your brain absolutely creates models or algorithms (or whatever you would like to call them). When you learn to ride a bicycle, for example, your brain creates a model of what you need to do to produce the desired result of riding a bicycle without crashing

Prove it. Where in the brain are the models stored. How are they accessed and updated. What is the biochemistry that is creating them. This is a well disputed concept in the field. Don't need models of bikes and desired results, just more chemotaxis if you think about it for a while.

We can waste time trying to decipher encoding schemes which might not even exist, or we can map the actual activity going on.

Coming together is how eukaryotes exist in the first place. One bacterium ingested another, and the ingested became the mitochondria. Merging in a symbiotic way expanded the capacity of a single cell. Incredible stuff.

Seeing them IS the visceral experience I'm talking about. We can even touch them and poke and prod them with things and see what they do. We feed them and grow them. You brush their waste products off your teeth and spew their gases out of either end of your GI tract. All of this interaction, including the abstract thoughts of it (because thinking itself is cellular activity, neurons are signaling each other to trigger broader associations formed from the total chain of cellular activity those thoughts engaged), together form the "visceral experience."

When I say visceral I don't human gut, I mean the inside of the cells themselves. Nothing is purely abstract, there is molecular activity going on for every single thing. It is the dynamics of that activity that determine the intelligence, because those dynamics are what "ground" everything. How would you approach the symbol grounding problem, because every time we note these systems failing to reason properly, it comes back to that issue.

None of these systems are superhuman, you should read the actual papers that put out those claims and you will see its a stretch. "Superhuman performance" is on specific BENCHMARKS only. For instance, none of the medical systems got anywhere (remember Watson?) and the self driving cars are proving to be way harder than we thought. They might as well be trains with all the stuff they have to do to get them work in actual dynamic driving situations. Games are not a good benchmark, because we created machine readable representations of the state space, the rules for transitions between states, and they have a formal structure that can be broken down into algorithmic steps. They don't play the games like we do, we have to carefully engineer the game into a form the machine can act on.

LLMs passing tests? Actually look at what "passing" means.

And please try to give me an abstract concept you think doesn't have any experiences tied to your understanding of it. I bet I can link many of the different experiences you use to create an analogy in order to understand it.

I should have used "not sure if ever" because everyone keeps getting caught up on that. I was being provocative.

I too thought we were in a new era. But then I learned the mechanics of how this tech works and its limitations. Then I compared with the thing we are trying to emulate/simulate see even more limitations. I base my conjecture of "never" on the severe hardware limitations I can see.

I use the word "never" because I know that if we were to overcome those limitations, it would be with machinery that looks and operates nothing like anything we have now (von neumann, finite instruction set architecture. The stored program computer essentially), so much so that all of the hangups we currently have with things like job loss and runaway superintelligence, do not apply.

We have made many gains, sure. But I try to point out that the symbol grounding problem persists, we just hid all the human involvement. None of you believes that Expert Systems will lead to an AGI, but "neural networks" are given a lot of leeway because of that illusion.

People made progress with Alchemy too.

Not a troll. I was a part of this project for four years:

Full Adult Fly Brain

I know that consciousness and intelligence are separate things I never claimed such. I'm just here to pick brains and discuss the computability of the brain. I don't argue these things to call anyone dumb, just curious to see what they say if presented with these ideas.

Those claims of super human capabilities in single domains are misleading. The machines performed well on the benchmarks, not necessarily in any real world scenarios. Give them some out of distribution data, not in their training datasets, and they crumble.

I use LLMs as an example, because they operate with the same fundamental architecture as all the others and its the "hot thing" right now. Progress in these areas doesn't necessarily mean overall progress in the goal of AGI and I just urge people to exercise caution and think critically about all the reporting.

EDIT: I posted that research project, because I worked extensively with neural networks to automate the process of building that connectome. I'm familiar with the hurdles that go into training a machine to see and trace the individual cells in those images and detect the points of synapse.

I use LLMs as an example, because I know that people are confusing using words with understanding the meaning of the words.

But we CAN see cells. We made microscopes to see them. And electron microscopes to see some of the machinery they are made of. And various other experiments with chemistry to indirectly determine what they are made of. And in the process, we expanded our corpus of experiences and new analogies that we can make with those experiences. Why do you think we have labs in school where we recreate these experiments? Giving students direct experience with the subject helps them LEARN better.

Metaphors ARE weak and sometimes non-explanatory when we don't have an analogous experience to draw from. This is the difficulty we face in science right now, the world of the very small and the very large is out of our reach and we have to make a lot of indirect assumptions that we back with other forms of evidence.

I don't think humans are special I think cells are special, and purely from a "what are these things actually DOING" standpoint.

Like have you SEEN ATP synthase? Look at the sophistication:

ATP Synthase in Action

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This is molecular machinery. It's frickin nanotechnology. This is power we haven't even begun to replicate. And I'm not saying we can't, I'm saying it is really really hard. Fill trillions of tiny sacs with machinery like this, all working together, and the challenge grows. And there is no computing happening here, just action. So the computers are already one step removed from the actual function, thus increasing the amount of compute required to simulate it much less the challenge of actually just straight up DOING it.

If the word doesn't compose into physical phenomena, it is still analogized to or in relation to physical phenomena we have experienced.

If not, expand please, because I'd love to see counterexamples. It would give me more to think about. I'm not here to win I WANT my argument deconstructed further so I know where to expand and continue researching, because of the things I missed or forgot to account for.

I don't think we are special. Far from it. This is purely a material hardware comparison. I posted a reply elsewhere in this thread that tries to address some of this a bit further if you want to take a look:

https://www.reddit.com/r/Futurology/comments/10s52md/comment/j71z12h/?utm_source=share&utm_medium=web2x&context=3

You all have to really have to go on a journey with me here. The mind FEELS computable but this is misleading.

Consider this: how much of your mind actually exists separate from the body. Im sure you have attempted a breakdown. You can start by removing control of your limbs. Still there. Then any sensation. Still there. Remove signals from your viscera like hunger. Mind is still there i guess. Now start removing everything from tour head and face. Sight sound taste. The rest of the sensations in your skin and any other motor control. Now you are a mind in a jar sensory depraved. You would say still in there though. But thats because you have a large corpus of experiences in your memory for thoughts to emerge from. Now try to imagine what you are if you NEVER had any of those experiences to draw from.

So to expand what i was getting at a bit further, when i say visceral experience i mean that all the coordinated activity going on in and around all the cells in your body IS the experience. You say processing doesn’t occur in the eye but that is the first place it does. The retina is multiple layers of neurons and is an extension of the brain, formed from the embryonic neural tissue. If you stretch it a bit further, at the molecular level, everything is an “extension” of the brain. If everything is then you can start to modularize the body in different ways. Now you can think of the brain as more the medium of coordination than the executive control. Your mind is the consensus of all the cells in your body.

The things I’ve been hypothesizing about in my studies of microbiology and neuroscience requires this bit of reconceptualizing these things, choosing a new frame of reference to see what you get.

You can think of neurons as both powerful individual organisms in their own right AND a neat trick: they can act in concert as if they were a single shared cytoplasm, but remain with separate membranes for speed and process isolation. Neurons need to quickly transmit signal and state from all parts of the body, so that, for instance, your feet are aware of whats going on with the hands and they can work together to acquire food to satisfy the stomach. This doesn’t work in a single shared cytoplasm with any speed and integrity at the scale of our bodies. Some microorganisms coordinate into shared cytoplasms, but our evolutionary line utilized differentiation to great affect.

Everyone makes the assumption that I’m saying humans are special. I’m really not. This applies to all life on this planet. CELLS are special, because the "computing power" is unmatched. Compare electronic relays vs vacuum tubes vs transistors. Can’t make a smartphone with vacuum tubes. Likewise, transistors are trounced by lipid membranes, carbohydrates, nucleic acids, and proteins among other things, in the same way. Computers shuffle voltage; we are “programmable” matter (as in, matter that can be shaped for purpose by automated processes, not that there are programs involved. Because there aren't). This is a pure substrate comparison, the degree of complexity makes all the difference, not just the presence of it. We are matter that decomposes and recomposes other matter. Computers are nowhere near that sophistication. Computers do not have the power to even simulate fractions of all that is going on in real time, because of rate limiting steps and combinatorial explosions that cause exponential time {O(n^2)} algorithmic complexity All you have to do is look up some of our attempts to see the engineering hurdles. Even if its logically possible from view of the abstract mathematical constructs, that doesn’t mean it can be implemented. Molecular activity at that scale is computationally intractable.

To go further, even if it is not computational intractable the problem still remains. How do you encode the things I've been talking about here. Really try to play this out in your mind. What even does just some pseudocode look like. Now look back at your pseudocode. How much heavy lifting is being done by the words. How many of these things can actually be implemented with a finite instruction set architecture. With Heisenberg’s uncertainty principle lurking about, how accurate are your models and algorithms of all this molecular machinery in action.

Synthetic biology would hardly be able to be called artificial intelligence by our concepts of the terms. We want a program we can run on computers that behave intelligently. Synthetic biology is just biology, a completely different paradigm as I’ve already laid out. You couldn’t program it to follow your command only exercise power over it. Slavery essentially. This is the reason i say never. The stored program computer is not up to the task, the stuff that makes up a brain which results in a mind is not programmable.

We and our eukaryotic brethren are intelligent, because we actually do the sophisticated things required by our definitions of intelligence. Its a hardware(wetware) problem, not a philosophically unreachable subject.

I know we haven’t experienced wavelengths. Thats the word we came up with to describe the material phenomenon known as light, and how to measure one aspect of that phenomenon that we directly experience.

Those words decompose to actual physical phenomena. We use those words as a shortcut description to invoke an analogous experience. Molecules aren't balls and sticks but its the easiest way we can conceptualize the reality we have uncovered beyond our senses, to make it in any way understandable.

Absolutely correct. We can decompose parts of our thinking and still do useful things and speed up the things that we do. I simply argue here that going further, to a programmed "intelligence" or mind fully as independently capable of ours, especially for accomplishing unstructured, unformalizable tasks in the unbounded environment of reality is a tall ask.

The practical, useful AI's, even if they continue to progress, are still ladders to the moon.

I'll just give a quick reply to this point about "genocide" here, and then post the rest of my thoughts that you spurred (thanks!) in a reply/chain of replies to your last post in order to expand upon and better frame the position that i'm coming from.

So you know what genocide is because you make analogies from your experiences. You have experienced death. You’ve seen it smelled it touched it thought about it and felt emotions about it especially in relation to your own survival. You have experienced many different ways to categorize things and other people so you understand the concept of groups of humans. You can compose from these experiences the concept of murder, and expand that to genocide. You haven’t experienced nothingness, but you have experienced what it is to have something, and then NOT have that something. Language provides shortcuts and quick abstractions for mental processing. You can quickly invoke many many experiences with a single word.

I’m saying that there are plenty of examples that even if something is turing complete, we cant do anything with it if it would take our machines 1000 yrs to compute

My skepticism mainly comes from there not seeming to be a way to programmatically solve the grounding problem. I dont see von neumann, instruction set architectures being sophisticated/powerful enough in comparison to the only example we have.

I didnt say we’ll never understand it, just that its way more complicated than we give credit for.

And aside from the point I argue that the brain isn’t computing, just because something is Turing complete doesnt mean we can build a machine to compute it. The Turing machine is a construct with infinite time and memory. We have neither.