We are constantly fed a version of AI that looks, sounds and acts suspiciously like us. It speaks in polished sentences, mimics emotions, expresses curiosity, claims to feel compassion, even dabbles in what it calls creativity.
But what we call AI today is nothing more than a statistical machine: a digital parrot regurgitating patterns mined from oceans of human data (the situation hasn’t changed much since it was discussed here five years ago). When it writes an answer to a question, it literally just guesses which letter and word will come next in a sequence – based on the data it’s been trained on.
This means AI has no understanding. No consciousness. No knowledge in any real, human sense. Just pure probability-driven, engineered brilliance — nothing more, and nothing less.
So why is a real “thinking” AI likely impossible? Because it’s bodiless. It has no senses, no flesh, no nerves, no pain, no pleasure. It doesn’t hunger, desire or fear. And because there is no cognition — not a shred — there’s a fundamental gap between the data it consumes (data born out of human feelings and experience) and what it can do with them.
Philosopher David Chalmers calls the mysterious mechanism underlying the relationship between our physical body and consciousness the “hard problem of consciousness”. Eminent scientists have recently hypothesised that consciousness actually emerges from the integration of internal, mental states with sensory representations (such as changes in heart rate, sweating and much more).
Given the paramount importance of the human senses and emotion for consciousness to “happen”, there is a profound and probably irreconcilable disconnect between general AI, the machine, and consciousness, a human phenomenon.
So why is a real “thinking” AI likely impossible? Because it’s bodiless. It has no senses, no flesh, no nerves, no pain, no pleasure. It doesn’t hunger, desire or fear. And because there is no cognition — not a shred — there’s a fundamental gap between the data it consumes (data born out of human feelings and experience) and what it can do with them.
What? No.
Chatbots can’t think because they literally aren’t designed to think. If you somehow gave a chatbot a body it would be just as mindless because it’s just a probability engine.
Exactly. People see “AI” and think LLMs and diffusion models. Those are both probabilistic translation engines. They’re no more intelligent than an AC/DC converter, just a lot more complex.
However, there are neural networks and sense arrays in the field of AI, and those are designed to replicate the process of thought.
The real route to a thinking AI is likely a combination of the two, where a neural network can call on expert systems including translation engines to do the heavy lifting and then run a more nuanced decision tree over the results.
Thing is, modern LLMs and diffusion models are already more complex than a single human mind can fully comprehend, so we default to internally labelling them as either “like us” or “magic”, even when we theoretically know them to be nothing but really deep predictive models.
They’re no more intelligent than an AC/DC converter
The problem is in the definition of intelligence.
To me, intelligence is simply problem-solving ability. It does not necessarily imply consciousness, having self-awareness or anything like that. A simple calculator is already displaying intelligence, even if limited to a very narrow situational set of problems, in the sense that it can resolve mathematical questions.
That doesn’t mean the calculator is self aware… it just means it can resolve problems. Biological systems can also resolve problems without necessarily being aware of what they are doing… does the fungus actually knows it’s solving a maze the scientists prepared for it when it just expands following what is preprogrammed by its biological instincts determined by natural selection? Do the ants really know what they are doing when they find the shortest path just by instinctively following a scent of pheromones left by other ants?
Knowing exactly what causes consciousness is an entirely different problem… and it’s one that has not been resolved by any scientist or philosopher in a satisfactory manner. So we simply do not know that.
Seems to me your definition of intelligence ignores whole aspects of true intelligence, at least of the human kind, such as emotional intelligence and social intelligence and artistic intelligence and moral intelligence…
“Problem solving” is the name for what you described and it doesn’t necessarily require intelligence. In fact most intelligent people have encountered situations where it made solving a problem more difficult.
Yes there there as many types of intelligence as there are types of problems. Emotional intelligence deals with emotional problems, social intelligence deals with social problems. This doesn’t conflict with my definition, it’s still problem solving.
Just because a being is intelligent does not mean it can solve all the problems of all kinds, it would require general intelligence, and even a generally intelligent being needs the right training… if you are trained wrong or trained for a different kind of problem that does not fit the current one then your current experience might actually get in the way, as you point out.
Slime mold can solve mazes.
All the evidence suggests that our own minds are also nothing more than probability engines. The reason we consider humans to be intelligent is because our brains learn to model the events in the physical world that are fed into our brains by the nervous system. The whole purpose of a brain is to try and keep the body in a state of homeostasis. That’s the basis for our volition. The brain gets data about about the state of the organism, and interprets it as hunger, pain, fear, and so on. Then it uses its internal world model to figure out actions that will put the body into a more desirable state. From this perspective, embodiment would indeed be a necessary component of human style intelligence.
While LLMs on their own are unlikely to provide a sufficient basis for a reasoning system, its not strictly impossible that a model trained on sensory data from a robot body it inhabits wouldn’t be able to build a representation of the world and its body that could be used as the basis for decision making and volition.
My understanding is that the reason LLMs struggle with solving math and logic problems is that those have certain answers, not probabilistic ones. That seems pretty fundamentally different from humans! In fact, we have a tendency to assign too much certainty to things which are actually probabilistic, which leads to its own reasoning errors. But we can also correctly identify actual truth, prove it through induction and deduction, and then hold onto that truth forever and use it to learn even more things.
We certainly do probabilistic reasoning, but we also do axiomatic reasoning i.e. more than probability engines.
I suspect that something like LLMs is part of our toolkit, but I agree that this can’t be the whole picture. Ideas like neurosymbolic AI might be on the right track here. The idea here is to leverage LLMs at parsing and classifying noisy input data, which they’re good at, then use a symbolic logic engine to operate on the classified data. Something along these lines is much more likely to produce genuine intelligence. We’re still in very early stages of both understanding how the brain works and figuring out how to implement artificial reasoning.
All the evidence suggests that our own minds are also nothing more than probability engines.
This completely understates the gulf between what we call AI and how the human brain actually works. The difference is so severe that acting as if they’re quantitatively comparable is basically pseudoscience. You might as well start claiming that we’re not far off from building a Dyson sphere just because we invented solar panels.
Most “AI” these days are built using linear feed forward networks. The brain is constructed using nonlinear recurrent networks which are can do far more with less. Now you could theoretically create the same output from a linear feed forward network but it’s way less efficient and would require many more neurons to achieve such a result. Which is wild when you consider that there are orders of magnitude more synapses in just the regions of the brain associated with language than there are parameters used in even today’s most advanced “AI” models. Now consider that human synapses rely on over a hundred qualitatively different neurotransmitters and not just a single 16-bit number. It’s also not just the scale of the signal that transmits information in a human synapse but the pattern too. Would you be surprised to know that there are a whole variety of signaling patterns neurons use? Because that’s true too. I haven’t even gotten into the differences in complexity in terms of how neurons process the information they receive. As of now there is no “AI” system that comes anywhere close to replicating that kind of complexity. It’s absurd to suggest where dealing with qualitatively similar machines here.
This completely understates the gulf between what we call AI and how the human brain actually works.
Way to completely misrepresent what I was actually saying. Nowhere was I suggesting that there isn’t a huge difference between the two. What I pointed out is that, while undeniably more complex, our brains appear to work on similar principles.
My only point was that the feedback loop from embodiment creates the basis for volition, and that what we call intelligence is our ability to create internal models of the world that we use for decision making. So, this is likely a prerequisite for any artificial system that has any meaningful intelligence.
Maybe try engaging with that instead of writing a wall of text arguing with a straw man.
our brains appear to work on similar principles.
Sure in the same way that a horse and a motorcycle operate on similar principles and serve the same function.
Maybe try engaging with that instead of writing a wall of text arguing with a straw man.
Where the straw man? You’ve missed my point entirely. LLMs and the human mind operate on categorically different principles. All the verbiage used to describe neural network models has little to do with how the brain actually works. That’s honestly wasn’t a problem until Tech companies started purposely misusing those terms and now far too many people seem to think “AI” is something it’s not.
LLMs and the human mind operate on categorically different principles.
A bold statement given that we don’t actually understand how the brain operates exactly and what algorithms that would translate into.
Where the straw man?
The straw man is you continuing to argue against equating LLMs with the functioning of the brain, something I never said here.
All the verbiage used to describe neural network models has little to do with how the brain actually works.
You appear to be conflating the implementation details of how the brain works with the what it’s doing in a semantic sense. There is zero evidence that all the complexity of the brain is inherent to the way our reasoning functions. Again, we don’t have a full understanding of how the brain accomplishes tasks like reasoning. It may be a lot more complex than what LLMs do, or it may not be. We do not know.
Finally, none of this has anything to do with the point I was actually making which is regarding embodiment. You decided to ignore that to focus on braying about tech companies and LLMs instead.
The straw man is you continuing to argue against equating LLMs with the functioning of the brain, something I never said here.
I’m not claiming you ever said they functioned exactly the same way. Im simply stating that you’re way off base when you claim that they appear to operate using the same principles or that all evidence suggests the human mind is nothing more than a probability machine. That’s not a straw man. You literally said those things.
There is zero evidence that all the complexity of the brain is inherent to the way our reasoning functions.
You’re betraying your own ignorance about neuroscience. The complexity of the brain is absolutely linked with its ability to reason and we have plenty of evidence to show that. The evolutionary process does not just create needless complexity if there is a more efficient path.
Again, we don’t have a full understanding of how the brain accomplishes tasks like reasoning. It may be a lot more complex than what LLMs do, or it may not be. We do not know.
This is such a silly statement especially when you’ve been claiming that both the brain and AI appear to work using the same principles. If you truly believe the mind is such a mystery then stop making that claim.
You decided to ignore that to focus on braying about tech companies and LLMs instead.
I don’t really care about your arguments concerning embodiment because they’re so beside the point when you just blowing right by the most basic principles of neuroscience.
I bring up tech companies because they’ve had a massively distorting effect on how many computer scientists think the world works. You’re not immune to it either simply because you’re a critic of capitalism. A ruthless criticism of that exists includes the very researchers whose work you’re taking at face value.
Im simply stating that you’re way off base when you claim that they appear to operate using the same principles or that all evidence suggests the human mind is nothing more than a probability machine.
I literally said these things, and you never gave any actual counter argument to either of them.
You’re betraying your own ignorance about neuroscience. The complexity of the brain is absolutely linked with its ability to reason and we have plenty of evidence to show that. The evolutionary process does not just create needless complexity if there is a more efficient path.
You’re betraying your ignorance of how biology works and illustrating that you have absolutely no business debating this subject. Efficiency is not the primary fitness function for evolution, it’s survivability. And that means having a lot of redundancy baked into the system. Here’s a concrete example for you of just how much of the brain isn’t actually essential for normal day to day function. https://www.rifters.com/crawl/?p=6116
This is such a silly statement especially when you’ve been claiming that both the brain and AI appear to work using the same principles.
There’s nothing silly in stating that the underlying principles are similar, but we don’t understand a lot of the mechanics of the brain. If you truly can’t understand such basic things there’s little point trying to have a meaningful discussion.
I don’t really care about your arguments concerning embodiment because they’re so beside the point when you just blowing right by the most basic principles of neuroscience.
That’s literally the whole context for this thread, it just doesn’t fit with the straw man you want to argue about.
A ruthless criticism of that exists includes the very researchers whose work you’re taking at face value.
Whose work am I taking at face value specifically? You’re just spewing nonsense here without engaging with anything I’m saying.
“AI” is sparkling autocorrect. Its not smart. Its just manipulation of stats at scale.
It’s not pretend. People are getting caught in a collective delusion.
People who don’t like “AI” should check out the newsletter and / or podcast of Ed Zitron. He goes hard on the topic.
What is your opinion of “Conscious” by Annika Harris?
