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While I agree that LLMs are hardly sapient, it's very hard to make this argument without being able to pinpoint what a model of intelligence actually is. "Huma

While I agree that LLMs are hardly sapient, it's very hard to make this argument without being able to pinpoint what a model of intelligence actually is. "Human brains lack any model of intelligence. It's just neurons firing in complicated patterns in response to inputs based on what statistically leads to reproductive success"

no_wizard 2y ago
That's not at all on par with what I'm saying. There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior. We shouldn't seek to muddy this. EDIT: Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. This means you must be able to generalize, which in turn allows intelligent beings to react to new environments and contexts without previous experience or input. Nothing I'm aware of on the market can do this. LLMs are great at statistically inferring things, but they can't generalize which means they lack reasoning. They also lack the ability to seek new information without prompting. The fact that all LLMs boil down to (relatively) simple mathematics should be enough to prove the point as well. It lacks spontaneous reasoning, which is why the ability to generalize is key
- highfrequency 2y ago
  What is that baseline threshold for intelligence? Could you provide concrete and objective results, that if demonstrated by a computer system would satisfy your criteria for intelligence?
  - no_wizard 2y ago
    see the edit. boils down to the ability to generalize, LLMs can't generalize. I'm not the only one who holds this view either. Francois Chollet, a former intelligence researcher at Google also shares this view.
    - highfrequency 2y ago
      Are you able to formulate "generalization" in a concrete and objective way that could be achieved unambiguously, and is currently achieved by a typical human? A lot of people would say that LLMs generalize pretty well - they certainly can understand natural language sequences that are not present in their training data.
      - whilenot-dev 2y ago
        > A lot of people would say that LLMs generalize pretty well What do you mean here? The trained model, the inference engine, is the one that makes an LLM for "a lot of people". > they certainly can understand natural language sequences that are not present in their training data Keeping the trained model as LLM in mind, I think learning a language includes generalization and is typically achieved by a human, so I'll try to formulate: Can a trained LLM model learn languages that hasn't been in its training set just by chatting/prompting? Given that any Korean texts were excluded from the training set, could Korean be learned? Does that even work with languages descending from the same language family (Spanish in the training set but Italian should be learned)?
    - stevenAthompson 2y ago
      > Francois Chollet, a former intelligence researcher at Google also shares this view. Great, now there are two of you.
    - voidspark 2y ago
      Chollet's argument was that it's not "true" generalization, which would be at the level of human cognition. He sets the bar so high that it becomes a No True Scotsman fallacy. The deep neural networks are practically generalizing well enough to solve many tasks better than humans.
      - daveguy 2y ago
        No. His argument is definitely closer to LLMs can't generalize. I think you would benefit from re-reading the paper. The point is that a puzzle consisting of simple reasoning about simple priors should be a fairly low bar for "intelligence" (necessary but not sufficient). LLMs performs abysmally because they have a very specific purpose trained goal that is different from solving the ARC puzzles. Humans solve these easily. And committees of humans do so perfectly. If LLMs were intelligent they would be able to construct algorithms consisting of simple applications of the priors. Training to a specific task and getting better is completely orthogonal to generalized search and application of priors. Humans do a mix of both search of the operations and pattern matching of recognizing the difference between start and stop state. That is because their "algorithm" is so general purpose. And we have very little idea how the two are combined efficiently. At least this is how I interpreted the paper.
- david-gpu 2y ago
  > There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior. Go on. We are listening.
- byearthithatius 2y ago
  "There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior" not really. The whole point they are trying to make is that the capability of these models IS ALREADY muddying the definition of intelligence. We can't really test it because the distribution its learned is so vast. Hence why he have things like ARC now. Even if its just gradient descent based distribution learning and there is no "internal system" (whatever you think that should look like) to support learning the distribution, the question is if that is more than what we are doing or if we are starting to replicate our own mechanisms of learning.
  - dingnuts 2y ago
    How does an LLM muddy the definition of intelligence any more than a database or search engine does? They are lossy databases with a natural language interface, nothing more.
    - tibbar 2y ago
      Ah, but what is in the database? At this point it's clearly not just facts, but problem-solving strategies and an execution engine. A database of problem-solving strategies which you can query with a natural language description of your problem and it returns an answer to your problem... well... sounds like intelligence to me.
      - uoaei 2y ago
        > problem-solving strategies and an execution engine Extremely unfounded claims. See: the root comment of this tree.
        travisjungroth 2y ago
        …things that look like problem solving strategies in performance, then.
    - madethisnow 2y ago
      datasets and search engines are deterministic. humans, and llms are not.
- nmarinov 2y ago
  I think the confusion is because you're referring to a common understanding of what AI is but I think the definition of AI is different for different people. Can you give your definition of AI? Also what is the "generally accepted baseline definition for what crosses the threshold of intelligent behavior"?
- voidspark 2y ago
  You are doubling down on a muddled vague non-technical intuition about these terms. Please tell us what that "baseline definition" is.
- appleorchard46 2y ago
  > Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. Be that as it may, a core trait is very different from a generally accepted threshold. What exactly is the threshold? Which environments are you referring to? How is it being measured? What goals are they? You may have quantitative and unambiguous answers to these questions, but I don't think they would be commonly agreed upon.
- aj7 2y ago
  LLM’s are statistically great at inferring things? Pray tell me how often Google’s AI search paragraph, at the top, is correct or useful. Is that statistically great?
- nurettin 2y ago
  > intelligence is an agent’s ability to achieve goals in a wide range of environments. This means you must be able to generalize, which in turn allows intelligent beings to react to new environments and contexts without previous experience or input. I applaud the bravery of trying to one shot a definition of intelligence, but no intelligent being acts without previous experience or input. If you're talking about in-sample vs out of sample, LLMs do that all the time. At some point in the conversation, they encounter something completely new and react to it in a way that emulates an intelligent agent. What really makes them tick is language being a huge part of the intelligence puzzle, and language is something LLMs can generate at will. When we discover and learn to emulate the rest, we will get closer and closer to super intelligence.
- nl 2y ago
  > Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. This is the embodiment argument - that intelligence requires the ability to interact with its environment. Far from being generally accepted, it's a controversial take. Could Stephen Hawking achieve goals in a wide range of environments without help? And yet it's still generally accepted that Stephen Hawking was intelligent.
devmor 2y ago
I don't think your detraction has much merit. If I don't understand how a combustion engine works, I don't need that engineering knowledge to tell you that a bicycle [an LLM] isn't a car [a human brain] just because it fits the classification of a transportation vehicle [conversational interface]. This topic is incredibly fractured because there is too much monetary interest in redefining what "intelligence" means, so I don't think a technical comparison is even useful unless the conversation begins with an explicit definition of intelligence in relation to the claims.
- Velorivox 2y ago
  Bicycles and cars are too close. The analogy I like is human leg versus tire. That is a starker depiction of how silly it is to compare the two in terms of structure rather than result.
  - devmor 2y ago
    That is a much better comparison.
- uoaei 2y ago
  If you don't know anything except how words are used, you can definitely disambiguate "bicycle" and "car" solely based on the fact that the contexts they appear in are incongruent the vast majority of the time, and when they appear in the same context, they are explicitly contrasted against each other. This is just the "fancy statistics" argument again, and it serves to describe any similar example you can come up with better than "intelligence exists inside this black box because I'm vibing with the output".
  - devmor 2y ago
    Why are you attempting to technically analyze a simile? That is not why comparisons are used.
- SkyBelow 2y ago
  One problem is that we have been basing too much on [human brain] for so long that we ended up with some ethical problems as we decided other brains didn't count as intelligent. As such, science has taken an approach of not assuming humans are uniquely intelligence. We seem to be the best around at doing different tasks with tools, but other animals are not completely incapable of doing the same. So [human brain] should really be [brain]. But is that good enough? Is a fruit fly brain intelligent? Is it a goal to aim for? There is a second problem that we aren't looking for [human brain] or [brain], but [intelligence] or [sapient] or something similar. We aren't even sure what we want as many people have different ideas, and, as you pointed out, we have different people with different interest pushing for different underlying definitions of what these ideas even are. There is also a great deal of impreciseness in most any definitions we use, and AI encroaches on this in a way that reality rarely attacks our definitions. Philosophically, we aren't well prepared to defend against such attacks. If we had every ancestor of the cat before us, could we point out the first cat from the last non-cat in that lineup? In a precise way that we would all agree upon that isn't arbitrary? I doubt we could.
OtherShrezzing 2y ago
>While I agree that LLMs are hardly sapient, it's very hard to make this argument without being able to pinpoint what a model of intelligence actually is. Maybe so, but it's trivial to do the inverse, and pinpoint something that's not intelligent. I'm happy to state that an entity which has seen every game guide ever written, but still can't beat the first generation Pokemon is not intelligent. This isn't the ceiling for intelligence. But it's a reasonable floor.
- 7h3kk1d 2y ago
  There's sentient humans who can't beat the first generation pokemon games.
  - antasvara 2y ago
    Is there a sentient human that has access to (and actually uses) all of the Pokémon game guides yet is incapable of beating Pokémon? Because that's what an LLM is working with.
    - 7h3kk1d 2y ago
      I'm quite sure my grandma could not. You can make the argument these people aren't intelligent but I think that's a contrived argument.
whilenot-dev 2y ago
What's wrong with just calling them smart algorithmic models? Being smart allows somewhat to be wrong, as long as that leads to a satisfying solution. Being intelligent on the other hand requires foundational correctness in concepts that aren't even defined yet. EDIT: I also somewhat like the term imperative knowledge (models) [0] [0]: https://en.wikipedia.org/wiki/Procedural_knowledge https://en.wikipedia.org/wiki/Procedural_knowledge
- jfengel 2y ago
  The problem with "smart" is that they fail at things that dumb people succeed at. They have ludicrous levels of knowledge and a jaw dropping ability to connect pieces while missing what's right in front of them. The gap makes me uncomfortable with the implications of the word "smart". It is orthogonal to that.
  - sigmoid10 2y ago
    >they fail at things that dumb people succeed at Funnily enough, you can also observe that in humans. The number of times I have observed people from highly intellectual, high income/academic families struggle with simple tasks that even the dumbest people do with ease is staggering. If you're not trained for something and suddenly confronted with it for the first time, you will also in all likelihood fail. "Smart" is just as ill-defined as any other clumsy approach to define intelligence.
  - nradov 2y ago
    Bombs can be smart, even though they sometimes miss the target.
a_victorp 2y ago
> Human brains lack any model of intelligence. It's just neurons firing in complicated patterns in response to inputs based on what statistically leads to reproductive success The fact that you can reason about intelligence is a counter argument to this
- immibis 2y ago
  It seems like LLMs can also reason about intelligence. Does that make them intelligent? We don't know what intelligence is, or isn't.
  - syndeo 2y ago
    It's fascinating how this discussion about intelligence bumps up against the limits of text itself. We're here, reasoning and reflecting on what makes us capable of this conversation. Yet, the very structure of our arguments, the way we question definitions or assert self-awareness, mirrors patterns that LLMs are becoming increasingly adept at replicating. How confidently can we, reading these words onscreen, distinguish genuine introspection from a sophisticated echo? Case in point… I didn't write that paragraph by myself.
    - Nevermark 2y ago
      So you got help from a natural intelligence? No fair. (natdeo?) Someone needs to create a clone site of HN's format and posts, but the rules only permit synthetic intelligence comments. All models pre-prompted to read prolifically, but comment and up/down vote carefully and sparingly, to optimize the quality of discussion. And no looking at nat-HN comments. It would be very interesting to compare discussions between the sites. A human-lurker per day graph over time would also be of interest. Side thought: Has anyone created a Reverse-Captcha yet?
      - wyre 2y ago
        This is an entertaining idea. User prompts can synthesize a users domain knowledge whether they are an entrepreneur, code dev, engineer, hacker, designer, etc and it can also have different users between different LLMs. I think the site would clone the upvotes of articles and the ordering of the front page, and gives directions when to comment on other’s posts.
shinycode 2y ago
> "Human brains lack any model of intelligence. It's just neurons firing in complicated patterns in response to inputs based on what statistically leads to reproductive success" Are you sure about that ? Do we have proof of that ? In happened all the time trought history of science that a lot of scientists were convinced of something and a model of reality up until someone discovers a new proof and or propose a new coherent model. That’s literally the history of science, disprove what we thought was an established model
- johnecheck 2y ago
  Indeed, a good point. My comment assumes that our current model of the human brain is (sufficiently) complete. Your comment reveals an interesting corollary - those that believe in something beyond our understanding, like the Christian soul, may never be convinced that an AI is truly sapient.
andrepd 2y ago
Human brains do way more things than language. And non-human animals (with no language) also reason, and we cannot understand those either, barely even the very simplest ones.

no_wizard 2y ago

That's not at all on par with what I'm saying. There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior. We shouldn't seek to muddy this. EDIT: Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. This means you must be able to generalize, which in turn allows intelligent beings to react to new environments and contexts without previous experience or input. Nothing I'm aware of on the market can do this. LLMs are great at statistically inferring things, but they can't generalize which means they lack reasoning. They also lack the ability to seek new information without prompting. The fact that all LLMs boil down to (relatively) simple mathematics should be enough to prove the point as well. It lacks spontaneous reasoning, which is why the ability to generalize is key

highfrequency 2y ago
What is that baseline threshold for intelligence? Could you provide concrete and objective results, that if demonstrated by a computer system would satisfy your criteria for intelligence?
- no_wizard 2y ago
  see the edit. boils down to the ability to generalize, LLMs can't generalize. I'm not the only one who holds this view either. Francois Chollet, a former intelligence researcher at Google also shares this view.
  - highfrequency 2y ago
    Are you able to formulate "generalization" in a concrete and objective way that could be achieved unambiguously, and is currently achieved by a typical human? A lot of people would say that LLMs generalize pretty well - they certainly can understand natural language sequences that are not present in their training data.
    - whilenot-dev 2y ago
      > A lot of people would say that LLMs generalize pretty well What do you mean here? The trained model, the inference engine, is the one that makes an LLM for "a lot of people". > they certainly can understand natural language sequences that are not present in their training data Keeping the trained model as LLM in mind, I think learning a language includes generalization and is typically achieved by a human, so I'll try to formulate: Can a trained LLM model learn languages that hasn't been in its training set just by chatting/prompting? Given that any Korean texts were excluded from the training set, could Korean be learned? Does that even work with languages descending from the same language family (Spanish in the training set but Italian should be learned)?
  - stevenAthompson 2y ago
    > Francois Chollet, a former intelligence researcher at Google also shares this view. Great, now there are two of you.
  - voidspark 2y ago
    Chollet's argument was that it's not "true" generalization, which would be at the level of human cognition. He sets the bar so high that it becomes a No True Scotsman fallacy. The deep neural networks are practically generalizing well enough to solve many tasks better than humans.
    - daveguy 2y ago
      No. His argument is definitely closer to LLMs can't generalize. I think you would benefit from re-reading the paper. The point is that a puzzle consisting of simple reasoning about simple priors should be a fairly low bar for "intelligence" (necessary but not sufficient). LLMs performs abysmally because they have a very specific purpose trained goal that is different from solving the ARC puzzles. Humans solve these easily. And committees of humans do so perfectly. If LLMs were intelligent they would be able to construct algorithms consisting of simple applications of the priors. Training to a specific task and getting better is completely orthogonal to generalized search and application of priors. Humans do a mix of both search of the operations and pattern matching of recognizing the difference between start and stop state. That is because their "algorithm" is so general purpose. And we have very little idea how the two are combined efficiently. At least this is how I interpreted the paper.
david-gpu 2y ago
> There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior. Go on. We are listening.
byearthithatius 2y ago
"There exists a generally accepted baseline definition for what crosses the threshold of intelligent behavior" not really. The whole point they are trying to make is that the capability of these models IS ALREADY muddying the definition of intelligence. We can't really test it because the distribution its learned is so vast. Hence why he have things like ARC now. Even if its just gradient descent based distribution learning and there is no "internal system" (whatever you think that should look like) to support learning the distribution, the question is if that is more than what we are doing or if we are starting to replicate our own mechanisms of learning.
- dingnuts 2y ago
  How does an LLM muddy the definition of intelligence any more than a database or search engine does? They are lossy databases with a natural language interface, nothing more.
  - tibbar 2y ago
    Ah, but what is in the database? At this point it's clearly not just facts, but problem-solving strategies and an execution engine. A database of problem-solving strategies which you can query with a natural language description of your problem and it returns an answer to your problem... well... sounds like intelligence to me.
    - uoaei 2y ago
      > problem-solving strategies and an execution engine Extremely unfounded claims. See: the root comment of this tree.
      - travisjungroth 2y ago
        …things that look like problem solving strategies in performance, then.
  - madethisnow 2y ago
    datasets and search engines are deterministic. humans, and llms are not.
nmarinov 2y ago
I think the confusion is because you're referring to a common understanding of what AI is but I think the definition of AI is different for different people. Can you give your definition of AI? Also what is the "generally accepted baseline definition for what crosses the threshold of intelligent behavior"?
voidspark 2y ago
You are doubling down on a muddled vague non-technical intuition about these terms. Please tell us what that "baseline definition" is.
appleorchard46 2y ago
> Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. Be that as it may, a core trait is very different from a generally accepted threshold. What exactly is the threshold? Which environments are you referring to? How is it being measured? What goals are they? You may have quantitative and unambiguous answers to these questions, but I don't think they would be commonly agreed upon.
aj7 2y ago
LLM’s are statistically great at inferring things? Pray tell me how often Google’s AI search paragraph, at the top, is correct or useful. Is that statistically great?
nurettin 2y ago
> intelligence is an agent’s ability to achieve goals in a wide range of environments. This means you must be able to generalize, which in turn allows intelligent beings to react to new environments and contexts without previous experience or input. I applaud the bravery of trying to one shot a definition of intelligence, but no intelligent being acts without previous experience or input. If you're talking about in-sample vs out of sample, LLMs do that all the time. At some point in the conversation, they encounter something completely new and react to it in a way that emulates an intelligent agent. What really makes them tick is language being a huge part of the intelligence puzzle, and language is something LLMs can generate at will. When we discover and learn to emulate the rest, we will get closer and closer to super intelligence.
nl 2y ago
> Generally its accepted that a core trait of intelligence is an agent’s ability to achieve goals in a wide range of environments. This is the embodiment argument - that intelligence requires the ability to interact with its environment. Far from being generally accepted, it's a controversial take. Could Stephen Hawking achieve goals in a wide range of environments without help? And yet it's still generally accepted that Stephen Hawking was intelligent.

devmor 2y ago

I don't think your detraction has much merit. If I don't understand how a combustion engine works, I don't need that engineering knowledge to tell you that a bicycle [an LLM] isn't a car [a human brain] just because it fits the classification of a transportation vehicle [conversational interface]. This topic is incredibly fractured because there is too much monetary interest in redefining what "intelligence" means, so I don't think a technical comparison is even useful unless the conversation begins with an explicit definition of intelligence in relation to the claims.

Velorivox 2y ago
Bicycles and cars are too close. The analogy I like is human leg versus tire. That is a starker depiction of how silly it is to compare the two in terms of structure rather than result.
- devmor 2y ago
  That is a much better comparison.
uoaei 2y ago
If you don't know anything except how words are used, you can definitely disambiguate "bicycle" and "car" solely based on the fact that the contexts they appear in are incongruent the vast majority of the time, and when they appear in the same context, they are explicitly contrasted against each other. This is just the "fancy statistics" argument again, and it serves to describe any similar example you can come up with better than "intelligence exists inside this black box because I'm vibing with the output".
- devmor 2y ago
  Why are you attempting to technically analyze a simile? That is not why comparisons are used.
SkyBelow 2y ago
One problem is that we have been basing too much on [human brain] for so long that we ended up with some ethical problems as we decided other brains didn't count as intelligent. As such, science has taken an approach of not assuming humans are uniquely intelligence. We seem to be the best around at doing different tasks with tools, but other animals are not completely incapable of doing the same. So [human brain] should really be [brain]. But is that good enough? Is a fruit fly brain intelligent? Is it a goal to aim for? There is a second problem that we aren't looking for [human brain] or [brain], but [intelligence] or [sapient] or something similar. We aren't even sure what we want as many people have different ideas, and, as you pointed out, we have different people with different interest pushing for different underlying definitions of what these ideas even are. There is also a great deal of impreciseness in most any definitions we use, and AI encroaches on this in a way that reality rarely attacks our definitions. Philosophically, we aren't well prepared to defend against such attacks. If we had every ancestor of the cat before us, could we point out the first cat from the last non-cat in that lineup? In a precise way that we would all agree upon that isn't arbitrary? I doubt we could.

OtherShrezzing 2y ago

>While I agree that LLMs are hardly sapient, it's very hard to make this argument without being able to pinpoint what a model of intelligence actually is. Maybe so, but it's trivial to do the inverse, and pinpoint something that's not intelligent. I'm happy to state that an entity which has seen every game guide ever written, but still can't beat the first generation Pokemon is not intelligent. This isn't the ceiling for intelligence. But it's a reasonable floor.

7h3kk1d 2y ago
There's sentient humans who can't beat the first generation pokemon games.
- antasvara 2y ago
  Is there a sentient human that has access to (and actually uses) all of the Pokémon game guides yet is incapable of beating Pokémon? Because that's what an LLM is working with.
  - 7h3kk1d 2y ago
    I'm quite sure my grandma could not. You can make the argument these people aren't intelligent but I think that's a contrived argument.

whilenot-dev 2y ago

What's wrong with just calling them smart algorithmic models? Being smart allows somewhat to be wrong, as long as that leads to a satisfying solution. Being intelligent on the other hand requires foundational correctness in concepts that aren't even defined yet. EDIT: I also somewhat like the term imperative knowledge (models) [0] [0]: https://en.wikipedia.org/wiki/Procedural_knowledge https://en.wikipedia.org/wiki/Procedural_knowledge

jfengel 2y ago
The problem with "smart" is that they fail at things that dumb people succeed at. They have ludicrous levels of knowledge and a jaw dropping ability to connect pieces while missing what's right in front of them. The gap makes me uncomfortable with the implications of the word "smart". It is orthogonal to that.
- sigmoid10 2y ago
  >they fail at things that dumb people succeed at Funnily enough, you can also observe that in humans. The number of times I have observed people from highly intellectual, high income/academic families struggle with simple tasks that even the dumbest people do with ease is staggering. If you're not trained for something and suddenly confronted with it for the first time, you will also in all likelihood fail. "Smart" is just as ill-defined as any other clumsy approach to define intelligence.
- nradov 2y ago
  Bombs can be smart, even though they sometimes miss the target.

a_victorp 2y ago

> Human brains lack any model of intelligence. It's just neurons firing in complicated patterns in response to inputs based on what statistically leads to reproductive success The fact that you can reason about intelligence is a counter argument to this

immibis 2y ago
It seems like LLMs can also reason about intelligence. Does that make them intelligent? We don't know what intelligence is, or isn't.
- syndeo 2y ago
  It's fascinating how this discussion about intelligence bumps up against the limits of text itself. We're here, reasoning and reflecting on what makes us capable of this conversation. Yet, the very structure of our arguments, the way we question definitions or assert self-awareness, mirrors patterns that LLMs are becoming increasingly adept at replicating. How confidently can we, reading these words onscreen, distinguish genuine introspection from a sophisticated echo? Case in point… I didn't write that paragraph by myself.
  - Nevermark 2y ago
    So you got help from a natural intelligence? No fair. (natdeo?) Someone needs to create a clone site of HN's format and posts, but the rules only permit synthetic intelligence comments. All models pre-prompted to read prolifically, but comment and up/down vote carefully and sparingly, to optimize the quality of discussion. And no looking at nat-HN comments. It would be very interesting to compare discussions between the sites. A human-lurker per day graph over time would also be of interest. Side thought: Has anyone created a Reverse-Captcha yet?
    - wyre 2y ago
      This is an entertaining idea. User prompts can synthesize a users domain knowledge whether they are an entrepreneur, code dev, engineer, hacker, designer, etc and it can also have different users between different LLMs. I think the site would clone the upvotes of articles and the ordering of the front page, and gives directions when to comment on other’s posts.

shinycode 2y ago

> "Human brains lack any model of intelligence. It's just neurons firing in complicated patterns in response to inputs based on what statistically leads to reproductive success" Are you sure about that ? Do we have proof of that ? In happened all the time trought history of science that a lot of scientists were convinced of something and a model of reality up until someone discovers a new proof and or propose a new coherent model. That’s literally the history of science, disprove what we thought was an established model

johnecheck 2y ago
Indeed, a good point. My comment assumes that our current model of the human brain is (sufficiently) complete. Your comment reveals an interesting corollary - those that believe in something beyond our understanding, like the Christian soul, may never be convinced that an AI is truly sapient.

andrepd 2y ago

Human brains do way more things than language. And non-human animals (with no language) also reason, and we cannot understand those either, barely even the very simplest ones.