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The difference is that we have neither the scientific knowledge nor the computational power to make an exact model of the human brain (nor we are anywhere close

by qsort 6y ago

The difference is that we have neither the scientific knowledge nor the computational power to make an exact model of the human brain (nor we are anywhere close to either requirement, AFAIK). In other words, we cannot pinpoint the exact sequence of operations and events that produce a certain behavior, while we absolutely can do that with ML models (you could in principle run machine learning models with pen and paper, obviously). If you could show me a program that emulates my brain to a certain degree of precision (it's unlikely that such a program would be a deterministic one, by the way), I would have no problem accepting that my brain is not meaningfully different from that program.

malkarouri 6y ago
So you are defining intelligence to be whatever the brain does? That is certainly a philosophical position.
- qsort 6y ago
  "Intelligence" is a word that, etymologically and semantically, is related to human or human-like capabilities. You wouldn't say that a leaf floating on a lake is swimming, and likewise, claiming that computers are "learning" or "intelligent" is at best a thin analogy and at worst a mischaracterization of the process. What's happening in my brain is something we don't have full scientific knowledge of, but we know it's not x86 machine code. While the two processes may be in many ways similar, conflating the two into this ill-defined concept of "intelligence" is a discussion about semantics more than anything else.
  - mannykannot 6y ago
    > "Intelligence" is a word that, etymologically and semantically, is related to human or human-like capabilities. You wouldn't say that a leaf floating on a lake is swimming. The definition of words changes in response to increasing knowledge - just take 'energy' for example. One cannot establish truths about the world by arguments from usage. (On the other hand, to be clear, I do not think that the current state of AI merits being called "intelligence". What happens in the future is speculation.) > What's happening in my brain is something we don't have full scientific knowledge of, but we know it's not x86 machine code. The introduction of x86 machine code at this point seems to be moving away from your original claims about "AI" being "just" relatively simple (though not simply linear) mathematical models, which are not "just" machine code either. The interesting (and very much open) question is how much of intelligence can be modeled in this way, and what else, if anything, is necessary. The more you stress the simplicity of these models, the more intriguing their achievements seem.
    - qsort 6y ago
      > The definition of words changes in response to increasing knowledge The usual process in mathematics and science is that you have a phenomenon that everyone agree exists but nobody can quite put their finger on it, so someone proposes a formal definition and if that definition turns out to be adequate, people work on the formal definition, and that's much easier because you now can use math, statistics, formal methods, etc; a prime example of this is the notion of "computability". I don't believe that we are seeing the same thing with the concept of "intelligence", this is probably in part because it's much harder to capture the concept in a formal definition. Computers do computable stuff. Overlapping that notion with "intelligence" serves no purpose in my opinion: it explains nothing, it doesn't clarify anything, and it's certainly not obvious that the two are related. > which are not "just" machine code either I'm using "machine code" as proxy for "instructions/lambdas/whatever for a computational model of your choice", which they certainly are. > The more you stress the simplicity of these models, the more intriguing their achievements seem. It's not my intention to downplay any of the achievements of "AI". They are certainly not less intriguing when viewed from my perspective, the same way a compiler is not less intriguing if you think it's "just code". My point is that any association of a formal concept (math, models, etc.) with philosophical concepts (intelligence, "truths about the world", consciousness, etc.) is always on thin ice, because natural language and formal concepts are hard to mix. Especially so when the concepts at play are so ephemeral.
      - Retric 6y ago
        People learn to hit a target by changing the structure of their brain to fit the task. Computers become better at hitting a target by changing a data structure. That seems directly analogous to me. Critically, learning doesn’t imply the ability to perfectly execute the task.
        qsort 6y ago
        I could not imagine two things that are more unrelated.
        6y ago
- rtx 6y ago
  AI isn't intelligent, its something created by intelligence.
laichzeit0 6y ago
It’s weird that you compare AI to the human brain. I think the goal is here in the long term is to surpass the mere human brain. For that reason it’s stupid to try and model it at all. Maybe some future neural architecture will make the human brain look like a computer built using vacuum tubes.
ajuc 6y ago
> The difference is that we have neither the scientific knowledge nor the computational power to make an exact model of the human brain So AI is the part of computing we don't know how to do yet as in the joke :) ?

by qsort 6y ago

malkarouri 6y ago

So you are defining intelligence to be whatever the brain does? That is certainly a philosophical position.

qsort 6y ago
"Intelligence" is a word that, etymologically and semantically, is related to human or human-like capabilities. You wouldn't say that a leaf floating on a lake is swimming, and likewise, claiming that computers are "learning" or "intelligent" is at best a thin analogy and at worst a mischaracterization of the process. What's happening in my brain is something we don't have full scientific knowledge of, but we know it's not x86 machine code. While the two processes may be in many ways similar, conflating the two into this ill-defined concept of "intelligence" is a discussion about semantics more than anything else.
- mannykannot 6y ago
  > "Intelligence" is a word that, etymologically and semantically, is related to human or human-like capabilities. You wouldn't say that a leaf floating on a lake is swimming. The definition of words changes in response to increasing knowledge - just take 'energy' for example. One cannot establish truths about the world by arguments from usage. (On the other hand, to be clear, I do not think that the current state of AI merits being called "intelligence". What happens in the future is speculation.) > What's happening in my brain is something we don't have full scientific knowledge of, but we know it's not x86 machine code. The introduction of x86 machine code at this point seems to be moving away from your original claims about "AI" being "just" relatively simple (though not simply linear) mathematical models, which are not "just" machine code either. The interesting (and very much open) question is how much of intelligence can be modeled in this way, and what else, if anything, is necessary. The more you stress the simplicity of these models, the more intriguing their achievements seem.
  - qsort 6y ago
    > The definition of words changes in response to increasing knowledge The usual process in mathematics and science is that you have a phenomenon that everyone agree exists but nobody can quite put their finger on it, so someone proposes a formal definition and if that definition turns out to be adequate, people work on the formal definition, and that's much easier because you now can use math, statistics, formal methods, etc; a prime example of this is the notion of "computability". I don't believe that we are seeing the same thing with the concept of "intelligence", this is probably in part because it's much harder to capture the concept in a formal definition. Computers do computable stuff. Overlapping that notion with "intelligence" serves no purpose in my opinion: it explains nothing, it doesn't clarify anything, and it's certainly not obvious that the two are related. > which are not "just" machine code either I'm using "machine code" as proxy for "instructions/lambdas/whatever for a computational model of your choice", which they certainly are. > The more you stress the simplicity of these models, the more intriguing their achievements seem. It's not my intention to downplay any of the achievements of "AI". They are certainly not less intriguing when viewed from my perspective, the same way a compiler is not less intriguing if you think it's "just code". My point is that any association of a formal concept (math, models, etc.) with philosophical concepts (intelligence, "truths about the world", consciousness, etc.) is always on thin ice, because natural language and formal concepts are hard to mix. Especially so when the concepts at play are so ephemeral.
    - Retric 6y ago
      People learn to hit a target by changing the structure of their brain to fit the task. Computers become better at hitting a target by changing a data structure. That seems directly analogous to me. Critically, learning doesn’t imply the ability to perfectly execute the task.
      - qsort 6y ago
        I could not imagine two things that are more unrelated.
        6y ago
rtx 6y ago
AI isn't intelligent, its something created by intelligence.

laichzeit0 6y ago

It’s weird that you compare AI to the human brain. I think the goal is here in the long term is to surpass the mere human brain. For that reason it’s stupid to try and model it at all. Maybe some future neural architecture will make the human brain look like a computer built using vacuum tubes.

ajuc 6y ago

> The difference is that we have neither the scientific knowledge nor the computational power to make an exact model of the human brain So AI is the part of computing we don't know how to do yet as in the joke :) ?