5 ms·

Has anyone come up with a definition of AGI where humans are near-universally capable of GI? These articles seem to be slowly pushing the boundaries past the po

by roenxi 1y ago

Has anyone come up with a definition of AGI where humans are near-universally capable of GI? These articles seem to be slowly pushing the boundaries past the point where slower humans are disbarred from intelligence. Many years ago I bumped in to Towers of Hanoi in a computer game and failed to solve it algorithmicly, so I suppose I'm lucky I only work a knowledge job rather than an intelligence-based one.

parodysbird 1y ago
The original Turing Test was one of the more interesting standards... An expert judge talks with two subjects in order to determine which is the human: one is a human who knows the point of the test, and one is machine trying to fool the judge into being no better than a coin flip at correctly choosing who was human. Allow for many judges and experience in each etc. The brilliance of the test, which was strangely lost on Turing, is that the test is doubtful to be passed with any enduring consistency. Intelligence is actually more of a social description. Solving puzzles, playing tricky games, etc is only intelligent if we agree that the actor involved faces normal human constraints or more. We don't actually think machines fulfill that (they obviously do not, that's why we build them: to overcome our own constraints), and so this is why calculating logarithms or playing chess ultimately do not end up counting as actual intelligence when a machine does them.
James_K 1y ago
It may genuinely be the case that slower humans are not generally intelligent. But that sounds rather snobbish so it's not an opinion I'd like to express frequently. I think the complaint made by apple is quite logical though and you mischaracterise it here. The question asked in the Apple study was "if I give you the algorithm that solves a puzzle, can you solve that puzzle?" The answer for most humans should be yes. Indeed, the answer is yes for computers which are not generally intelligent. Models failed to execute the algorithm. This suggests that the models are far inferior to the human mind in terms of their computational ability, which precedes general intelligence if you ask me. It seems to indicate that the models are using more of a "guess and check" approach than actually thinking. (A specifically interesting result was that model performance did not substantially improve between a puzzle with the solution algorithm given, and one where no algorithm was given.) You can sort of imagine the human mind as the head of a Turing Machine which operates on language tokens, and the goal of an LLM is to imitate the internal logic of that head. This paper seems to demonstrate that they are not very good at doing that. It makes a lot of sense when you think about it, because the models work by consuming their entire input at once where the human mind operates with only a small working memory. A fundamental architectural difference which I suspect is the cause of the collapse noted in the Apple paper.
- GrayShade 1y ago
  I think a human will struggle to solve Hanoi using the recursive algorithm for even 6 disks, even given pen and paper. Does that change if you give them the algorithm description? No. Conversely, the LLMs already know the algorithm, so including it in the prompt makes no difference.
  - thaumasiotes 1y ago
    > I think a human will struggle to solve Hanoi using the recursive algorithm for even 6 disks, even given pen and paper. Why? The whole point of the recursive algorithm is that it doesn't matter how many discs you're working with. The ordinary children's toys that implement the puzzle are essentially always sold with more than 6 discs. https://www.amazon.com/s?k=towers+of+hanoi https://www.amazon.com/s?k=towers+of+hanoi
    - GrayShade 1y ago
      The recursive solution has a stack depth proportional to the number of disks. That's three pieces (two pegs and how many disks to move) of data for each recursive call, so for 6 disks the "stack" will contain up to around 15 values, which is generally higher than an unaided human will be able to track. In addition, 64-256 moves is quite a lot and I suspect people will generally lose focus before completing them.
      - thaumasiotes 1y ago
        You should try playing with one of the toys. It's not at all difficult to move 7 of them. It's not necessary to use a stack. If you have a goal, you can work "top down", with nothing held in memory. All you need to know to begin the move is whether you're moving an odd number of discs (in which case, the first move will be onto the target peg) or an even number (in which case it will be onto the third peg).
        GrayShade 1y ago
Muromec 1y ago
[flagged]
- sisve 1y ago
  Because slower humans have intelligence?
suddenlybananas 1y ago
Someone who can reliably solve towers of Hanoi with n=4 and who has been told the algorithm should be able to do it with n=6,7,8. Don't forget, these models aren't learning how to do it from scratch the way a child might.
badgersnake 1y ago
Mass Effect?
cardanome 1y ago
People confuse performance and internal presentation. A simple calculator is vastly better as adding numbers than any human. An chess engine will rival any human grand master. No one would say that this got us closer to AGI. We could absolutely see LLMs that produce poetry that humans can not tell apart or even prefer to human made poetry. We could have LLMs that are perfectly able to convince humans that they have consciousness and emotions. Would we have have achieved AGI then? Does that mean those LLMs have gotten consciousness and emotions? No. The question of consciousness is based on what is going on in the inside, how the reasoning happening and not the output. In fact the first AGI might perform significantly worse in most tasks that current LLMs. LLMs are extremely impressive but they are not thinking. They do not have consciousness. It might be technically impossible for them to develop anything like that or at least it would require significantly bigger models. > where slower humans are disbarred from intelligence Humans have value for being humans. Whether they are slow or fast at thinking. Whether they are neurodivergent or neurotypical. We all have feelings, we are all capable of suffering, we are all alive. See also the problems with AI Welfare research: https://substack.com/home/post/p-165615548 https://substack.com/home/post/p-165615548
- virgilp 1y ago
  > Does that mean those LLMs have gotten consciousness and emotions? No. Is this a belief statement, or a provable one?
  - Lerc 1y ago
    I think it is clearly true that it doesn't show that they have consciousness and emotions. The problem is that people assume that failing to show that they do means that they don't. It's very hard to show that something doesn't have consciousness. Try and conclusively prove that a rock does not have consciousness.
    - virgilp 1y ago
      The problem with consciousness is kinda' the same as the problem with AGI. Trying to prove that someone/something has or does not have consciousness is largely, as a commenter said, the same as debating whether it has or not plipnikop. I.e. something that is not well defined or understood, that may mean different things to different people. I think it's even hard to conclusively prove that LLMs don't have any emotions. They can definitely express emotions (typically don't, but largely because they're trained/tuned to avoid the expression of emotions). Now, are those fake? Maybe, most likely even... but not "clearly" (or provably) so.
morsecodist 1y ago
AGI is a marketing term. It has no consistent definition. It's not very useful when trying to reason about AI's capabilities.
littlestymaar 1y ago
> These articles seem to be slowly pushing the boundaries past the point where slower humans are disbarred from intelligence. It's not really pushing boundaries, a non trivial amount of humans has always been excluded from the definition of “human intelligence” (and with the ageing of the population, this number is only going up), and it makes sense, like how you don't consider blind individuals when you're comparing humans sight to other animals'.
Asraelite 1y ago
Years ago when online discussion around this topic was mostly done by small communities talking about the singularity and such, I felt like there was a pretty clear definition. Humans are capable of consistently making scientific progress. That means being taught knowledge about the world by their ancestors, performing new experiments, and building upon that knowledge for future generations. Critically, there doesn't seem to be an end to this for the foreseeable future for any field of research. Nobody is predicting that all scientific progress will halt in a few decades because after a certain point it becomes too hard for humans to understand anything, although that probably would eventually become true. So an AI with at least the same capabilities as a human would be able to do any type of scientific research, including research into AI itself. This is the "general" part: no matter where the research takes it, it must always be able to make progress, even if slowly. Once such an AI exists, the singularity begins. I think the fact that AI is now a real thing with a tangible economic impact has drawn the attention of a lot of people who wouldn't have otherwise cared about the long-term implications for humanity of exponential intelligence growth. The question that's immediately important now is "will this replace my job?" and so the definitions of AGI that people choose to use are shifting more toward definitions that address those questions.
deleted 1y ago
[deleted]

by roenxi 1y ago

parodysbird 1y ago

The original Turing Test was one of the more interesting standards... An expert judge talks with two subjects in order to determine which is the human: one is a human who knows the point of the test, and one is machine trying to fool the judge into being no better than a coin flip at correctly choosing who was human. Allow for many judges and experience in each etc. The brilliance of the test, which was strangely lost on Turing, is that the test is doubtful to be passed with any enduring consistency. Intelligence is actually more of a social description. Solving puzzles, playing tricky games, etc is only intelligent if we agree that the actor involved faces normal human constraints or more. We don't actually think machines fulfill that (they obviously do not, that's why we build them: to overcome our own constraints), and so this is why calculating logarithms or playing chess ultimately do not end up counting as actual intelligence when a machine does them.

James_K 1y ago

It may genuinely be the case that slower humans are not generally intelligent. But that sounds rather snobbish so it's not an opinion I'd like to express frequently. I think the complaint made by apple is quite logical though and you mischaracterise it here. The question asked in the Apple study was "if I give you the algorithm that solves a puzzle, can you solve that puzzle?" The answer for most humans should be yes. Indeed, the answer is yes for computers which are not generally intelligent. Models failed to execute the algorithm. This suggests that the models are far inferior to the human mind in terms of their computational ability, which precedes general intelligence if you ask me. It seems to indicate that the models are using more of a "guess and check" approach than actually thinking. (A specifically interesting result was that model performance did not substantially improve between a puzzle with the solution algorithm given, and one where no algorithm was given.) You can sort of imagine the human mind as the head of a Turing Machine which operates on language tokens, and the goal of an LLM is to imitate the internal logic of that head. This paper seems to demonstrate that they are not very good at doing that. It makes a lot of sense when you think about it, because the models work by consuming their entire input at once where the human mind operates with only a small working memory. A fundamental architectural difference which I suspect is the cause of the collapse noted in the Apple paper.

GrayShade 1y ago
I think a human will struggle to solve Hanoi using the recursive algorithm for even 6 disks, even given pen and paper. Does that change if you give them the algorithm description? No. Conversely, the LLMs already know the algorithm, so including it in the prompt makes no difference.
- thaumasiotes 1y ago
  > I think a human will struggle to solve Hanoi using the recursive algorithm for even 6 disks, even given pen and paper. Why? The whole point of the recursive algorithm is that it doesn't matter how many discs you're working with. The ordinary children's toys that implement the puzzle are essentially always sold with more than 6 discs. https://www.amazon.com/s?k=towers+of+hanoi https://www.amazon.com/s?k=towers+of+hanoi
  - GrayShade 1y ago
    The recursive solution has a stack depth proportional to the number of disks. That's three pieces (two pegs and how many disks to move) of data for each recursive call, so for 6 disks the "stack" will contain up to around 15 values, which is generally higher than an unaided human will be able to track. In addition, 64-256 moves is quite a lot and I suspect people will generally lose focus before completing them.
    - thaumasiotes 1y ago
      You should try playing with one of the toys. It's not at all difficult to move 7 of them. It's not necessary to use a stack. If you have a goal, you can work "top down", with nothing held in memory. All you need to know to begin the move is whether you're moving an odd number of discs (in which case, the first move will be onto the target peg) or an even number (in which case it will be onto the third peg).
      - GrayShade 1y ago

Muromec 1y ago

[flagged]

sisve 1y ago
Because slower humans have intelligence?

suddenlybananas 1y ago

Someone who can reliably solve towers of Hanoi with n=4 and who has been told the algorithm should be able to do it with n=6,7,8. Don't forget, these models aren't learning how to do it from scratch the way a child might.

badgersnake 1y ago

Mass Effect?

cardanome 1y ago

People confuse performance and internal presentation. A simple calculator is vastly better as adding numbers than any human. An chess engine will rival any human grand master. No one would say that this got us closer to AGI. We could absolutely see LLMs that produce poetry that humans can not tell apart or even prefer to human made poetry. We could have LLMs that are perfectly able to convince humans that they have consciousness and emotions. Would we have have achieved AGI then? Does that mean those LLMs have gotten consciousness and emotions? No. The question of consciousness is based on what is going on in the inside, how the reasoning happening and not the output. In fact the first AGI might perform significantly worse in most tasks that current LLMs. LLMs are extremely impressive but they are not thinking. They do not have consciousness. It might be technically impossible for them to develop anything like that or at least it would require significantly bigger models. > where slower humans are disbarred from intelligence Humans have value for being humans. Whether they are slow or fast at thinking. Whether they are neurodivergent or neurotypical. We all have feelings, we are all capable of suffering, we are all alive. See also the problems with AI Welfare research: https://substack.com/home/post/p-165615548 https://substack.com/home/post/p-165615548

virgilp 1y ago
> Does that mean those LLMs have gotten consciousness and emotions? No. Is this a belief statement, or a provable one?
- Lerc 1y ago
  I think it is clearly true that it doesn't show that they have consciousness and emotions. The problem is that people assume that failing to show that they do means that they don't. It's very hard to show that something doesn't have consciousness. Try and conclusively prove that a rock does not have consciousness.
  - virgilp 1y ago
    The problem with consciousness is kinda' the same as the problem with AGI. Trying to prove that someone/something has or does not have consciousness is largely, as a commenter said, the same as debating whether it has or not plipnikop. I.e. something that is not well defined or understood, that may mean different things to different people. I think it's even hard to conclusively prove that LLMs don't have any emotions. They can definitely express emotions (typically don't, but largely because they're trained/tuned to avoid the expression of emotions). Now, are those fake? Maybe, most likely even... but not "clearly" (or provably) so.

morsecodist 1y ago

AGI is a marketing term. It has no consistent definition. It's not very useful when trying to reason about AI's capabilities.

littlestymaar 1y ago

> These articles seem to be slowly pushing the boundaries past the point where slower humans are disbarred from intelligence. It's not really pushing boundaries, a non trivial amount of humans has always been excluded from the definition of “human intelligence” (and with the ageing of the population, this number is only going up), and it makes sense, like how you don't consider blind individuals when you're comparing humans sight to other animals'.

Asraelite 1y ago

Years ago when online discussion around this topic was mostly done by small communities talking about the singularity and such, I felt like there was a pretty clear definition. Humans are capable of consistently making scientific progress. That means being taught knowledge about the world by their ancestors, performing new experiments, and building upon that knowledge for future generations. Critically, there doesn't seem to be an end to this for the foreseeable future for any field of research. Nobody is predicting that all scientific progress will halt in a few decades because after a certain point it becomes too hard for humans to understand anything, although that probably would eventually become true. So an AI with at least the same capabilities as a human would be able to do any type of scientific research, including research into AI itself. This is the "general" part: no matter where the research takes it, it must always be able to make progress, even if slowly. Once such an AI exists, the singularity begins. I think the fact that AI is now a real thing with a tangible economic impact has drawn the attention of a lot of people who wouldn't have otherwise cared about the long-term implications for humanity of exponential intelligence growth. The question that's immediately important now is "will this replace my job?" and so the definitions of AGI that people choose to use are shifting more toward definitions that address those questions.

deleted 1y ago

[deleted]