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I think the article is in the general category of articles suggesting that planes would work better if they flapped their wings. AI's "think" like planes "fly"

I think the article is in the general category of articles suggesting that planes would work better if they flapped their wings. AI's "think" like planes "fly" and submarines "swim". Does it matter if a plane experiences flight the way an eagle does if it still gets you from LA to New York in a few hours?

lucisferre 1y ago
Much of the discussion of AI flirts with science fiction more than fact. Let's start with the fact that AGI is not a well defined or agreed upon term of reference.
- empath75 1y ago
  100% agreed. I think, in fact, that "intelligence" itself is a near-meaningless term, let alone AGI. The evidence for this is that nobody can agree on what actually requires intelligence, other than there is seemingly broad belief among people that if a computer can do it, then it doesn't. If you can't point at some activity and say: "There, this absolutely requires intelligence, let there be zero doubt that this entity possesses it", then it's not measurable and probably doesn't exist.
deleted 1y ago
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staticman2 1y ago
I feel the term AGI is meaningless but if I'm going to strongman the article. If your claim is, "AGI's "think" like planes "fly" and submarines "swim". You only get to make that claim with confidence if you've invented an AGI.
emp17344 1y ago
Except AI doesn’t do anything better than the human mind, and doesn’t have any use cases beyond what humans can do.
- empath75 1y ago
  > Except AI doesn’t do anything better than the human mind, There are all kinds of tasks that AI's are better at than most people.
catlifeonmars 1y ago
I think the analogy actually works better the other way. LLMs “think” the way humans speak. This is closer to having a machine that worked by flapping its wings when a more efficient machine would use fixed wings and a jet engine. Language is an extremely roundabout way to understanding.
- Dylan16807 1y ago
  At least the roundabout flappy machine gets off the ground in your analogy. The other options we have are big logic chains that don't work and neural simulations that would require all the computers in the world.
  - catlifeonmars 1y ago
    Yeah definitely. We have to start somewhere and what we have works. I just think that language based models are a v0
- lostmsu 1y ago
  LLMs don't think the way humans speak. LLMs process sequences of high-dimensional vectors.
  - catlifeonmars 1y ago
    Yeah that was very hand wavy on my part. What I meant to say is that LLMs encode the relationships between words. The idea being that the relationship between words is a good enough representation of the relationship between the things that the words represent. I am conjecturing 1. that solely relying on written artifacts by produced by humans has some upper bound on the amount of knowledge that can be represented. 2. that language is an inefficient representation of human knowledge. It’s redundant and contains inaccuracies. Using written artifacts is not the shortest path to learning. For example, take mathematics. It’s not sufficient to read a ton of math literature to effectively learn math. There’s a component of discovery that comes from e.g attempting to write a proof that can’t be replaced by reading all of the proofs that already exist. Anyway I would take all this with a giant grain of salt.

lucisferre 1y ago

Much of the discussion of AI flirts with science fiction more than fact. Let's start with the fact that AGI is not a well defined or agreed upon term of reference.

empath75 1y ago
100% agreed. I think, in fact, that "intelligence" itself is a near-meaningless term, let alone AGI. The evidence for this is that nobody can agree on what actually requires intelligence, other than there is seemingly broad belief among people that if a computer can do it, then it doesn't. If you can't point at some activity and say: "There, this absolutely requires intelligence, let there be zero doubt that this entity possesses it", then it's not measurable and probably doesn't exist.

deleted 1y ago

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staticman2 1y ago

I feel the term AGI is meaningless but if I'm going to strongman the article. If your claim is, "AGI's "think" like planes "fly" and submarines "swim". You only get to make that claim with confidence if you've invented an AGI.

emp17344 1y ago

Except AI doesn’t do anything better than the human mind, and doesn’t have any use cases beyond what humans can do.

empath75 1y ago
> Except AI doesn’t do anything better than the human mind, There are all kinds of tasks that AI's are better at than most people.

catlifeonmars 1y ago

I think the analogy actually works better the other way. LLMs “think” the way humans speak. This is closer to having a machine that worked by flapping its wings when a more efficient machine would use fixed wings and a jet engine. Language is an extremely roundabout way to understanding.

Dylan16807 1y ago
At least the roundabout flappy machine gets off the ground in your analogy. The other options we have are big logic chains that don't work and neural simulations that would require all the computers in the world.
- catlifeonmars 1y ago
  Yeah definitely. We have to start somewhere and what we have works. I just think that language based models are a v0
lostmsu 1y ago
LLMs don't think the way humans speak. LLMs process sequences of high-dimensional vectors.
- catlifeonmars 1y ago
  Yeah that was very hand wavy on my part. What I meant to say is that LLMs encode the relationships between words. The idea being that the relationship between words is a good enough representation of the relationship between the things that the words represent. I am conjecturing 1. that solely relying on written artifacts by produced by humans has some upper bound on the amount of knowledge that can be represented. 2. that language is an inefficient representation of human knowledge. It’s redundant and contains inaccuracies. Using written artifacts is not the shortest path to learning. For example, take mathematics. It’s not sufficient to read a ton of math literature to effectively learn math. There’s a component of discovery that comes from e.g attempting to write a proof that can’t be replaced by reading all of the proofs that already exist. Anyway I would take all this with a giant grain of salt.