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> There will never be enough computing power to create AGI using machine learning that can do the same [as the human brain], because we’d run out of natural resources long before we'd even get close I don’t understand how people can so confidently make claims like this. We might underestimate how difficult AGI is, but come on?!
After all, earth could be understood as solar powered super computer, that took a couple of million years to produce humanity.
Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
Sure, maybe your cousin Throckmorton is dumb but that's besides the point.
That said, I see no reason human level cognition is impossible. We're not magic. We're machines that follow the laws of physics. ML systems may be far from capturing what goes on in these computers, but that doesn't mean magic exists.
[0] If it walks like a duck, quacks like a duck, and swims like a duck, and looks like a duck it's probably a duck. But probably doesn't mean it isn't a well made animatronic. We have those too and they'll convince many humans they are ducks. But that doesn't change what's inside. The subtly matters.
Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
> There will never be enough computing power to create AGI using machine learning that can do the same [as the human brain], because we’d run out of natural resources long before we'd even get close I don’t understand how people can so confidently make claims like this. We might underestimate how difficult AGI is, but come on?!
Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
Are you talking about the press release that the story on HN currently links to, or the paper that press release is about? The paper (I'm not vouching for it; I just skimmed it) appears to reduce AGI to a theoretical computational model, and then supplies a proof that it's not solvable in polynomial time.
If it's not solvable in polynomial time, how did nature solve it in a couple of million years?
AGI is about as far away as it was two decades ago. Language models are merely a dent, and probably will be the precursor to a natural language interface to the thing.
Also I would think most people would consider AGI science fiction in 2004 - now we consider it a technical possibility which demonstrates a huge change.
I'm not an AGI optimist myself, but I'd be very surprised if a time traveller told me that mankind won't have AGI by, say, 2250.