4 ms·

No, the current limit is not physical, it's that nobody has any idea how general intelligence works. You do not, in fact, get general intelligence by accident

by rspeer 10y ago

No, the current limit is not physical, it's that nobody has any idea how general intelligence works. You do not, in fact, get general intelligence by accident by throwing a lot of connections in one place, just like you do not get a human just by throwing a lot of organic molecules and water in one place.

phailhaus 10y ago
> just like you do not get a human just by throwing a lot of organic molecules and water in one place. Well, not unless you have a couple billion years to sit around.
- aetherson 10y ago
  It's worse than that! It's a couple of billion years, and a planet's worth of organic molecules and water. And, there's a least some evidence that it's even worse than that -- intelligence does not appear to be common in the universe. So it might well be a couple of billion years * a million planets worth of organic molecules and water (or a hundred million planets. Or a billion planets).
mfav 10y ago
As the other commenter noted, "letting a bunch of molecules sit around" was precisely where we got intelligence from in the first place. So it is possible that we reach AI just by randomly permuting connections and weights. Of course it's more likely we intelligently set (or "evolve") these connections and weights, but this allows us to set an upper bound on computation/time needed.
- rtx 10y ago
  The probality is pretty low.
- gls2ro 10y ago
  > As the other commenter noted, "letting a bunch of molecules sit around" was precisely where we got intelligence from in the first place. I don't think this was the case. Yes there is evolution but it is not random. Actually most of the molecules sitting around did not evolve to intelligence. In case our evolution we had natural selection. In case of AI we have artificial selection (selection made by humans) and even if we consider ourselves smart enough to do this we cannot prove that we are able to make it happen (choosing the correct AIs/algorithms to survive) until it happens. Maybe I cannot express this clear enough but the advantage natural evolution has over artificial evolution is the huge number of "experiments" - meaning it had time enough to do a lot of small changes until something worked.
  - gnaritas 10y ago
    > Maybe I cannot express this clear enough but the advantage natural evolution has over artificial evolution is the huge number of "experiments" - meaning it had time enough to do a lot of small changes until something worked. I think you have that backwards; natural evolution is absurdly slow because it takes a very long time to cycle through generations of animals whereas genetic programming on a computer to evolve algorithms can happen billions of times a day because computers are much faster at cycling through possibilities. > meaning it had time enough to do a lot of small changes until something worked. Computers can do it faster.
    - gls2ro 10y ago
      Yes, now you got me thinking more about my concept of how I see the difference between evolution by natural selection and evolution by artificial selection. And I agree with you that AI can be much faster. I still think the artificial selection can be influence by us - humans - so we might add flows in the sistem from the beginning. Of course AI can learn to identify them maybe. But maybe not. Like in the case when looking from inside a system one cannot see how the system really is so it cannot fix it. Of course what I say are just some hypothesis, nothing proven and I think they cannot yet be falsifiable.
DiThi 10y ago
As nature itself has shown, it's not necessary to understand it to create it. That's part of what makes it scary: It will probably happen and we can't predict the outcome.
- mcguire 10y ago
  That describes literally everything.
- eli_gottlieb 10y ago
  >As nature itself has shown, it's not necessary to understand it to create it. Unless intelligence itself conforms to natural principles, unless it "cuts with the grain" of nature's preexisting laws. Which, frankly, it does. Information theory and thermodynamics are a thing.
eli_gottlieb 10y ago
>You do not, in fact, get general intelligence by accident by throwing a lot of connections in one place, just like you do not get a human just by throwing a lot of organic molecules and water in one place. Don't tell that to the deep learning cult! They'll have to think about how it all works!
- rspeer 10y ago
  I think deep learning is both useful and overhyped. If we got in the habit of calling it something like "large-scale parameter fitting by gradient descent", we could talk about it more sensibly. I have not met any actual deep learning researchers who think they are creating AGI. I think that it's non-experts who write about deep learning research who think that deep learning is creating AGI.
  - eli_gottlieb 9y ago
    Well, I dunno. Yann Lecun and Yoshua Bengio have both given presentations on moving from existing perception tasks towards human-level AI, focusing on how to do so with neural nets whose parameters are fitted via gradient descent. And I'm not even sure I would call it "parameter fitting". I'd call it, "continuous circuit searching via gradient descent", because that's all you're doing: searching for a nice analog circuit for your task within a large, continuous space of such circuits.

by rspeer 10y ago

phailhaus 10y ago

> just like you do not get a human just by throwing a lot of organic molecules and water in one place. Well, not unless you have a couple billion years to sit around.

aetherson 10y ago
It's worse than that! It's a couple of billion years, and a planet's worth of organic molecules and water. And, there's a least some evidence that it's even worse than that -- intelligence does not appear to be common in the universe. So it might well be a couple of billion years * a million planets worth of organic molecules and water (or a hundred million planets. Or a billion planets).

mfav 10y ago

As the other commenter noted, "letting a bunch of molecules sit around" was precisely where we got intelligence from in the first place. So it is possible that we reach AI just by randomly permuting connections and weights. Of course it's more likely we intelligently set (or "evolve") these connections and weights, but this allows us to set an upper bound on computation/time needed.

rtx 10y ago
The probality is pretty low.
gls2ro 10y ago
> As the other commenter noted, "letting a bunch of molecules sit around" was precisely where we got intelligence from in the first place. I don't think this was the case. Yes there is evolution but it is not random. Actually most of the molecules sitting around did not evolve to intelligence. In case our evolution we had natural selection. In case of AI we have artificial selection (selection made by humans) and even if we consider ourselves smart enough to do this we cannot prove that we are able to make it happen (choosing the correct AIs/algorithms to survive) until it happens. Maybe I cannot express this clear enough but the advantage natural evolution has over artificial evolution is the huge number of "experiments" - meaning it had time enough to do a lot of small changes until something worked.
- gnaritas 10y ago
  > Maybe I cannot express this clear enough but the advantage natural evolution has over artificial evolution is the huge number of "experiments" - meaning it had time enough to do a lot of small changes until something worked. I think you have that backwards; natural evolution is absurdly slow because it takes a very long time to cycle through generations of animals whereas genetic programming on a computer to evolve algorithms can happen billions of times a day because computers are much faster at cycling through possibilities. > meaning it had time enough to do a lot of small changes until something worked. Computers can do it faster.
  - gls2ro 10y ago
    Yes, now you got me thinking more about my concept of how I see the difference between evolution by natural selection and evolution by artificial selection. And I agree with you that AI can be much faster. I still think the artificial selection can be influence by us - humans - so we might add flows in the sistem from the beginning. Of course AI can learn to identify them maybe. But maybe not. Like in the case when looking from inside a system one cannot see how the system really is so it cannot fix it. Of course what I say are just some hypothesis, nothing proven and I think they cannot yet be falsifiable.

DiThi 10y ago

As nature itself has shown, it's not necessary to understand it to create it. That's part of what makes it scary: It will probably happen and we can't predict the outcome.

mcguire 10y ago
That describes literally everything.
eli_gottlieb 10y ago
>As nature itself has shown, it's not necessary to understand it to create it. Unless intelligence itself conforms to natural principles, unless it "cuts with the grain" of nature's preexisting laws. Which, frankly, it does. Information theory and thermodynamics are a thing.

eli_gottlieb 10y ago

>You do not, in fact, get general intelligence by accident by throwing a lot of connections in one place, just like you do not get a human just by throwing a lot of organic molecules and water in one place. Don't tell that to the deep learning cult! They'll have to think about how it all works!

rspeer 10y ago
I think deep learning is both useful and overhyped. If we got in the habit of calling it something like "large-scale parameter fitting by gradient descent", we could talk about it more sensibly. I have not met any actual deep learning researchers who think they are creating AGI. I think that it's non-experts who write about deep learning research who think that deep learning is creating AGI.
- eli_gottlieb 9y ago
  Well, I dunno. Yann Lecun and Yoshua Bengio have both given presentations on moving from existing perception tasks towards human-level AI, focusing on how to do so with neural nets whose parameters are fitted via gradient descent. And I'm not even sure I would call it "parameter fitting". I'd call it, "continuous circuit searching via gradient descent", because that's all you're doing: searching for a nice analog circuit for your task within a large, continuous space of such circuits.