4 ms·

I would agree with this article that every independent solution today does not have the slightest chance to be iteratively improved to some kind of real intelli

by blixt 12y ago

I would agree with this article that every independent solution today does not have the slightest chance to be iteratively improved to some kind of real intelligence. Even the "generic" game playing AI is very limited outside the scope of a pixel buffer and some digital output signals. However, I don't understand how the arguments correlate to "there is no need to worry about AI". The real worry should come from the fact that there are now many, many more people looking at the problem of AI than before, and it's a competition that now has serious money behind it. The article mentioned the infinite monkey theorem as a counterargument, but ironically that is exactly how I think we will stumble upon generic intelligence. The more people that work on it and have the confidence, belief, and money to actually try out random things, the more likely it is that someone out there will discover the step change that will, in a day, take AI from deep prediction algorithms to eerily deliberate behavior. Even if no one manages to shortcut our way to generic intelligence, we sure as hell will brute force it. While we're extremely early in the world of simulating organic brains, they exist. People have constructed virtual organic bodies controlled by virtual electric currents from virtual neurons in virtual brains. It's happening today, and as capacity, domain knowledge, and most importantly awareness increases, more and more people will work on the problem and bigger and bigger brains will be simulated. I really don't see how we can question whether we will eventually reach human level intelligence running on computers. The only way I see generic machine intelligence not happening is by making people believe it is so impossible that no one ever tries to do it. And maybe that was the purpose of this article.

blixt 12y ago
Here's one project simulating the C. elegans (earth worm) in a virtual environment. If they (or any other project out there working on similar problems) can prove that the simplest organic life form can be simulated in a computer, I think that's a big initial step towards brute forced brain simulation. http://www.openworm.org/ http://www.openworm.org/
eli_gottlieb 12y ago
>I would agree with this article that every independent solution today does not have the slightest chance to be iteratively improved to some kind of real intelligence. Even the "generic" game playing AI is very limited outside the scope of a pixel buffer and some digital output signals. Why do people who are laypersons to machine learning continue to insist, despite what those in the field say, that we are learning nothing about the principles of general-domain learning from current developments? I think DeepMind is making genuine discoveries: they're certainly able to build things nobody was able to build before.
- blixt 12y ago
  Steps are certainly being made, but I don't think anyone in the field said any of the technology that exists today can be iterated upon to get even close to the kind of AI that would eventually become superintelligent. But yes, I do believe that with the amount of people working on these problems, we may very well "hit gold" and come up with something that does have the potential to become superintelligent, before we get there through brute-forcing means.
lsz9 12y ago
No doubt increased funding and interests will increase the odds of stumbling upon "cheap" strong AI - a faster-than-brute-force solution. But consider the only strong intelligence we know: say intelligence only relied on the brain (which might well not be the case). This organ consumes a large fraction of the energy available to the individual. I'm not saying evolution produces optimal solutions but I guess its fair to say that a vastly superior algorithm would have had a good chance of concurring the world by now. So imitating the biological processes of the brain in silicon would be rather costly no matter the gain. And that would in the end (at best) be a one-in-seven-billion individual ie. no magic powers. I guess funding will flow towards practical systems that augument some consumer who will in the end provide a return on the investment. Just saying we are not short on intelligence and its not likely to be cheap to run massive scale super-AI in silicon.
- blixt 12y ago
  This is all very vague theorizing of course, but I believe that once we reach a level of artificial intelligence that resembles biological intelligence, scaling it will be quite feasible on a silicon platform. You've also removed the element of maintaining a body (exercise, eating, hygiene) as well as expanded potential interfaces (direct connection to the internet) so that even a 1:1 silicon brain would presumably be more efficient. The next thing you can do is optimize the time step element, so that for every 1 second of thinking in a silicon brain, it has performed the equivalent of 10 seconds of thinking in a human brain. At that point, you've surpassed human intelligence. It's also safe to assume that if we do reach this point, we've learned a lot more about how biological intelligence works, and may be able to use to our advantage the beneficial intelligence properties of savants. The really big downside with all these approaches is that the intelligence will be built from a blueprint that includes emotions, and we may do something that is very morally wrong towards the intelligence that we created.

by blixt 12y ago

blixt 12y ago

Here's one project simulating the C. elegans (earth worm) in a virtual environment. If they (or any other project out there working on similar problems) can prove that the simplest organic life form can be simulated in a computer, I think that's a big initial step towards brute forced brain simulation. http://www.openworm.org/ http://www.openworm.org/

eli_gottlieb 12y ago

>I would agree with this article that every independent solution today does not have the slightest chance to be iteratively improved to some kind of real intelligence. Even the "generic" game playing AI is very limited outside the scope of a pixel buffer and some digital output signals. Why do people who are laypersons to machine learning continue to insist, despite what those in the field say, that we are learning nothing about the principles of general-domain learning from current developments? I think DeepMind is making genuine discoveries: they're certainly able to build things nobody was able to build before.

blixt 12y ago
Steps are certainly being made, but I don't think anyone in the field said any of the technology that exists today can be iterated upon to get even close to the kind of AI that would eventually become superintelligent. But yes, I do believe that with the amount of people working on these problems, we may very well "hit gold" and come up with something that does have the potential to become superintelligent, before we get there through brute-forcing means.

lsz9 12y ago

No doubt increased funding and interests will increase the odds of stumbling upon "cheap" strong AI - a faster-than-brute-force solution. But consider the only strong intelligence we know: say intelligence only relied on the brain (which might well not be the case). This organ consumes a large fraction of the energy available to the individual. I'm not saying evolution produces optimal solutions but I guess its fair to say that a vastly superior algorithm would have had a good chance of concurring the world by now. So imitating the biological processes of the brain in silicon would be rather costly no matter the gain. And that would in the end (at best) be a one-in-seven-billion individual ie. no magic powers. I guess funding will flow towards practical systems that augument some consumer who will in the end provide a return on the investment. Just saying we are not short on intelligence and its not likely to be cheap to run massive scale super-AI in silicon.

blixt 12y ago
This is all very vague theorizing of course, but I believe that once we reach a level of artificial intelligence that resembles biological intelligence, scaling it will be quite feasible on a silicon platform. You've also removed the element of maintaining a body (exercise, eating, hygiene) as well as expanded potential interfaces (direct connection to the internet) so that even a 1:1 silicon brain would presumably be more efficient. The next thing you can do is optimize the time step element, so that for every 1 second of thinking in a silicon brain, it has performed the equivalent of 10 seconds of thinking in a human brain. At that point, you've surpassed human intelligence. It's also safe to assume that if we do reach this point, we've learned a lot more about how biological intelligence works, and may be able to use to our advantage the beneficial intelligence properties of savants. The really big downside with all these approaches is that the intelligence will be built from a blueprint that includes emotions, and we may do something that is very morally wrong towards the intelligence that we created.