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I'm only about... 50% serious when I say this. But all of these huge tech companies getting into serious AI and learning really makes me worry that Singularity

I'm only about... 50% serious when I say this. But all of these huge tech companies getting into serious AI and learning really makes me worry that Singularity is coming way sooner then I would have hoped. Like in the next 10 years.

rimantas 12y ago
Our brains are so far away from understanding themselves that those 10 years won't bring much, let alone the singularity.
msutherl 12y ago
I honestly don't see any evidence to suggest this.
shock-value 12y ago
Most of the recent advances don't really constitute what you are probably thinking of as "serious" AI. What's happening now is mostly just scientists putting newly available massively parallel processing units (GPUs etc.) to work at sort of "brute forcing" the problem of AI. You could technically say it's a step above brute-forcing in that, after randomly assigning neural weights, gradient descent and other tricks are used to more quickly settle into good solutions. But the science is simply nowhere near the level of the human brain, and the current state of the art is still only "proficient" at relatively simple pattern matching, rather than coming up with decisions that actually influence the state of the world that it is perceiving. The deep architectural insights that will likely be needed before computers can approach the level of human intelligence still haven't been made yet, it seems to me based on what I know of the current research.
- nl 12y ago
  Yeah, this is almost completely wrong - or at least outdated thinking. While it's entirely likely that better AI algorithms will become available, the progress being made by "brute forcing" problems using lots of data and lots of computing power is much more than was expected 10 years ago. For example, Facebook's facial recognition software now correctly recognizes faces 97.25% of the time. Humans do 97.53%[1]. I'd encourage you to read the Norvig et. al paper: "The Unreasonable Effectiveness of Data" [1] http://www.technologyreview.com/news/525586/facebook-creates-software-that-matches-faces-almost-as-well-as-you-do/ http://www.technologyreview.com/news/525586/facebook-creates... [2] https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf https://static.googleusercontent.com/media/research.google.c...
  - paganel 12y ago
    > For example, Facebook's facial recognition software now correctly recognizes faces 97.25% of the time. Humans do 97.53%[1]. One could say that is only data, nothing "intelligent" about pattern-matching it. But I'm biased, I'm a non-believer when it comes to reaching the singularity, as in I don't think we will ever be able to build something that will understand jokes, sexual innuendo or who/which will experience the Madeleine effect (http://en.wikipedia.org/wiki/Madeleine_%28cake%29#Literary_reference http://en.wikipedia.org/wiki/Madeleine_%28cake%29#Literary_r...)
    - skj 12y ago
      The difference between "artificial intelligence" and "automated problem solving" is how much the algorithm designers understand what's going on. Computers will certainly be able to understand jokes or innuendo. At least as well as people do, anyway. As far as the Madeleine effect goes, I'm not sure why you consider that intelligence?
      - paganel 12y ago
        > Computers will certainly be able to understand jokes or innuendo. At least as well as people do, anyway. Serious question, are we close to anywhere on that? I last looked at AI-related stuff around 10 years ago, when "sentiment analysis" as it was then called was only capable of approximating what "good press" and "bad press" meant. > As far as the Madeleine effect goes, I'm not sure why you consider that intelligence? I'm making a generalization in thinking that "intelligence" ultimately means "human intelligence", and I'm also assuming (probably wrong, there's no exact science for it) that things like the "Madeleine effect" sit at the core of us being humans, and the third (and last generalization) in thinking that if you're not experiencing things like the "Madeleine effect" you're not really human-like, so you cannot really be "intelligent". Writers like Asimov and Arthur C. Clarke have written about this problem (what it means to be human when "robots" will come about) way better than I could ever dream of doing, but my favorite presentation of the potential issues when the Singularity will come around remains Stanislaw Lem's "The Cyberiad". Or we could continue focusing on technicalities only and call it a day.
giardini 12y ago
I'm reading "Life's Ratchet: How Molecular Machines Extract Order from Chaos" by Peter M. Hoffmann, and it pretty thoroughly disavowed me of the notion that we're anywhere near understanding how the brain works, which doesn't bode well for one approach to the Singularity. While the book isn't about AI per se, the complexity that it hints at in biological systems is (yet another) warning shot across the bow of my personal AI voyaging ship, telling me to avoid those waters (actually it's more like the Kraken from Pirates of the Caribbean). I've never espoused AI technology that attempted to emulate the physical brain, believing it too complex an approach. But taking another brief peek into the black box of living systems scared the crap out of me! I'm glad I didn't pursue biochemistry as a field of study so many years ago. My mind would be full up by now with little to show for it.
- sp332 12y ago
  AI is artificial, it doesn't have to be a copy of a human brain.
mbq 12y ago
They are not; this is machine learning not AGI, it is not even Turing complete.
TheEzEzz 12y ago
You're getting downvoted with a lot of rebutting comments, so I'll jump in to your defense. This is obviously not true AI, but powerful image recognition is one of the holy grails of the original AI quest. Reaching human level (and likely above-human level soon) image recognition capabilities will not unleash the singularity, but I don't think anyone knows how many steps lie between achieving this sub-step and achieving the final goal. Certainly visual recognition is a huge component of mammalian brains (both in terms of brain volume and in terms of behavior). Even more worrying, Microsoft claims that this same technology can be applied to sound recognition, and it doesn't seem unlikely that it could cover all senses, given proper inputs. If this all holds up and gets polished, this effectively marks the first major step in human-like AI. Again, how many steps remain no one knows, but we should absolutely take notice of results like this and seek better arguments one way or the other. Saying "nuh-uh" won't change the way this research unfolds, and does us no favors for preparing for it as it matures.
- thefreeman 12y ago
  Thanks. I probably should not have referenced Singularity, and should phrased my original sentiment better. I understand that we are nowhere near building AI's that can model the human brain and thought process accurately. But I do think that there will be a point, far before that, at which point machines / ai's will have the ability to improve themselves outside of the algorithms programmed into them. At that point, I think there is definitely the possibility for an exponentially growing increase in their sophistication, far far faster then humans have the ability to learn and develop. This is due to the fact that AI's never have to rest, never get tired or forget things, and could potentially have the entire world of networked devices and information at its disposal. Anyway, I pretty much accepted that I was probably going to tank some down votes when I made my original post. But I achieved my main goal of seeing some interesting points / discussion about the feasibility of such a claim.

rimantas 12y ago

Our brains are so far away from understanding themselves that those 10 years won't bring much, let alone the singularity.

msutherl 12y ago

I honestly don't see any evidence to suggest this.

shock-value 12y ago

Most of the recent advances don't really constitute what you are probably thinking of as "serious" AI. What's happening now is mostly just scientists putting newly available massively parallel processing units (GPUs etc.) to work at sort of "brute forcing" the problem of AI. You could technically say it's a step above brute-forcing in that, after randomly assigning neural weights, gradient descent and other tricks are used to more quickly settle into good solutions. But the science is simply nowhere near the level of the human brain, and the current state of the art is still only "proficient" at relatively simple pattern matching, rather than coming up with decisions that actually influence the state of the world that it is perceiving. The deep architectural insights that will likely be needed before computers can approach the level of human intelligence still haven't been made yet, it seems to me based on what I know of the current research.

nl 12y ago
Yeah, this is almost completely wrong - or at least outdated thinking. While it's entirely likely that better AI algorithms will become available, the progress being made by "brute forcing" problems using lots of data and lots of computing power is much more than was expected 10 years ago. For example, Facebook's facial recognition software now correctly recognizes faces 97.25% of the time. Humans do 97.53%[1]. I'd encourage you to read the Norvig et. al paper: "The Unreasonable Effectiveness of Data" [1] http://www.technologyreview.com/news/525586/facebook-creates-software-that-matches-faces-almost-as-well-as-you-do/ http://www.technologyreview.com/news/525586/facebook-creates... [2] https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf https://static.googleusercontent.com/media/research.google.c...
- paganel 12y ago
  > For example, Facebook's facial recognition software now correctly recognizes faces 97.25% of the time. Humans do 97.53%[1]. One could say that is only data, nothing "intelligent" about pattern-matching it. But I'm biased, I'm a non-believer when it comes to reaching the singularity, as in I don't think we will ever be able to build something that will understand jokes, sexual innuendo or who/which will experience the Madeleine effect (http://en.wikipedia.org/wiki/Madeleine_%28cake%29#Literary_reference http://en.wikipedia.org/wiki/Madeleine_%28cake%29#Literary_r...)
  - skj 12y ago
    The difference between "artificial intelligence" and "automated problem solving" is how much the algorithm designers understand what's going on. Computers will certainly be able to understand jokes or innuendo. At least as well as people do, anyway. As far as the Madeleine effect goes, I'm not sure why you consider that intelligence?
    - paganel 12y ago
      > Computers will certainly be able to understand jokes or innuendo. At least as well as people do, anyway. Serious question, are we close to anywhere on that? I last looked at AI-related stuff around 10 years ago, when "sentiment analysis" as it was then called was only capable of approximating what "good press" and "bad press" meant. > As far as the Madeleine effect goes, I'm not sure why you consider that intelligence? I'm making a generalization in thinking that "intelligence" ultimately means "human intelligence", and I'm also assuming (probably wrong, there's no exact science for it) that things like the "Madeleine effect" sit at the core of us being humans, and the third (and last generalization) in thinking that if you're not experiencing things like the "Madeleine effect" you're not really human-like, so you cannot really be "intelligent". Writers like Asimov and Arthur C. Clarke have written about this problem (what it means to be human when "robots" will come about) way better than I could ever dream of doing, but my favorite presentation of the potential issues when the Singularity will come around remains Stanislaw Lem's "The Cyberiad". Or we could continue focusing on technicalities only and call it a day.

giardini 12y ago

I'm reading "Life's Ratchet: How Molecular Machines Extract Order from Chaos" by Peter M. Hoffmann, and it pretty thoroughly disavowed me of the notion that we're anywhere near understanding how the brain works, which doesn't bode well for one approach to the Singularity. While the book isn't about AI per se, the complexity that it hints at in biological systems is (yet another) warning shot across the bow of my personal AI voyaging ship, telling me to avoid those waters (actually it's more like the Kraken from Pirates of the Caribbean). I've never espoused AI technology that attempted to emulate the physical brain, believing it too complex an approach. But taking another brief peek into the black box of living systems scared the crap out of me! I'm glad I didn't pursue biochemistry as a field of study so many years ago. My mind would be full up by now with little to show for it.

sp332 12y ago
AI is artificial, it doesn't have to be a copy of a human brain.

mbq 12y ago

They are not; this is machine learning not AGI, it is not even Turing complete.

TheEzEzz 12y ago

You're getting downvoted with a lot of rebutting comments, so I'll jump in to your defense. This is obviously not true AI, but powerful image recognition is one of the holy grails of the original AI quest. Reaching human level (and likely above-human level soon) image recognition capabilities will not unleash the singularity, but I don't think anyone knows how many steps lie between achieving this sub-step and achieving the final goal. Certainly visual recognition is a huge component of mammalian brains (both in terms of brain volume and in terms of behavior). Even more worrying, Microsoft claims that this same technology can be applied to sound recognition, and it doesn't seem unlikely that it could cover all senses, given proper inputs. If this all holds up and gets polished, this effectively marks the first major step in human-like AI. Again, how many steps remain no one knows, but we should absolutely take notice of results like this and seek better arguments one way or the other. Saying "nuh-uh" won't change the way this research unfolds, and does us no favors for preparing for it as it matures.

thefreeman 12y ago
Thanks. I probably should not have referenced Singularity, and should phrased my original sentiment better. I understand that we are nowhere near building AI's that can model the human brain and thought process accurately. But I do think that there will be a point, far before that, at which point machines / ai's will have the ability to improve themselves outside of the algorithms programmed into them. At that point, I think there is definitely the possibility for an exponentially growing increase in their sophistication, far far faster then humans have the ability to learn and develop. This is due to the fact that AI's never have to rest, never get tired or forget things, and could potentially have the entire world of networked devices and information at its disposal. Anyway, I pretty much accepted that I was probably going to tank some down votes when I made my original post. But I achieved my main goal of seeing some interesting points / discussion about the feasibility of such a claim.