4 ms·

Vernor Vinge coined the term, and he was a computer scientist (though more famous as a science fiction writer, a profession which I guess TBF makes money from v

Vernor Vinge coined the term, and he was a computer scientist (though more famous as a science fiction writer, a profession which I guess TBF makes money from visions...). An exponential looks the same whereever you are on it, so arguably we are in the singularity now, and have been for quite some time... "Singularity" is a terrible term for an exponential. It's meant to convey that we can't predict what's next... which has always been the case. The problem of predicting an exponentialling expanding search space of arbitrary conplexity is that it gets big fast. It also means each little 'bit' of information allows you to see a little further, sometimes revealing things you could never have imagined (because you couldn't see that far before).

jasonwatkinspdx 5y ago
But the above comment's entire point is there's zero reason for us to assume we're on an unbounded exponential vs a sigmoid.
- unoti 5y ago
  > But the above comment's entire point is there's zero reason for us to assume we're on an unbounded exponential vs a sigmoid. Something about that which is discussed at length in "The Singularity is Near" is the idea that the unbounded exponential is actually comprised of many smaller sigmoids. Technological progress looks like sigmoids locally-- for example you have the industrial revolution, the cotton gin, steam power, etc. all looking like a sigmoids of the exploitation of automation. At some point you get all those benefits and progress starts to level off like a sigmoids. Then another sigmoid comes along when you get electricity, and a new sigmoid starts. Then later we get computers, and that starts to level off, then networking comes along and we get a new sigmoid. Then deep learning... The AI winters were the levelling off of sigmoids by one way of thinking. And maybe we're tapering off on our current round of what we can do with existing architectures.
  - ImaCake 5y ago
    I’m no expert, just a humble biostatistics student, generally when you sum together a lot of random variables following a specific distribution you end up with basically the same distribution (scaled by the N random vars). So a lot of sigmoids put together (e.g. covid spread) will still eventually be a sigmoid. Biology seems to run on sigmoids that at first look like exponentials.
    - hyperpallium2 5y ago
      These ones aren't random, because they build on previous ones. In nature, you get a sigmoid because you run out of resource, I think? True at any scale. Pragmatic people point will out one limit on GI is all the accessible matter in the universe. But, theoretically, I think, there is no limit on complexity. BTW you might like this paper on the exponential growth in complexity of life on earth, over long timescales. https://www.technologyreview.com/2013/04/15/113741/moores-law-and-the-origin-of-life/ https://www.technologyreview.com/2013/04/15/113741/moores-la...
    - bloak 5y ago
      > generally when you sum together a lot of random variables following a specific distribution you end up with basically the same distribution (scaled by the N random vars). So a lot of sigmoids put together (e.g. covid spread) will still eventually be a sigmoid. I haven't studied statistics very much, but I'm fairly sure the https://en.wikipedia.org/wiki/Central_limit_theorem https://en.wikipedia.org/wiki/Central_limit_theorem says something a bit different from that!
      - ImaCake 5y ago
        Woops yes. If you sum them together you do get a normal dist. Come to think of it a cumulative normal distribution is a sigmoid.
  - jasonwatkinspdx 5y ago
    That's the same argument. There's nothing that assures us automation itself is an unbounded exponential.
- zardo 5y ago
  The point of the singularity isn't that technological growth will accelerate to cause some inevitable future, but that the rate of change will get so high, that 'minor' differences between how two technologies progress would lead to drastically different settings for your science fiction stories (which was Vinge's focus).
nonameiguess 5y ago
Singularity in the sense of a black hole refers to where spacetime becomes a single one-dimensional point. As far as I understand the usage in futurism, it is supposed to be similar, not in that growth is exponential, but asymptotic. The slope becomes infinite when progress is plotted against time, so all of time left to come effectively compresses to a single "state of technology" value. All possible future progress happens instantaneously. This is, of course, not possible, but it's supposed to be an approximation. All progress is not literally instant, but in the "foom" or "hard takeoff" recursive self-improvement scenarios, developments that might have taken millennia in the past now happen in microseconds because the controlling force is just that much smarter than all of the collective powers of human science and engineering. To a human observer, it may as well be instantaneous. To be clear, I still think this is ridiculous and am not endorsing the view, just explaining what I understand the usage to mean.
- gnramires 5y ago
  Indeed, Rich Sutton argued that we already have been through an exponential phase of self-improvement, we have been using computers to build better computers for decades, and have been using technology to improve our learning and cognition for a long time. Piece this together with: 'Brain efficiency: Much more than you wanted to know' [1] which shows how our brains are incredibly efficient (near theoretical limits) at what they do, it's hard to think a bona fide intelligence singularity is anywhere likely. To quote Feynman, 'There is no miracle people'[2], and analogously 'There are no miracle beings' -- intelligence is built out of systems, and learning, and inference. There's a possibility that the skills relevant to AI success are vastly different from our natural skills, such that although the human brain is highly efficient, it's efficient at the wrong things. That's clearly true in a few ways: we are not so good at arithmetic for example, a small CPU can literally be millions-billions times faster than a human at that. (that's addressed a little in the article as well) I wonder if AI could indeed be vastly better at something like computer programming, mathematics than we are. But there's no singularity (at most a Moore-like law will continue until AI intelligence saturates at a different skillset than our own). [1] https://www.lesswrong.com/posts/xwBuoE9p8GE7RAuhd/brain-efficiency-much-more-than-you-wanted-to-know https://www.lesswrong.com/posts/xwBuoE9p8GE7RAuhd/brain-effi... [2] https://www.youtube.com/watch?v=IIDLcaQVMqw https://www.youtube.com/watch?v=IIDLcaQVMqw
api 5y ago
> An exponential looks the same whereever you are on it, so arguably we are in the singularity now, and have been for quite some time... By that view we've been in the singularity since the first cell self-reproduced on primordial Earth. Of course maybe that's true. As you say an exponential looks the same no matter where you are on it.

jasonwatkinspdx 5y ago

But the above comment's entire point is there's zero reason for us to assume we're on an unbounded exponential vs a sigmoid.

unoti 5y ago
> But the above comment's entire point is there's zero reason for us to assume we're on an unbounded exponential vs a sigmoid. Something about that which is discussed at length in "The Singularity is Near" is the idea that the unbounded exponential is actually comprised of many smaller sigmoids. Technological progress looks like sigmoids locally-- for example you have the industrial revolution, the cotton gin, steam power, etc. all looking like a sigmoids of the exploitation of automation. At some point you get all those benefits and progress starts to level off like a sigmoids. Then another sigmoid comes along when you get electricity, and a new sigmoid starts. Then later we get computers, and that starts to level off, then networking comes along and we get a new sigmoid. Then deep learning... The AI winters were the levelling off of sigmoids by one way of thinking. And maybe we're tapering off on our current round of what we can do with existing architectures.
- ImaCake 5y ago
  I’m no expert, just a humble biostatistics student, generally when you sum together a lot of random variables following a specific distribution you end up with basically the same distribution (scaled by the N random vars). So a lot of sigmoids put together (e.g. covid spread) will still eventually be a sigmoid. Biology seems to run on sigmoids that at first look like exponentials.
  - hyperpallium2 5y ago
    These ones aren't random, because they build on previous ones. In nature, you get a sigmoid because you run out of resource, I think? True at any scale. Pragmatic people point will out one limit on GI is all the accessible matter in the universe. But, theoretically, I think, there is no limit on complexity. BTW you might like this paper on the exponential growth in complexity of life on earth, over long timescales. https://www.technologyreview.com/2013/04/15/113741/moores-law-and-the-origin-of-life/ https://www.technologyreview.com/2013/04/15/113741/moores-la...
  - bloak 5y ago
    > generally when you sum together a lot of random variables following a specific distribution you end up with basically the same distribution (scaled by the N random vars). So a lot of sigmoids put together (e.g. covid spread) will still eventually be a sigmoid. I haven't studied statistics very much, but I'm fairly sure the https://en.wikipedia.org/wiki/Central_limit_theorem https://en.wikipedia.org/wiki/Central_limit_theorem says something a bit different from that!
    - ImaCake 5y ago
      Woops yes. If you sum them together you do get a normal dist. Come to think of it a cumulative normal distribution is a sigmoid.
- jasonwatkinspdx 5y ago
  That's the same argument. There's nothing that assures us automation itself is an unbounded exponential.
zardo 5y ago
The point of the singularity isn't that technological growth will accelerate to cause some inevitable future, but that the rate of change will get so high, that 'minor' differences between how two technologies progress would lead to drastically different settings for your science fiction stories (which was Vinge's focus).

nonameiguess 5y ago

Singularity in the sense of a black hole refers to where spacetime becomes a single one-dimensional point. As far as I understand the usage in futurism, it is supposed to be similar, not in that growth is exponential, but asymptotic. The slope becomes infinite when progress is plotted against time, so all of time left to come effectively compresses to a single "state of technology" value. All possible future progress happens instantaneously. This is, of course, not possible, but it's supposed to be an approximation. All progress is not literally instant, but in the "foom" or "hard takeoff" recursive self-improvement scenarios, developments that might have taken millennia in the past now happen in microseconds because the controlling force is just that much smarter than all of the collective powers of human science and engineering. To a human observer, it may as well be instantaneous. To be clear, I still think this is ridiculous and am not endorsing the view, just explaining what I understand the usage to mean.

gnramires 5y ago
Indeed, Rich Sutton argued that we already have been through an exponential phase of self-improvement, we have been using computers to build better computers for decades, and have been using technology to improve our learning and cognition for a long time. Piece this together with: 'Brain efficiency: Much more than you wanted to know' [1] which shows how our brains are incredibly efficient (near theoretical limits) at what they do, it's hard to think a bona fide intelligence singularity is anywhere likely. To quote Feynman, 'There is no miracle people'[2], and analogously 'There are no miracle beings' -- intelligence is built out of systems, and learning, and inference. There's a possibility that the skills relevant to AI success are vastly different from our natural skills, such that although the human brain is highly efficient, it's efficient at the wrong things. That's clearly true in a few ways: we are not so good at arithmetic for example, a small CPU can literally be millions-billions times faster than a human at that. (that's addressed a little in the article as well) I wonder if AI could indeed be vastly better at something like computer programming, mathematics than we are. But there's no singularity (at most a Moore-like law will continue until AI intelligence saturates at a different skillset than our own). [1] https://www.lesswrong.com/posts/xwBuoE9p8GE7RAuhd/brain-efficiency-much-more-than-you-wanted-to-know https://www.lesswrong.com/posts/xwBuoE9p8GE7RAuhd/brain-effi... [2] https://www.youtube.com/watch?v=IIDLcaQVMqw https://www.youtube.com/watch?v=IIDLcaQVMqw

api 5y ago

> An exponential looks the same whereever you are on it, so arguably we are in the singularity now, and have been for quite some time... By that view we've been in the singularity since the first cell self-reproduced on primordial Earth. Of course maybe that's true. As you say an exponential looks the same no matter where you are on it.