6 ms·

Stanford to host 100-year study on artificial intelligence

127 points by bra-ket 12y ago

bra-ket 12y ago
https://ai100.stanford.edu/ https://ai100.stanford.edu/
pcthrowaway 12y ago
Someone behind this study clearly has little faith in the imminence of AGI.
- chriswarbo 12y ago
  Well, it's been imminent since the summer of 1956 ( http://en.wikipedia.org/wiki/Dartmouth_Conferences http://en.wikipedia.org/wiki/Dartmouth_Conferences )
  - marcosdumay 12y ago
    Or, in other words, for about half the time those people are expecting no AI. Never mind the Moore's Law putting computers more capable than our brains less than 30 years away.
    - gweinberg 12y ago
      Nobody thinks Moore's law will last another 30 years.
      - dudus 12y ago
        Nobody thought it would last till here
        jblow 12y ago
        See this graph: http://www.extremetech.com/wp-content/uploads/2013/08/CPU-Scaling.jpg http://www.extremetech.com/wp-content/uploads/2013/08/CPU-Sc... The green line was the only one still going, and it plateaued about a year ago (you'd see that in a newer graph).
        dysfunction 12y ago
        The green line is the only one that Moore's law is about. Power consumption plateauing is a good thing, clock speed was never going to be the primary driver of performance increases long-term, and instruction-level parellelism (green line) is not a measure of performance-per-clock-cycle.
      - maaku 12y ago
        There's plenty of room on the bottom.
      - marcosdumay 12y ago
        Well, I think it's already dead for some good 3 or 4 years. It just didn't start stinking yet. But that's no reason to think that it'll take more than 100 years.
    - kmicklas 12y ago
      Moore's Law is about transistor density, not computing power, so no it won't. We could probably already build a computer more powerful than the human brain, it would just be huge (millions of cores or something). But that wouldn't help, because the real issue is that the Von Neumann architecture fundamentally prevents scaling the kinds of computations we want to do for neural networks. We need something more neuromorphic, although probably still discrete. (I'm guessing basically just a giant DSP integrated into memory on the same core.)
      - rl3 12y ago
        You may find these relevant: http://www.technologyreview.com/news/529691/ibm-chip-processes-data-similar-to-the-way-your-brain-does/ http://www.technologyreview.com/news/529691/ibm-chip-process... http://www.kurzweilai.net/ibm-simulates-530-billon-neurons-100-trillion-synapses-on-worlds-fastest-supercomputer http://www.kurzweilai.net/ibm-simulates-530-billon-neurons-1...
  - eli_gottlieb 12y ago
    Once upon a time, men said that AGI was imminent despite the fact that they had no computational model whatsoever of human cognition, and no limitary results other. Now, we have increasingly good computational models of human cognition, with abundant limitary results on both human and mechanical reasoning, but only madmen believe AGI will work in their lifetimes. Irony!
slg 12y ago
Somewhat cynical question, but is the 100 year aspect of this study anything beyond a marketing gimmick?
- rguzman 12y ago
  Even if the study doesn't live as long as its name states, a clear mission is useful because it guides people's decision making. A researcher in this should be optimizing her efforts for the 100 year timescale and not for the ~5 year one.
  - x1798DE 12y ago
    I don't see how that changes the individual researcher's incentive to make achieving short term, publishable discoveries a priority.
    - dangerlibrary 12y ago
      One concrete example would be data acquisition. Long term, large sample panel data sets take decades to produce, but are incredibly valuable if well designed / executed. If you are applying for funding as part of a 100 year study, you won't get continued funding unless you put in the effort up front to design the data acquisition correctly.
      - Someone 12y ago
        Another is what a project can offer your personnel. A four-year project will almost solely have temporary jobs. A hundred-year project will be able to offer more permanent assignments. That creates less 'publish or perish' pressure. It also may attract scientists with different character traits who wouldn't be able to compete in the rat race to tenure.
  - slg 12y ago
    But I am not sure how saying it is a 100 year study really changes that? Sure it might be better than a 5 year study, but is it better than one that is simply ongoing? Or how about opening a specialized department focused on this type of thing? 100 seems like an arbitrary number that was only chosen to make this seem important. "Stanford to host ongoing study on artificial intelligence" is just a less interesting headline.
nostromo 12y ago
The study's final authors may not be human. As such, they will clearly be biased.
- ema 12y ago
  Well, humans aren't unbiased either.
samteeeee 12y ago
Wintermute
stephengoodwin 12y ago
The headline in 2040: 100-year Stanford AI study to add first Android professor.
vph 12y ago
100 is a nice, round and even number. It's also a marketing ploy. Truth is none of these guys can make an accurate prediction about what AI can do in 20 years.
- killerdhmo 12y ago
  I don't know the researchers in question but Turing's paper [0] was surprisingly predictive in 1936, decades before any of this came to light. It's not out of the question that they could set the direction of research for a decade or two in the future. I agree, 100 as a number is a marketing ploy. But I like the idea of a sustainable long term mission, rather than the funding rat race and trend chasing you tend to see. [0] http://www.abelard.org/turpap/turpap.php http://www.abelard.org/turpap/turpap.php
  - marcosdumay 12y ago
    > I believe that in about fifty years time it will be possible to programme computers with a storage capacity of about 10^9 to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning. He was mostly right, out of only some 25 years, 50% more. A really great estimate for something that changed so fast. But just next: > Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted. That was quite off the mark. Anyway, Turing's prediction was for 50 years in the future, that's orders of magnitude easier than 100 years in the future. And nearly all of the predictions by that time were completely wrong, what makes you think those people are the ones of our time that'll get their predictions right?
    - Raphael 12y ago
      Playing Chess against Stockfish, there's an setting for "thinking time".
vph 12y ago
100 is a nice, round and even number. It's also a marketing ploy. Truth is none of these guys can make an accurate prediction about AI within 20 years.
ccvannorman 12y ago
Headline from 2115: Stanford AI100 study results suggest a strong AI breakthrough a mere 15 years away
- dave_sullivan 12y ago
  Indeed. On the flip side, "AI" is a moving target--people used to think mathematical proofs, chess, and jeopardy required "intelligence", but we now know we just need software. I've heard people say "We've made no progress towards AI", but I think that's as hyperbolic as saying "it's right around the corner". Progress (in this case, using machine learning to build cool things) isn't this on/off thing. There are worse fields of study to enter than machine learning. You'll learn things that are broadly applicable. And maybe "real AI" happens someday, this would be on par with invention of flight or moon landing, both of which sounded batshit before someone (a bunch of people) did it.
drewda 12y ago
Reminds me of a symposium I attended at Stanford in 2000 titled "Will Spiritual Robots Replace Humanity by 2100?"[1][2]. (At the time, Bill Joy had written a provocative cover story for Wired headlined "Why the Future Doesn't Need Us: Our most powerful 21st-century technologies - robotics, genetic engineering, and nanotech - are threatening to make humans an endangered species"[3] and this panel was assembled in response.) Glad to see that the backers of this new initiative agree with the more nuanced folks on that panel, like John Holland--that these will continue to be meaty questions to consider, both in computational and philosophical terms, well past 2100. [1] http://news.stanford.edu/news/2000/march29/robots-329.html http://news.stanford.edu/news/2000/march29/robots-329.html [2] https://www.youtube.com/playlist?list=PLvW5zob1PPbbFUZK_LdzU8iJBSFb2Zhyb https://www.youtube.com/playlist?list=PLvW5zob1PPbbFUZK_LdzU... [3] http://archive.wired.com/wired/archive/8.04/joy.html http://archive.wired.com/wired/archive/8.04/joy.html
facepalm 12y ago
Reminds me of a German legend I recently read to my child, of Till Eulenspiegel. He traveled around in the middle ages and pranked people. Once a couple of professors challenged him to teach a horse to read. He immediately said "of course I can do it, but since horses are not very smart, it will probably take 20 years". His thinking was that before 20 years the horse might die, or the professors who challenged him might die, so he would be fine.
sixQuarks 12y ago
The singularity or humanity will destroy everything within 50 years. If we make it another 100 years, I'll be pretty surprised. Old, and surprised that is.
melipone 12y ago
It seems to me it's more about the effects of AI on people and society than about AI itself.
deleted 12y ago
[deleted]
ajarmst 12y ago
Damn it. I am, like, NEVER going to finish this dissertation.
atrilla 12y ago
Related to the impact of AI to society, especially wrt the increase of unemployment. I was reading the comments of this MIT Tech Review (http://www.technologyreview.com/news/533686/2014-in-computing-breakthroughs-in-artificial-intelligence/ http://www.technologyreview.com/news/533686/2014-in-computin...) and I came across this opinion, which gave me the shivers. Two points: 1) AI taking manual workforce-based jobs. I can't help seeing how beneficial the industrialisation of processes has been for humanity. Instead of relying on inaccurate human judgement for manufacturing jobs, we let machines produce perfectly similar assets much better than we can do. This has increased the reliability of the outputs, in addition to lowering the prices of the products, which has made them affordable to many more people. Jobs get more specialised, so like the tools human beings have developed throughout history. Once more, survival entails adaptation. And this is again a matter of supply and demand. In Spain, where the economic crisis is still hitting the markets and unemployment, having a proper specialised education no longer guarantees landing a job (and it's not because evil robots are doing the tasks of leaving scientists). 2) AI taking over engineers, lawyers, etc. AI is difficult per se. Nobody comes up with a human replica made of metal by chance. Things take their time, and improvements are gradual. That's a matter of fact. At present, AI (plus Machine Learning, Pattern Recognition...) delivers a set of tools that allow us to see father, from the shoulders of giants. We had never been able to digest the amount of data we are capable of doing nowadays. Isn't this progress? We haven't yet created a creative machine and I don't see it coming any time soon. I am so firmly convinced that AI has so much good to do that I just created a blog (http://ai-maker.com/ http://ai-maker.com/) solely dedicated to AI and its applications, and I'm going to dedicate my spare time for the following years to grow this side project into something awesome, because that's where AI is leading us.
- edanm 12y ago
  It might interest you to join the LessWrong community, or read up on the work of MIRI (the Machine Intelligence Research Institute, https://intelligence.org/ https://intelligence.org/). You can start by reading a few posts at the site: www.lesswrong.com.

127 points by bra-ket 12y ago

bra-ket 12y ago

https://ai100.stanford.edu/ https://ai100.stanford.edu/

pcthrowaway 12y ago

Someone behind this study clearly has little faith in the imminence of AGI.

chriswarbo 12y ago
Well, it's been imminent since the summer of 1956 ( http://en.wikipedia.org/wiki/Dartmouth_Conferences http://en.wikipedia.org/wiki/Dartmouth_Conferences )
- marcosdumay 12y ago
  Or, in other words, for about half the time those people are expecting no AI. Never mind the Moore's Law putting computers more capable than our brains less than 30 years away.
  - gweinberg 12y ago
    Nobody thinks Moore's law will last another 30 years.
    - dudus 12y ago
      Nobody thought it would last till here
      - jblow 12y ago
        See this graph: http://www.extremetech.com/wp-content/uploads/2013/08/CPU-Scaling.jpg http://www.extremetech.com/wp-content/uploads/2013/08/CPU-Sc... The green line was the only one still going, and it plateaued about a year ago (you'd see that in a newer graph).
        dysfunction 12y ago
        The green line is the only one that Moore's law is about. Power consumption plateauing is a good thing, clock speed was never going to be the primary driver of performance increases long-term, and instruction-level parellelism (green line) is not a measure of performance-per-clock-cycle.
    - maaku 12y ago
      There's plenty of room on the bottom.
    - marcosdumay 12y ago
      Well, I think it's already dead for some good 3 or 4 years. It just didn't start stinking yet. But that's no reason to think that it'll take more than 100 years.
  - kmicklas 12y ago
    Moore's Law is about transistor density, not computing power, so no it won't. We could probably already build a computer more powerful than the human brain, it would just be huge (millions of cores or something). But that wouldn't help, because the real issue is that the Von Neumann architecture fundamentally prevents scaling the kinds of computations we want to do for neural networks. We need something more neuromorphic, although probably still discrete. (I'm guessing basically just a giant DSP integrated into memory on the same core.)
    - rl3 12y ago
      You may find these relevant: http://www.technologyreview.com/news/529691/ibm-chip-processes-data-similar-to-the-way-your-brain-does/ http://www.technologyreview.com/news/529691/ibm-chip-process... http://www.kurzweilai.net/ibm-simulates-530-billon-neurons-100-trillion-synapses-on-worlds-fastest-supercomputer http://www.kurzweilai.net/ibm-simulates-530-billon-neurons-1...
- eli_gottlieb 12y ago
  Once upon a time, men said that AGI was imminent despite the fact that they had no computational model whatsoever of human cognition, and no limitary results other. Now, we have increasingly good computational models of human cognition, with abundant limitary results on both human and mechanical reasoning, but only madmen believe AGI will work in their lifetimes. Irony!

slg 12y ago

Somewhat cynical question, but is the 100 year aspect of this study anything beyond a marketing gimmick?

rguzman 12y ago
Even if the study doesn't live as long as its name states, a clear mission is useful because it guides people's decision making. A researcher in this should be optimizing her efforts for the 100 year timescale and not for the ~5 year one.
- x1798DE 12y ago
  I don't see how that changes the individual researcher's incentive to make achieving short term, publishable discoveries a priority.
  - dangerlibrary 12y ago
    One concrete example would be data acquisition. Long term, large sample panel data sets take decades to produce, but are incredibly valuable if well designed / executed. If you are applying for funding as part of a 100 year study, you won't get continued funding unless you put in the effort up front to design the data acquisition correctly.
    - Someone 12y ago
      Another is what a project can offer your personnel. A four-year project will almost solely have temporary jobs. A hundred-year project will be able to offer more permanent assignments. That creates less 'publish or perish' pressure. It also may attract scientists with different character traits who wouldn't be able to compete in the rat race to tenure.
- slg 12y ago
  But I am not sure how saying it is a 100 year study really changes that? Sure it might be better than a 5 year study, but is it better than one that is simply ongoing? Or how about opening a specialized department focused on this type of thing? 100 seems like an arbitrary number that was only chosen to make this seem important. "Stanford to host ongoing study on artificial intelligence" is just a less interesting headline.

nostromo 12y ago

The study's final authors may not be human. As such, they will clearly be biased.

ema 12y ago
Well, humans aren't unbiased either.

samteeeee 12y ago

Wintermute

stephengoodwin 12y ago

The headline in 2040: 100-year Stanford AI study to add first Android professor.

vph 12y ago

100 is a nice, round and even number. It's also a marketing ploy. Truth is none of these guys can make an accurate prediction about what AI can do in 20 years.

killerdhmo 12y ago
I don't know the researchers in question but Turing's paper [0] was surprisingly predictive in 1936, decades before any of this came to light. It's not out of the question that they could set the direction of research for a decade or two in the future. I agree, 100 as a number is a marketing ploy. But I like the idea of a sustainable long term mission, rather than the funding rat race and trend chasing you tend to see. [0] http://www.abelard.org/turpap/turpap.php http://www.abelard.org/turpap/turpap.php
- marcosdumay 12y ago
  > I believe that in about fifty years time it will be possible to programme computers with a storage capacity of about 10^9 to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning. He was mostly right, out of only some 25 years, 50% more. A really great estimate for something that changed so fast. But just next: > Nevertheless I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted. That was quite off the mark. Anyway, Turing's prediction was for 50 years in the future, that's orders of magnitude easier than 100 years in the future. And nearly all of the predictions by that time were completely wrong, what makes you think those people are the ones of our time that'll get their predictions right?
  - Raphael 12y ago
    Playing Chess against Stockfish, there's an setting for "thinking time".

vph 12y ago

100 is a nice, round and even number. It's also a marketing ploy. Truth is none of these guys can make an accurate prediction about AI within 20 years.

ccvannorman 12y ago

Headline from 2115: Stanford AI100 study results suggest a strong AI breakthrough a mere 15 years away

dave_sullivan 12y ago
Indeed. On the flip side, "AI" is a moving target--people used to think mathematical proofs, chess, and jeopardy required "intelligence", but we now know we just need software. I've heard people say "We've made no progress towards AI", but I think that's as hyperbolic as saying "it's right around the corner". Progress (in this case, using machine learning to build cool things) isn't this on/off thing. There are worse fields of study to enter than machine learning. You'll learn things that are broadly applicable. And maybe "real AI" happens someday, this would be on par with invention of flight or moon landing, both of which sounded batshit before someone (a bunch of people) did it.

drewda 12y ago

Reminds me of a symposium I attended at Stanford in 2000 titled "Will Spiritual Robots Replace Humanity by 2100?"[1][2]. (At the time, Bill Joy had written a provocative cover story for Wired headlined "Why the Future Doesn't Need Us: Our most powerful 21st-century technologies - robotics, genetic engineering, and nanotech - are threatening to make humans an endangered species"[3] and this panel was assembled in response.) Glad to see that the backers of this new initiative agree with the more nuanced folks on that panel, like John Holland--that these will continue to be meaty questions to consider, both in computational and philosophical terms, well past 2100. [1] http://news.stanford.edu/news/2000/march29/robots-329.html http://news.stanford.edu/news/2000/march29/robots-329.html [2] https://www.youtube.com/playlist?list=PLvW5zob1PPbbFUZK_LdzU8iJBSFb2Zhyb https://www.youtube.com/playlist?list=PLvW5zob1PPbbFUZK_LdzU... [3] http://archive.wired.com/wired/archive/8.04/joy.html http://archive.wired.com/wired/archive/8.04/joy.html

facepalm 12y ago

Reminds me of a German legend I recently read to my child, of Till Eulenspiegel. He traveled around in the middle ages and pranked people. Once a couple of professors challenged him to teach a horse to read. He immediately said "of course I can do it, but since horses are not very smart, it will probably take 20 years". His thinking was that before 20 years the horse might die, or the professors who challenged him might die, so he would be fine.

sixQuarks 12y ago

The singularity or humanity will destroy everything within 50 years. If we make it another 100 years, I'll be pretty surprised. Old, and surprised that is.

melipone 12y ago

It seems to me it's more about the effects of AI on people and society than about AI itself.

deleted 12y ago

[deleted]

ajarmst 12y ago

Damn it. I am, like, NEVER going to finish this dissertation.

atrilla 12y ago

Related to the impact of AI to society, especially wrt the increase of unemployment. I was reading the comments of this MIT Tech Review (http://www.technologyreview.com/news/533686/2014-in-computing-breakthroughs-in-artificial-intelligence/ http://www.technologyreview.com/news/533686/2014-in-computin...) and I came across this opinion, which gave me the shivers. Two points: 1) AI taking manual workforce-based jobs. I can't help seeing how beneficial the industrialisation of processes has been for humanity. Instead of relying on inaccurate human judgement for manufacturing jobs, we let machines produce perfectly similar assets much better than we can do. This has increased the reliability of the outputs, in addition to lowering the prices of the products, which has made them affordable to many more people. Jobs get more specialised, so like the tools human beings have developed throughout history. Once more, survival entails adaptation. And this is again a matter of supply and demand. In Spain, where the economic crisis is still hitting the markets and unemployment, having a proper specialised education no longer guarantees landing a job (and it's not because evil robots are doing the tasks of leaving scientists). 2) AI taking over engineers, lawyers, etc. AI is difficult per se. Nobody comes up with a human replica made of metal by chance. Things take their time, and improvements are gradual. That's a matter of fact. At present, AI (plus Machine Learning, Pattern Recognition...) delivers a set of tools that allow us to see father, from the shoulders of giants. We had never been able to digest the amount of data we are capable of doing nowadays. Isn't this progress? We haven't yet created a creative machine and I don't see it coming any time soon. I am so firmly convinced that AI has so much good to do that I just created a blog (http://ai-maker.com/ http://ai-maker.com/) solely dedicated to AI and its applications, and I'm going to dedicate my spare time for the following years to grow this side project into something awesome, because that's where AI is leading us.

edanm 12y ago
It might interest you to join the LessWrong community, or read up on the work of MIRI (the Machine Intelligence Research Institute, https://intelligence.org/ https://intelligence.org/). You can start by reading a few posts at the site: www.lesswrong.com.