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Except ancient philosophers weren't even working with scientific methodology. The issue is with how much empirical data you need to be able to form hypotheses a

by qrendel 11y ago

Except ancient philosophers weren't even working with scientific methodology. The issue is with how much empirical data you need to be able to form hypotheses about the world and falsify them, of which humans are almost certainly not doing a near-optimal job. Otherwise we might as well say scientific revolutions are independent of intelligence and the edifice of pre-existing knowledge, and depend only on observed data about the world, and there's substantial evidence against this[1]. For a counterargument from one of the believers of bootstrapping, superintelligent AI: http://lesswrong.com/lw/qk/that_alien_message/ http://lesswrong.com/lw/qk/that_alien_message/ [1] http://infoproc.blogspot.com/2008/07/annals-of-psychometry-iqs-of-eminent.html http://infoproc.blogspot.com/2008/07/annals-of-psychometry-i... ... In addition to evidence such as the long periods of time before simple understandings like natural selection, the heliocentric model, and constant acceleration of gravity were developed.

mariusz79 11y ago
no matter how many hypothesis you create you need to be able to test them. AI won't be able to run experiments by itself, at least not in the beginning. and even when it could, some of them will require years to complete, simply because so much science depends on real physical phenomena that often are very slow. Computer based simulations are often very slow, and AI won't be able to speed it up, just because it's AI.
- dframe 11y ago
  Incorrect thinking in two ways : >A.I could run experiments by itself if it is provided with enough information to do so. Classical physics (already possible) and even quantum physics, once fully understood can be programmed. There are already scores of algorithms and computer programs that can run physics experiments and it doesn't take years. You seem to be misinformed about even present technological capability > Computer simulations aren't slow. Distributed computing and processing power allow for a considerable number of experiments to be simulated. If you work in this area, I feel you have a totally different view of things. You can either speak in terms of 'x' isn't possible and end it there or say 'x' is possible and I'm going to discover how.
  - mariusz79 11y ago
    Let's just consider a basic example - AI tries to develop better algorithms to simulate fluid dynamics. 1. How do you expect AI to create these simulations? Will it program it itself? I assume that the answer is yes, if so a. it needs to know how to program. b. it needs to know how to efficiently use the hardware that it can access. c. it may need to know all the quirks of the software, hardware and operating system that it works with. d. it also will need to have a pretty good math skills Someone will need to teach AI how to do all of that or it will need to learn by itself.. This will take time.And experience. Such AI will need to run the simulation it created, analyze it, compare results, come up with a hypothesis, and do it all over again to refine the results. What if there is a wrong assumption about fluid dynamics that is caused by some wrong assumptions on a lower level, i.e theory of matter. How will that change the results and will AI need to go back a step lower to "fix" our understanding of matter? what if there are some issues with math that first need to be "fixed", or totally new math theories must first be created? Of course AI will not need to have everything perfect, right from the beginning, and better theories will suffice, but to say that long-term experiments such as this, are not necessary simply because AI will solve physics is just wrong.
- JabavuAdams 11y ago
  Sure, but the concentration of capital and the leverage a GAI is likely to have should streamline the project-management and fund-raising aspects. Imagine if you didn't have to convince anyone else to fund your experiments.
adwn 11y ago
> For a counterargument from one of the believers of bootstrapping, superintelligent AI: http://lesswrong.com/lw/qk/that_alien_message/ http://lesswrong.com/lw/qk/that_alien_message/ Woah, Yudkowsky takes really long to get to the point, doesn't he? So his point seems to be, that humans aren't very efficient in processing empirical evidence, and an AI might be better at this, because it would be really, really smart?
- qrendel 11y ago
  Yeah, I've always had that same complaint about his writing. Unfortunately just the relevant portions I might have quoted still wouldn't have fit concisely in the comment. Primarily the parts about how models used to describe the world often predate the observed phenomena they're used to describe (Riemannian geometry for general relativity, in his example), and human ability to eliminate hypotheses based on observed data isn't even vaguely imaginably close to the limits set by information theory. Not that all this is to say advances in AI will automatically guarantee wonderful new physics, much less a final theory explaining it all, but it seems really unlikely that massively improved cognition (through AI or other means) wouldn't lead to much faster progress on all sorts of problems. We're certainly not making optimal use of our observed data about the world, and even if that was the bottleneck, AI should be better at collecting and correlating more data at once anyway. The LHC already relies on machine learning to sort through the massive number of collisions and detections being produced, so the recent experimental advances are basically reliant on AI as it is.

by qrendel 11y ago

mariusz79 11y ago

no matter how many hypothesis you create you need to be able to test them. AI won't be able to run experiments by itself, at least not in the beginning. and even when it could, some of them will require years to complete, simply because so much science depends on real physical phenomena that often are very slow. Computer based simulations are often very slow, and AI won't be able to speed it up, just because it's AI.

dframe 11y ago
Incorrect thinking in two ways : >A.I could run experiments by itself if it is provided with enough information to do so. Classical physics (already possible) and even quantum physics, once fully understood can be programmed. There are already scores of algorithms and computer programs that can run physics experiments and it doesn't take years. You seem to be misinformed about even present technological capability > Computer simulations aren't slow. Distributed computing and processing power allow for a considerable number of experiments to be simulated. If you work in this area, I feel you have a totally different view of things. You can either speak in terms of 'x' isn't possible and end it there or say 'x' is possible and I'm going to discover how.
- mariusz79 11y ago
  Let's just consider a basic example - AI tries to develop better algorithms to simulate fluid dynamics. 1. How do you expect AI to create these simulations? Will it program it itself? I assume that the answer is yes, if so a. it needs to know how to program. b. it needs to know how to efficiently use the hardware that it can access. c. it may need to know all the quirks of the software, hardware and operating system that it works with. d. it also will need to have a pretty good math skills Someone will need to teach AI how to do all of that or it will need to learn by itself.. This will take time.And experience. Such AI will need to run the simulation it created, analyze it, compare results, come up with a hypothesis, and do it all over again to refine the results. What if there is a wrong assumption about fluid dynamics that is caused by some wrong assumptions on a lower level, i.e theory of matter. How will that change the results and will AI need to go back a step lower to "fix" our understanding of matter? what if there are some issues with math that first need to be "fixed", or totally new math theories must first be created? Of course AI will not need to have everything perfect, right from the beginning, and better theories will suffice, but to say that long-term experiments such as this, are not necessary simply because AI will solve physics is just wrong.
JabavuAdams 11y ago
Sure, but the concentration of capital and the leverage a GAI is likely to have should streamline the project-management and fund-raising aspects. Imagine if you didn't have to convince anyone else to fund your experiments.

adwn 11y ago

> For a counterargument from one of the believers of bootstrapping, superintelligent AI: http://lesswrong.com/lw/qk/that_alien_message/ http://lesswrong.com/lw/qk/that_alien_message/ Woah, Yudkowsky takes really long to get to the point, doesn't he? So his point seems to be, that humans aren't very efficient in processing empirical evidence, and an AI might be better at this, because it would be really, really smart?

qrendel 11y ago
Yeah, I've always had that same complaint about his writing. Unfortunately just the relevant portions I might have quoted still wouldn't have fit concisely in the comment. Primarily the parts about how models used to describe the world often predate the observed phenomena they're used to describe (Riemannian geometry for general relativity, in his example), and human ability to eliminate hypotheses based on observed data isn't even vaguely imaginably close to the limits set by information theory. Not that all this is to say advances in AI will automatically guarantee wonderful new physics, much less a final theory explaining it all, but it seems really unlikely that massively improved cognition (through AI or other means) wouldn't lead to much faster progress on all sorts of problems. We're certainly not making optimal use of our observed data about the world, and even if that was the bottleneck, AI should be better at collecting and correlating more data at once anyway. The LHC already relies on machine learning to sort through the massive number of collisions and detections being produced, so the recent experimental advances are basically reliant on AI as it is.