Self-Improving Artificial Intelligence

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Self-Improving Artificial Intelligence

October 24, 2007 lecture by Steve Omohundro for the Stanford University Computer Systems Colloquium (EE 380). Steve presents fundamental principles that underlie the operation of "self-improving systems," i.e., computer software and hardware that improve themselves by learning from their own operations.

EE 380 | Computer Systems Colloquium:

Stanford Computer Systems Laboratory:

Stanford Center for Professional Development:

Stanford University Channel on YouTube:

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  • GarfieldGaming
    December 20, 2013 at 1:03 pm

    What if one of these “bugs” takes over a robotics factory? and a weapons factory? and blacks out the world? and kills everything tha tmoves?

  • zhisko chen
    January 9, 2014 at 5:37 pm

    “HUmans are problems i prefer robots”

  • Emiel Blom
    June 15, 2014 at 8:48 am

    Wow

  • zLFOBz
    July 5, 2014 at 12:16 pm

    “Terminator”

  • Iaroslav Shcherbatyi
    September 2, 2014 at 9:36 pm

    He should be more careful with optimality condition at 14:57. At the very least the time functions T1,2(S) should be concave, otherwise it is not necessary that the value of S1(S2) that satisfies this condition will maximize the utility function. And as usually amount of resources is bounded, even for concave time functions T1,2(S) those S1(S2) satisfying this condition might not belong to feasible region (solution S1(S2) might be obtained negative for instance, which makes not much sense if you specify that S1, S2 are in [0,1])

  • Travler X
    September 8, 2015 at 5:01 am

    Published in 2008 and it is such a dated discussion.
    There seems to be a bit of an apples to oranges discussion taking place, and there is absent some of the most relevant parts of discussions as well.
    Depending on what one’s own definition of what an AI is or the prognosis of what an AI will be, an AI is not necessarily going to be able to improve itself to the point of becoming a singularity or even the singularity. Mr. Omohundro does seem to be aware of distinctive differences between the two. As opposed to a singularity which would have a measurable cognition, an AI is a purely computation system which lacks any real SENSE of self awareness but is processing information much in the way DNA does.
    This discussion conveniently ignores the complex nature of the task of creating a viable AI which performs these tasks with enough clarity to not make changes to itself that do not result in its loss of function much less utility. This discussion seems to take place inside the “perfect world” or ,should I say, lab conditions. What happens when such a system meets the reality of having to struggle to evolve itself with only mathematics as its cognition or ,in other words, with only mathematics and no real driving psychology. It’s one thing for DNA that has survived billions of years to do it many times and it is another thing for an electronic abacus to do it successfully once.
    Furthermore, in taking small steps it may prove more prudent to begin by developing a do nothing widget that is not burdened by functionality but can mutate itself just to see how entropy will affect its systems in ways that have not been theorized in draft board development…..
    Of course, I could be wrong about everything I just said, however, I do think that there will have to be a sound philosophical basis needed for a true interactive and cognitive singularity to arise from integrated computational systems that would be more than an insane reptilian robot. It would take a certain amount and type of ethics to keep it from blindly expanding and consuming until it has altered its own environment beyond its ability to adapt to. Assuming, that like all cognitive systems it would not be without its flaws which would show up as irrational behavioral quirks, it would need to have enough situational awareness coupled with its own self awareness to avoid making irreversible fatal changes to itself.
    It’s 2015 and due to the massive propagation of smartphones and the like as well as the pace of advances in neural prosthetic, neural imaging, and neural implants as well as biological nanotechnology it is looking more and more as if the information theory may just cheat and leap straight to the first singularity being a symbiotic entity attached to humans in order to optimize its own capacity by load sharing with humans as a optimizing efficiency effect since humans naturally process some types of information better than machines.

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    is there any higher quality of this speech?

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    December 13, 2016 at 12:05 am

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