From: Vladimir Nesov (email@example.com)
Date: Tue Oct 23 2007 - 20:27:38 MDT
Do you consider brain-on-transistors way improbable? In some decades
technology should allow at least destructive by-layer brain scanning, so
that brain then can be reimplemented on a different substrate to run 1000
times faster, which should be almost as good singularity-wise.
On 10/24/07, William Pearson <firstname.lastname@example.org> wrote:
> I can't currently get around the problem that we haven't had any
> instances of this happening. In a way we have had negative instances
> of some hypotheses involving AI, e.g. each planck time we don't create
> a realistic intelligence could be counted as evidence that we won't
> create one in the next planck second (and this hypothesis is very
> reliable, to date). And by induction it is not probable to create one
> in any planck time. And until we do create one, we shouldn't have a
> reason for increasing the probability of one being created, and we
> should be forever decreasing it.
> Now you could argue that the probability of creating an AI in any
> given time period is independent of one another. We have no evidence
> for this meta-hypothesis either, due to not having created an AI for
> us to analyse the distributions of how they are created. Although we
> have a fair amount of evidence that is consistent with the hypothesis
> that the probability of creating an AI not independent of time, and
> just very low.
> Possibly you could look at the number of people that have put there
> mind to creating something new, and see how many actually achieved
> there goal. How to get a good delineation of what to include as
> evidence would be problematic in this case (e.g. should the alchemists
> and there philosopher's stone be counted), and it is likely that we
> will have far more evidence of people being successful compared to the
> number of unknown failures.
> Or the kurzweil way, which I will paraphrase as: Defining AI as part
> of the type of computer system with a high resource usage and showing
> that the hypothesis that we have been increasing the resources
> available of computer systems by a certain rate over time has a lot of
> evidence. Now I don't like this one much, because while we have
> evidence we will increase resources available to computers, there is
> no evidence we will create the right computer system for intelligence
> given sufficient resources.
> Is there any principled way of deciding which way of calculating the
> probability of humans creating AI is the better to base decisions off?
> Now my knowledge of bayesian decision theory is rusty, so it may well
> be that I am missing something or my analyses are faulty. Any pointers
> to things already written? And note I am looking for a body of data I
> could feed to a Bayesian classifier, so no general human type
> arguments for AI.
> Will Pearson
-- Vladimir Nesov mailto:email@example.com
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