But you forgot to explain how an AGI program would know:
What is a butler?  What is an assassin? How are those two related?  Why
would anyone assume that a butler has something to do with an assassin?
What is a the?  What is a is?  What is a the again?  What is a he?  (And
knowing what a he is how does it become bound the the butler?)  What is
a... (Do I actually have to spell it all out for you?).

The logic of the problem that you gave is EXTREMELY simple and yes a lot of
us were aware that in trying to find the answer to a problem one often has
to collect more information.  But the problem that currently confronts the
development of AGI is that when you actually try to assign ALL the details
to your story into a fine grained explanation of how a person is able
to figure it out, it suddenly becomes MUCH much more complicated.  When you
add to that the recognition that there is a potential for lot of sources of
ambiguity in the derivation of a conclusion for a real world problem and
that an AGI program is going to be going on automatic without people spoon
feeding it with explicit directions, the logic of a real world problem (or
even a theatrical hack like this) becomes inexpressibly complicated.  I
certainly don't want to belabor what most of know is obvious, but I have
noticed that you aren't a stickler for detail either.

The skepticism that I have towards your claim (implicit or explicit) that
you have it figured out is not that the theory is completely lame but that
you seem to have no idea what it is that I have been trying to say.  Do you
get it now?  Of course not, because, in your mind, you don't have to: You
already have it all figured out.

Sorry if I seem unpleasant, but this is my honest opinion.  I am not
exaggerating to make my point seem stronger than it is.

Jim Bromer


On Sat, Sep 1, 2012 at 10:56 AM, Sergio Pissanetzky
<[email protected]>wrote:

> AGI,****
>
> ** **
>
> I don't recall having explained granularity on this blog before. My
> neglect has caused ****
>
> misunderstandings. So here it is. ****
>
> ** **
>
> When we describe our world, we arbitrarily select the *granularity* of our
> description. ****
>
> (A) "The buttler is the assasin. He was at the scene, and he has a
> motive." ****
>
> That's a very coarse granularity, but it is already a causal set. ****
>
> Still, we can already take action. We can arrest the buttler and find more
> facts. ****
>
> (B) "The crime took place at 7:30." ****
>
> (C) "The buttler left the scene at 7:29."****
>
> And we can draw a conclusion: ****
>
> (D) "The buttler was not at the scene at the time of the crime. ****
>
> We have now a better description, a finer granularity. ****
>
> But what does it mean to "draw a conclusion?" ****
>
> It  means to *bind* or *associate* B and C to generate D. ****
>
> This is a logical step, and requires a mathematical logic operating on the
> causal set. ****
>
> The logic removes uncertainty from the causal set and creates structure. *
> ***
>
> The set {B, C} is uncertain. We know B and C, but we ask "so what?" ****
>
> To reach D we have to remove the uncertainty. ****
>
> Removing uncertainty is easy for our brains. ****
>
> We don't even notice it happened because we are not aware of it happening.
> ****
>
> It is unconscious, and our brains do it all the time. ****
>
> ** **
>
> You the reader can continue the excercise. ****
>
> Every bit of information we acquire is followed by a "remove uncertainty"
> step. ****
>
> Our brains are constantly removing uncertainty. ****
>
> AGI will never work unless we learn how to "remove uncertainty" on a
> computer. ****
>
> No adaptive system will work unless we learn how to "remove uncertainty"
> on a computer. ****
>
> Have courage, don't leave the uncertainty there. ****
>
> ** **
>
> I must have tired everyone by saying entropy all the time. But entropy is
> just a measure of uncertainty. If someone is 6 feet tall, I must use "feet"
> to say that.****
>
> ** **
>
> Sergio****
>
> ** **
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