Aaron: No, you can't recognize those using images. Yes, you can recognize them
with other means
Sounds mystical. What does this element - “the ability to support you etc”
physically consist of – and in what aspect of these chairs is it evident? And
with what means can you recognize it that are not sensory/imagistic?
In my next post I will physically analyse parts of these chairs – why don’t you
do similar?
P.S. One can realistically frame a concept like you’re referring to – let’s
crudely call it “bum-supportability”. But the problems of analysing that
concept are much the same, only more complicated, as those of analysing chairs.
You’re in danger of getting into an infinite regress.
From: Aaron Hosford
Sent: Wednesday, October 24, 2012 12:03 AM
To: AGI
Subject: Re: [agi] Re: Superficiality Produces Misunderstanding - Not Good
Enough
Sorry, gmail didn't like a key combination. As I was saying:
Considering I just told you what the COMMON ELEMENTS and COMMON RELATIONSHIPS
OF THOSE ELEMENTS were, namely "not the shape, but the combination of
capability to support a behind and the potential inclination of a person to
take advantage of that capability (or intention of the creator to provide such
an artifact)", I'm going to concluded you either weren't paying attention or
didn't understand what I was saying.
The common elements are:
1. the ability to support you while sitting
2. a person's intention for it to be used in that way
No, you can't recognize those using images. Yes, you can recognize them with
other means. Once you've built something that works in these terms (how an
object is used) instead of merely how an object is shaped, it's easy to apply
those same terms to other classes of objects.
On Tue, Oct 23, 2012 at 5:59 PM, Aaron Hosford <[email protected]> wrote:
Considering I just told you what the COMMON ELEMENTS and COMMON RELATIONSHIPS
OF THOSE ELEMENTS were, namely "not the shape, but the combination of
capability to support a behind and the potential inclination of a person to
take advantage of that capability (or intention of the creator to provide such
an artifact)", I'm going to concluded you either weren't paying attention or
didn't understand what I was saying.
The common elements are:
1. the ability to support you while sitting
On Tue, Oct 23, 2012 at 1:04 PM, Mike Tintner <[email protected]>
wrote:
Aaron,
I have just sent out a post to PM wh. applies equally to you.
This is waffle.
You have to identify -
what are the COMMON ELEMENTS - and COMMON RELATIONSHIPS OF THOSE ELEMENTS
– that will enable you or your semantic net to identify these different figures
as belonging to the same class of “chair” and not “collages of wood” or “piles
of assorted forms” or “computer desk” or “collections of tools”?
ARE there any common elements?
You haven’t identified any
You have to provide a direct clue as to how you are going to solve this
problem – the problem of AGI – and not just waffle.
From: [email protected]
Sent: Tuesday, October 23, 2012 6:34 PM
To: AGI
Subject: Re: [agi] Re: Superficiality Produces Misunderstanding - Not Good
Enough
The thing which typifies the category "chair" is not the shape, but the
combination of capability to support a behind and the potential inclination of
a person to take advantage of that capability (or intention of the creator to
provide such an artifact). These are things that are easy to represent in
semantic nets, and difficult to represent as rules about shape.
If I have a representation of an object as a semantic net describing its
parts and their physical relationships to each other, I can write a straight
forward algorithm to analyze the transitive "supports" and "is connected to"
relations in that description to determine whether the spot I intend to sit is
supported. I can also determine whether or not my behind, when placed there,
will itself be supported, or whether I'll slide off or topple over.
The network generating algorithm can be designed to provide the information
needed to perform this simulation (simulation being the reason you say images
are necessary in the first place). Once the simulation has been performed the
first time, the node representing the chair as a whole object can be labeled
with a summary of the results, acting as a cache for relevant information so
that the expensive operation of full physical simulation can be avoided next
time the information is needed. It is this caching ability that gives
hierarchical semantic nets their leg up over other ways of representing the
problem.
-- Sent from my Palm Pre
----------------------------------------------------------------------------
On Oct 23, 2012 11:30 AM, Mike Tintner <[email protected]> wrote:
PM & Aaron,
You do realise that whatever semantic net system you use must apply to not
just one chair, but chair after chair – image after image?
Bearing that in mind, explain the elements of your semantic net which you
will use to analyse these fairly simple figures as **chairs**::
http://image.shutterstock.com/display_pic_with_logo/95781/95781,1218564477,2/stock-vector-modern-chair-vector-16059484.jpg
Let’s label these chairs 1-25 (going L to R from the top down, row after
row)
Start with just 1. and 2. top left and explain how your net will recognize
2 as another example of 1.
How IOW do you define a “chair” in terms of simple abstract forms?
Then we can apply your system, successively, to 3. 4. etc.
This is the problem that has defeated all AGI-ers and all psychologists and
philosophers so far.
But Aaron (and PM?) has a semantic net solution to it - if you can solve
jungle scenes, this should be a piece of cake.
I am saying, Aaron, you do not understand this problem – the problem of
visual object recognition/conceptualisation//applicability of semantic nets.
You are saying you do – and it’s me who is confused. Show me.
From: Piaget Modeler
Sent: Tuesday, October 23, 2012 4:41 PM
To: AGI
Subject: RE: [agi] Re: Superficiality Produces Misunderstanding - Not Good
Enough
Mike,
When you type "Chair" what should happen is the AGI's model should activate
the chair concept
first at a perceptual level to form the pixels into the words, then at a
linguistic level to form letters
into a word, then at a conceptual level, then at a simulation level where
images of chair instances
are evoked.
This is just simple activation. Semantic networks tied into perception and
simulation would achieve
the necessary effect you seek. Transformations on these
perception-simulation-semantic networks
is what much of Piaget's work was about.
~PM.
----------------------------------------------------------------------------
From: [email protected]
To: [email protected]
Subject: Re: [agi] Re: Superficiality Produces Misunderstanding - Not Good
Enough
Date: Tue, 23 Oct 2012 15:09:30 +0100
CHAIR
...
It should be able to handle any transformation of the concept, as in
DRAW ME (or POINT TO/RECOGNIZE) A CHAIR IN TWO PIECES –..
..SQUASHED
..IN PIECES
-HALF VISIBLE
..WITH AN ARM MISSING
...WITH NO SEAT
..IN POLKA DOTS
...WITH RED STRIPES
Concepts are designed for a world of everchanging, everevolving multiform
objects (and actions). Semantic networks have zero creativity or adaptability
– are applicable only to a uniform set of objects, (basically a database) -
and also, crucially, have zero ability to physically recognize or interact with
the relevant objects. I’ve been into it at length recently. You’re the one not
paying attention.
The suggestion that networks or similar can handle concepts is completely
absurd.
This is yet another form of the central problem of AGI, which you clearly
do not understand – and I’m not trying to be abusive – I’ve been realising
this again recently – people here are culturally punchdrunk with concepts like
*concept* and *creativity*, and just don’t understand them in terms of AGI.
From: Jim Bromer
Sent: Tuesday, October 23, 2012 2:04 PM
To: AGI
Subject: Re: [agi] Re: Superficiality Produces Misunderstanding - Not Good
Enough
Mike Tintner <[email protected]> wrote:
AI doesn’t handle concepts.
Give me one example to prove that AI doesn't handle concepts.
Jim Bromer
On Tue, Oct 23, 2012 at 4:24 AM, Mike Tintner <[email protected]>
wrote:
Jim: Mike refuses to try to understand what I am saying because he would
have to give up his sense of a superior point of view in order to understand it
Concepts have nothing to do with semantic networks.
AI doesn’t handle concepts.
That is the challenge for AGI.
The form of concepts is graphics.
The referents of concepts are infinite realms..
What are you saying that is relevant to this, or that can challenge this
– from any evidence?
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
AGI | Archives | Modify Your Subscription
-------------------------------------------
AGI
Archives: https://www.listbox.com/member/archive/303/=now
RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393
Modify Your Subscription:
https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968
Powered by Listbox: http://www.listbox.com
