Hi Ben, 

Thank you for your response. I started reading the paper and was wondering 
if you could help me clarify a confusion i apparently have when it comes to 
the meaning of meaning: 

How is linguistic meaning connected to human embodied meaning that we would 
call human (or AGI) understanding. 

Linguistic meaning seems to be about the linguistic meta-language that 
shows how a human would parse a sentence unambiguously, so that a human 
can, in principle, understand the meaning of a sentence, although, what is, 
say, instructed by a sentence, as understood by a human seems not captured, 
but would require more machinery.

In this sense, linguistic machinery seems to embody (as a theory of mind) 
how humans understand (in a cognitive economical manner), rather than what 
humans understand --at least this is what confuses me ...

any thought would be much appreciated ...

thank you,

Daniel





On Wednesday, 19 April 2017 09:16:42 UTC+3, Ben Goertzel wrote:
>
> We have a probabilistic logic engine (PLN) which works on (optionally 
> probabilistically labeled) logic expressions....   This logic engine 
> can also help with extracting semantic information from natural 
> language or perceptual observations.  However, it's best used together 
> with other methods that carry out "lower levels" of processing in 
> feedback and cooperation with it... 
>
> In the case of vision, Ralf Mayet is leading an effort to use a 
> modified InfoGAN deep NN to extract semantic information from 
> images/videos/sounds to pass into PLN, the Pattern Miner, and so forth 
>
> In the case of textual language, Linas is leading an effort to extract 
> a first pass of semantic and syntactic information from unannotated 
> text corpora via this general approach 
>
> https://arxiv.org/abs/1401.3372 
>
> The same approach should work when non-textual groundings are included 
> in the corpus, or when the learning is real-time experiential rather 
> than batch-based.... but there's plenty of nitty-gritty work here... 
>
> ben goertzel 
>
> On Wed, Apr 19, 2017 at 7:23 AM, Daniel Gross <[email protected] 
> <javascript:>> wrote: 
> > Hi Linas, 
> > 
> > How do you propose to learn an ontology from the data -- also, what 
> purpose 
> > would, in your opinion, the learned ontology serve. Or stated 
> differently, 
> > in what way are you thinking to engender higher-level cognitive 
> capabilities 
> > via machine learned bundled neuron (and implicit ontologies, perhaps). 
> > 
> > thank you, 
> > 
> > Daniel 
> > 
> > 
> > On Wednesday, 19 April 2017 03:40:47 UTC+3, linas wrote: 
> >> 
> >> 
> >> 
> >> On Tue, Apr 18, 2017 at 3:22 PM, Alex <[email protected]> wrote: 
> >>> 
> >>> Maybe we can solve the problem about modelling classes (and using OO 
> and 
> >>> UML notions for knowledge representation) with the following 
> (pseudo)code 
> >>> 
> >>> - We can define ConceptNode "Object", that consists from the set or 
> >>> properties and functions 
> >>> 
> >>> - We can require that any class e.g. Invoice is the inherited from the 
> >>> Object: 
> >>>   IntensionalInheritanceLink 
> >>>     Invoice 
> >>>     Object 
> >>> 
> >>> - We can require that any more specifica class, e.g. VATInvoice is the 
> >>> inherited from the more general class: 
> >>>   IntensionalInheritanceLink 
> >>>     VATInvoice 
> >>>     Invoice 
> >>> 
> >>> - We can require that any instance is inherited from the concrete 
> class: 
> >>>   ExtensionalInheritanceLinks 
> >>>     invoice_no_2314 
> >>>     VATInvoice 
> >> 
> >> 
> >> If you wish, you can do stuff like that. opencog per se is agnostic 
> about 
> >> how you do this, you can do it however you want. The proper way to do 
> this 
> >> is discussed in many places; for example here: 
> >> https://en.wikipedia.org/wiki/Upper_ontology 
> >> 
> >> I'm not particularly excited about building ontologies by hand, its 
> much 
> >> more interesting (to me) to understand how they can be learned 
> >> automatically, from raw data. 
> >>> 
> >>> 
> >>> But I don't know yet what can and what can not be the parent for 
> >>> extensional and intensional inheritance. Can an entity be 
> extensionally 
> >>> inherited from the more complex object or it can be extensionally 
> inherited 
> >>> from empty set-placeholder only. When we introduce notion of set, then 
> the 
> >>> futher question always arise - does OpenCog make distinction between 
> sets 
> >>> and proper classes? 
> >> 
> >> 
> >> Why? This "distinction" only matters if you want to implement set 
> theory. 
> >> My pre-emptive strike to halt this train of thought is this: Why would 
> you 
> >> want to implement set theory, instead of, say, model theory or 
> universal 
> >> algebra, or category theory, or topos theory?  why the heck would 
> >> distinguishing a set-theoretical-set from a 
> set-theoretical-proper-class 
> >> matter? (which oh by the way is similar but not the same thing as a 
> >> category-theoretic-proper-class...) 
> >> 
> >> You've got multiple ideas going here, at once: the best way to 
> hand-craft 
> >> some ontology; the best theoretical framework to do it in; the 
> philosophy of 
> >> knowledge representation in general... and, my personal favorite: how 
> do I 
> >> get the machine to do this automatically, without manual intervention? 
> >> 
> >>> 
> >>> 
> >>> There is second problem as well - there is only one - mixed 
> >>> InheritanceLink. One can use SubsetLink for the extensional 
> inheritance 
> >>> (still it feels strange), but there is certainly necessary syntactic 
> sugar 
> >>> for intensional inheritance, because it is hard to write and read 
> SubsetLink 
> >>> of property sets again and again 
> >>> (http://wiki.opencog.org/w/InheritanceLink). 
> >> 
> >> 
> >> If the machine has learned an ontology with a million subset links in 
> it, 
> >> no human being is ever going to read or want to read that network. 
> It'll be 
> >> like looking at a bundle of neurons: the best you can do is say "oh 
> wow, a 
> >> bundle of neurons!" 
> >> 
> >> --linas 
> >>> 
> >>> 
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> -- 
> Ben Goertzel, PhD 
> http://goertzel.org 
>
> "I am God! I am nothing, I'm play, I am freedom, I am life. I am the 
> boundary, I am the peak." -- Alexander Scriabin 
>

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