Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning

[Ravi Sharma <drravisharma@xxxxxxxxx>]

Leo

Great post and useful.

What I wanted and also been seeking to learn from John and Rich was that whatever (practical) real things we are after, can logic, math and ontology help us define it so that there is a common agreeable understanding among participants. John's summary is that it is the language that binds us, certainly for those who have same language, but can the understanding be described by images, mind-models that can then be described by logic, math and ontology. The catch is how do we understand logic, math, ontology without at least a very rich vocabulary and some grammar i.e. language?

On Quantum Chromodynamics - there are open questions e.g. related to Higgs mass and also certainly those areas that require gravitation integration and related dark matter energy etc.

On Fri, Apr 24, 2015 at 7:25 PM, Rich Cooper <metasemantics@xxxxxxxxxxxxxxxxxxxxxx> wrote:

Dear Leo,

 

Thanks for your inputs, in particular:

LO> Rich, I think you tend to confuse epistemology with ontology.

 

I identify with Thomas' statement that engineering is about "let's get something built", and that is also my attitude, though I also emphasize front end feasibility analysis and completeness of matching the plan with the actual measured progress.  In that sense, I suppose I do think epistemologically. 

 

But with half my experiential conceptual apparatus invested in computer science concepts, and in economic concepts, learned from many software development tasks, I plan to keep my views.  I think in those computer science and engineering terms, not about metaphysics and obscure terminologies as a philosophy professor would.  In that sense you are correct, but I like my version better {:-]).  It suits my purposes better.  Perhaps for your, the philosophical orthodoxy is most effective and helpful.  Good for both of us!

 

LO> Ontology, as part of metaphysics, sits atop both science and epistemology. It’s not consensus-based agreement like some ISO standard and it’s not some kind of neurocognitive thing peculiar to each person separately and distinctly.

 

That sounds like a religious proclamation of faith.  And since I am not a pure philosopher, but a practical engineer, I take those with a grain of salt.  You by contrast, appear to accept that ontology is "not some kind of neurocognitive thing" and not "peculiar to each person separately and distinctly".  I understand that you believe this, and you may get good use from that belief, but I don't share it. 

 

Instead, I believe that each person uses the genetic mechanisms he is born with (neurocognitive?) along with the specific store of experiences he has channeled in his brain development and ideation (experience).  He can then use that knowledge, plus his instantaneous understanding of what choices are available to him at each decision point, to maximize his expected survivability. 

 

Therefore, I believe each person successively develops his Self as he experiences each step in his development, from birth leading up to the person you can hold a conversation with.  It is unlikely that person will be thinking about metaphysics, but very likely the person will be thinking about his daily concerns, his social group, his economic conditions, and other much more lifestyle things.  That makes his Self (ontology) as unique as any other property of a genetically diverse, existentially diverse population; this is definitely "peculiar to each person separately and distinctly". 

 

Thanks for your thoughtful post,

 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Obrst, Leo J.
Sent: Friday, April 24, 2015 6:04 PM
To: [ontolog-forum] ; 'Thomas Johnston'

Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Rich, I think you tend to confuse epistemology with ontology.

 

Probably most of us can agree on a chair, and when seeing and feeling it, agree on some properties, though we may use different words or sounds to describe those. However, the things in the world remain the same (if you are a minimal realist), and what varies is our ascribing and describing. I really don’t want to give up reference, even though that’s a thorny issue. If you consider science as a serious discipline, minimally science tries to cut through (via observation and theorizing) to consistently valid descriptions of reality and perhaps (causal, whatever that might mean) explanations of those descriptions. Ontology, as part of metaphysics, sits atop both science and epistemology. It’s not consensus-based agreement like some ISO standard and it’s not some kind of neurocogntive thing peculiar to each person separately and distinctly.

 

If you think you create your own ontology, I think you are just caught in your own epistemology, and your metaphysics needs enrichening. Solipsism and nihilism are of course potential alternatives always, but maybe aren’t so useful.

 

I think Quine had it mostly right, as Thomas mentioned, because he (Quine) tried to connect the semantics to the underlying ontological referents (once again, as many have tried) by using logic and the objects quantified over. However, I don’t think that is quite right, since at least to my mind, you can quantify over notions that you don’t really think exist, ever or even potentially (and so logic is a language for describing, not a language for telling you what there is). However, logic does allow you to have access to those things, and if you quantify over them, then they are at least candidates for real things, i.e, they provide a kind of low level entry for ontological commitment. So an ontology is a logical theory, yes, but about something in the real world. The “logical theory” part of that is easier than the “real world” part.

 

At least, that is my understanding, and as always (and perhaps usually), it may be flawed.

 

Thanks,

Leo

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Friday, April 24, 2015 12:52 PM
To: 'Thomas Johnston'; '[ontolog-forum] '
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Dear Thomas, Ravi, John, Hans et al,

 

TJ> Surely there are no algorithms for deriving anyone's ontology.

 

I don't think you can say that at this point.  Let me try a simple statement:

 

Tell the subject to think of an animal.  Tell the subject to guess the animal in the familiar 20 questions manner.  Continue with the questions, ever more and more specific, until you guess the actual animal.  If it take more than 20 questions, that's acceptable.  Ask about properties, classes, situations, enablers, inhibitors, foods, young, and any other question that can split the set of plausible answers in half each time. 

 

The point is, you can ask someone leading questions until you have discovered the person's ontology to some extent.  The problem with such a cumbersome method is that you have to ask a lot of questions to get the whole thing known.  So designing a questionnaire that can be used to separate philosophical viewpoints should be feasible, and should result in a view of the subject's stated ontology, if not the subject's actual ontology. 

 

TJ> And the best heuristic remains Quine's: we express our ontological commitments in what we are willing to quantify over. "There exists an x such that ...." expresses a commitment to a kind (a universal whose instantiations are particulars), as well as claiming that there in fact is at least one such instantiation.

 

Yes, I have heard philosophers on this list discuss "ontological commitments", but I don't find that explanation very compelling.  Perhaps you can explain why I can't commit to both "x has type y" and also "x has type z".  Interesting types are those that combine (a la flavors(tm)) with other types without causing inconsistencies.  So I tend to ignore "ontological commitments" that are not specifically explained within the context of the first type statement. 

 

JFS> See Thomas Kuhn's writings about the way science develops.  Following is a short, but useful excerpt:    https://cseweb.ucsd.edu/~goguen/courses/275f00/kuhn.html "Objectivity, Value Judgment, and Theory Choice"

 

Thanks; I'm reading it now.  Thomas Kuhn states:

 

The oxygen theory, for example, was universally acknowledged to account for observed weight relations in chemical reactions, something the phlogiston theory had previously scarcely attempted to do. But the phlogiston theory, unlike its rival, could account for the metals' being much more alike than the ores from which they were formed. One theory thus matched experience better in one area, the other in another. To choose between them on the basis of accuracy, a scientist would need to decide the area in which accuracy was more significant.

 

That twenty-questions method is limited to about one million entities in the first twenty questions.  Since real world ontology is at least that complex, many more questions would be required to discover the full set of beliefs.  So there are algorithms, at least in principle, which would discover an individual's ontological belief system. 

 

A more generic algorithm would create questions to ask, depending on the previous set of answers back to the beginning of the interview.  But it seems to me that making a Q&A system that can ask questions about objects, events, properties, schedules, logical relationships, temporal relationships, and many other kinds of things is feasible.  That Q&A system I imagine could ask questions about each or ever situation that is practiced by some onto in the ontology. 

 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Thomas Johnston
Sent: Friday, April 24, 2015 8:41 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Surely there are no algorithms for deriving anyone's ontology. And the best heuristic remains Quine's: we express our ontological commitments in what we are willing to quantify over. "There exists an x such that ...." expresses a commitment to a kind (a universal whose instantiations are particulars), as well as claiming that there in fact is at least one such instantiation.

 

 

On Thursday, April 23, 2015 9:32 PM, Rich Cooper <metasemantics@xxxxxxxxxxxxxxxxxxxxxx> wrote:

 

Ravi and Hans,

 

Now that there are three of us, we have a group that subscribes to the belief that ontology is a mathematical description of an individual's known types of entities, plus each one's potential behaviors.  Our differences seem to be whether the ontology is generated through an individual subjective aggregation of experience, or whether the ontology is generated in some more widespread, objectively understood way. 

 

The issue seems to be how can we compute that ontology given that the individual is available for (nondestructive) reverse engineering.  If we can take what we know of ontology in the abstract, and find its wiggles, perhaps we can learn to predict the wiggles and then simulate ontologeny (!) processes versus the more well known ontogeny processes.  There may be similar underlying descriptions we can mathematize. 

 

So how can we compute an individual's ontology?  Algorithms anyone?

 

Sincerely,

Rich Cooper,

Rich Cooper,

 

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Hans Polzer
Sent: Thursday, April 23, 2015 4:16 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Rich, Ravi:

 

I don’t have much to add to this dialog, but would observe that we should “embrace” diversity – and deal with that diversity, rather than suppress it. I’m not sure that encouraging growing diversity is always good – I think that’s how speciation occurs. My own belief is that we should discourage casual diversity – diversity for the sake of diversity or out of ignorance of what others have done. I will admit that sometimes that ignorance leads to positive innovation, but it also leads to “frictional losses”, to bring physics back into the discussion a bit.

 

Regarding the use of the term commonality, I’d like to point out that it requires some implicit understanding of the types of differences and the extent of such differences across which the thing in questions is “common”. However, we rarely see anyone using the term “common” to specify the differences across which something is common.

 

Hans

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Rich Cooper
Sent: Thursday, April 23, 2015 5:57 PM
To: '[ontolog-forum] '
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Dear Ravi,

 

You wrote:

 

RS>How does math or logic help us all with different philosophic and linguistic backgrounds to help converge towards universal understanding?

 

To me, it seems that math or logic DOES NOT help us all to ... converge towards ... understanding.  Neither math nor logic helps us to understand the same things because we do not have the same experiences in our memories. 

 

RS> Can ontologies, being based on logic help us better understand neural world and mind-brain puzzle?

 

Math and logic are linear in the sense that we can use those tools to predict our near term future, or to chart the probabilities of different outcomes, and otherwise tell us something about the future given the current and the past. 

 

But people are dynamically structured, in the sense that we modify our behaviors to accomplish our individual goals.  Feedback control systems do the same thing for relatively simple mathematical structures, but again they are linear extrapolations used to squeeze the knowledge so we can find out where it leaks. 

 

The best you can say is that on some occasions, people in close groups converge to using a single word to denote a very, very simple situation.  "War" in the thirties meant WWI, then long over, not a new threat.  But in the forties, "war" supposedly still meant the same thing to everyone, but the experiences of people directly involved or affected by war were completely different than the experiences of those uninvolved and unaffected, or of Alaskan Inuit, or of Australian aborigines, or of Chinese University Professors, and many more obvious cases.  Each of these groups exist where the divergence in "understanding" is huge for critical words.  But there are many more cases that are more subtle, where the word is used by many, but the meaning is very, very different.  Hence polysemy evolved to let the divergence keep diverging. 

 

That is why I prefer to cast linguistic discussions as two agents learning how to communicate with each other, instead of casting discussions as a class of identical clones imbibing the same cool aid dictionary of a universal symbology that none of them fully understand. 

 

RS> We may have different philosophies but Newton's laws and classical mechanics go a long way for scientist and engineers; is this due to experimental verification of math that is behind them?

 

Actually, as an electrical engineer, computer scientist, and systems engineer at various points in my hectic career, I have NEVER had to use Newton's laws, classical mechanics, or any of that stuff.  I used e(t) = i(t) * z(t) and its imaginary friend in quadrature for lots of things in signal processing and electronics.  I used Fourier and Yates transforms, control theory, optimal control, directed graphs, undirected network graphs, and gazillions of other math, but I don't recall using physics or mechanics for much of anything.  I used a lot of logic in electronic logic design tasks.  I used simulation equations for many representations, but none of that is the most important math in my history. 

 

Math to model throughput, response time, multiplexing, logic, security, many other figures of merit (FOMs) get quite detailed when described in math of various kinds, but it is almost never completely linear with today's technology.  So that kind of math is far more important to my engineering associates who are not in physical mechanics, but who use math heap by heap. 

 

And, as JFS said a few emails ago, even physicists don't agree on all that physics stuff.  Look at dark matter, or cold fusion.  Every slight difference among a group of collaborating physicists creates one or more physicist with diverging opinion from the essential theories of the remaining group. 

 

So my opinion is that we necessarily have divergence in opinions for good evolutionary reasons, and we should ENHANCE that divergence at least until we understand it in full.  All progress has been made through divergent cracks in the infrastructure of that era's "common thoughts(t)". 

 

RS> A note on your exhilaration about brain being a wonderful machine, and certainly hope evolving - how did brain-mind of Mammals evolve, (we know that Aves also have some superb capabilities) and homo sapiens the best so far but universe probably (and most likely) has beings with mind-brain-consciousness billions of light years ahead of us? If we do not understand inter-species communication, how will we understand communications - among different alien life (forms)?

 

We have some small insight into a few other species, such as the work at Georgia State about primates and communications lessons learned.  There is also work (but I am not familiar with the details) of communication among wolves, dogs, crows, dolphins, parrots, whales, and many other species. 

 

But the problem, IMHO, is that each species in a conversation lacks the basic experiences and neural wiring of the other species.  Researchers call that topic "embodied intelligence". 

 

I can't hold my breath and explore the ocean rim like the dolphins do, and they can't operate mechanical and electronic equipment like I can, nor can Narwhales vote.  So our advances on that front have been really slow, but with new knowledge gradually accreting on the journal floors. 

 

Sooner or later there will emerge a pile large enough to bring us new knowledge of other species. 

 

RS>Rich - I have not given enough thought to the relationship between physics - math (logic) and philosophy hence the ambiguity. Any clarity would help.

 

For that question, I am probably not the best choice.  As I pointed out above, I have used physics very sparingly since college.  I consider math and logic to be descriptive of systems I want to understand, develop, or modify.  For that reason it is useful.  But for philosophy, I have seldom found intriguing enough philosophical questions to interest me.  You may get better responses from Matthew West, or John Sowa, or one of the others who are more interested and invested in the philosophical details. 

 

Sincerely,

Rich Cooper,

Rich Cooper,

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Ravi Sharma
Sent: Wednesday, April 22, 2015 11:55 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

Rich

 

Perhaps better choice of words for "universal understanding" could be "common" understanding or something else that implies agreement on the concept by many.

 

What I wanted to convey in the last sentence of communication was that perhaps there was a way for people to agree on understanding topics such as Physics. What is Physics? It is about description of nature of physical universe. Things about mind-brain and metaphysics are more complex or yet to be developed to the extent to which some math helps us understand physics today.

 

We may have different philosophies but Newton's laws and classical mechanics go a long way for scientist and engineers; is this due to experimental verification of math that is behind them?

 

I am looking at partitioning some parts of physics where Math can help many of us to agree on the  range of validity. Is it the mathematics (which I presume is based on Logic and or "imagination" or Concepts) that makes understanding more agreeable - often backed by measurements / experiments?

 

Rich - I have not given enough thought to the relationship between physics - math (logic) and philosophy hence the ambiguity. Any clarity would help.

 

A note on your exhilaration about brain being a wonderful machine, and certainly hope evolving - how did brain-mind of Mammals evolve, (we know that Aves also have some superb capabilities) and homo sapiens the best so far but universe probably (and most likely) has beings with mind-brain-consciousness billions of light years ahead of us? If we do not understand inter-species communication, how will we understand communications - among different alien life (forms)?

 

Can ontologies, being based on logic help us better understand neural world and mind-brain puzzle?

 

Regards,

 

On Wed, Apr 22, 2015 at 6:44 PM, Rich Cooper <metasemantics@xxxxxxxxxxxxxxxxxxxxxx> wrote:

Ravi,

 

Can you describe in much more vivid detail what you mean by your question:

 

How does math or logic help us all with different philosophic and linguistic backgrounds to help converge towards universal understanding?

 

Why do you think that "universal understanding" exists?  Perhaps there is only "individual understanding".  How would we be able to detect cases of "universal understanding" to distinguish them from "individual understanding"?

 

In my opinion, we only converge with the groups of people we interact with on a regular basis.  But we never converge for the sake of converging.  There must be an individual motivator to join a specific group.  That motivator tends to be strong in some people for some groups and the inverse for others.  But there is no good enough history database to really collect actual data on the hundreds of years of written history behind us.  But experiments like that could be done more easily now. 

 

So we can only sigh at the lack of history details.

 

Sincerely,

Rich Cooper,

Rich Cooper,

 

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Ravi Sharma
Sent: Wednesday, April 22, 2015 2:22 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Watch out Watson: Here comes Amazon Machine Learning - ZDNet - 2015.04.10

 

John

YES -

1.    All our recent or useful discoveries and products are based on engineering which are ultimately dependent on physics approximations. Physics attempts to include life sciences phenomena but not yet convincingly till we can synthesize Life reliably! But otherwise physics is attempt at description of at least non-life matter.

2.    Scientists / Engineers know their models are based on Range of Validity and approximations related to desired accuracy, deviations from mean, etc.

3.    Reality and truth get us into the fuzzy areas where knowledge of how the brain works could help us better define the context or meaning. All Cosmic skylight (e.g. at night) falling on retina - does it describe reality? What kind?

o  when individual photons from different sources impinged on retina but actually originated from different objects at different times some of which in our local-time may not even exist now.

o  how long after photon entered retina - i.e. to individual subject's brain processing time?

o  as believed in some philosophies that what appears in senses is not-real the reality is Only One.Thomas Johnson's description in email thread: that Being is One (and so an explanation of Being should be one) it goes earlier to Parmenidian - centuries earlier than 600BC.

o  your earlier comments relating to models of objects perceived by individual brain and connectionism and including referenced URL- your work with Majumdar.

4.    Now my Question - How does math or logic help us all with different philosophic and linguistic backgrounds to help converge towards universal understanding? At least Physicists understand Relativity and Symmetry models through mathematical "language"?

Regards,

Ravi

 

On Wed, Apr 22, 2015 at 12:46 PM, John F Sowa <sowa@xxxxxxxxxxx> wrote:

On 4/22/2015 2:45 PM, Thomas Johnston wrote:
> But two theories are not better than one, as regimented attempts
> to understand things. I think the underlying intuition which pushes
> physicists towards a unified theory...

Tom, physics is the *worst* example.  Almost nobody ever uses the
most general theories.  For any particular example, they *always*
use a special-case approximation that is tailored for that example.
And most of them, even for the same project, are *inconsistent*
with one another.

Physicists have known for over a century that Newtonian physics
is only an approximation, but it is still the most widely used
theory.  But even then, there are huge numbers of special cases
of Newtonian mechanics:  supersonic fluids; subsonic fluids;
turbulent flow; viscous flow; incompressible fluids (which really
aren't).  The biggest examples are the incredible number of
approximations for computing the global weather -- different
versions for multiple levels of the atmosphere, different regions
of the earth, different terrains, geographies, ocean currents,
times of day, seasons of the year, etc., etc., etc...

The total number of widely used approximations is in the thousands.
The number of detailed approximations is in the billions -- every
engineer for every project takes a large number of general-purpose
approximations and specializes them for different parts of the project.

Every large system -- ranging from your cell phone to your car to the
trains, planes, and road systems you use every day -- is based on a
large collection of mutually inconsistent approximations to the basic
laws of physics -- all of which are *known* to be false when pushed
to the limits.

Fundamental principle:  The human brain is the most complex natural
system known.  It is far more complex than the global weather, the
Large Hadron Collider, or the global collection of all the human
constructions on earth.

Analogy:  The Greek theories of the cosmos by the pre-Socratics
are closer to modern physics than any current theory of the brain
is to the way it actually works.

John

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