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Author Topic:   Current status/developments in Intelligent Design Theory
Andya Primanda
Inactive Member


Message 91 of 112 (223710)
07-14-2005 8:34 AM


Harun Yahya snubs ID?
Well I think someone else wants to come out of the ID big tent.

Harun Yahya, in a recent article, calls the ID movement 'another one of Satan's distractions'

http://www.harunyahya.com/new_releases/news/intelligent_design.php

Quotes:

quote:
In the United States in the second half of the 1980s, a theory known as "intelligent design" was launched against the theory of evolution, maintaining that all living things came into being not by chance--as Darwinism maintains--but as the result of an "intelligent design."

quote:
"Intelligent Design" Is Another of Satan's Distractions

In rejecting one false claim such as evolution, one must be very careful not to fall prey to another of Satan's snares. One of Satan's main objectives is to prevent the recognition of Allah by any means possible, and to cause people to ignore His remembrance.

There are those whom Satan has not been able to deceive with the concept of evolution. But if he can divert them in another direction, such as that of "intelligent design" he will again have achieved his end, in turning people away from remembering Allah.


-----

One of my regular Islamic creationist opponents use the handle 'Intelligent Design'. I can't help but feel sorry for this guy, him being a staunch supporter of HY but HY then criticizes the term 'Intelligent Design'...

This message has been edited by Andya Primanda, 07-14-2005 08:36 AM


  
mick
Member (Idle past 3920 days)
Posts: 913
Joined: 02-17-2005


Message 92 of 112 (224243)
07-17-2005 3:44 PM


discovery institute blog
I'm still searching for cutting edge ID research.

Readers of this thread may be interested/irritated/bored by the blog, Intelligent Design: The Future run by the Discovery Institute. It appears that their imagination is still largely exercised by the existence of the bacterial flagellum.

Mick


  
Brad McFall
Member (Idle past 3967 days)
Posts: 3428
From: Ithaca,NY, USA
Joined: 12-20-2001


Message 93 of 112 (224262)
07-17-2005 5:10 PM
Reply to: Message 81 by GDR
07-11-2005 1:52 PM


Re: Intelligent Design winning over Catholic Church
quote:
The question of how those mutations occurred is not part of Darwinism, once again, as I understand it. The question of whether the mutations occurred by a "an unguided, unplanned process of random variation and natural selection", or whether there is an "Intelligent Designer" manipulating these mutations would, as I see it be another question entirely, and frankly, I can't see why science would have any position
"
on
that".

I would guess that Anglo-Saxon biologos does or did because it would have attempted to preempt any further willy-nilly Lysenskoist graft.

If one INSISTS on Kant's notion of a TREE and its divisions and growth via grafting (which there is no reason to discount from Lysenkos former discipline) then the biological trinomial can not simply NAME AWAY any claims in nature that way that might be the charm of the collector simply attempting to describe what was observed in as many subjective ways as could be thought allowing "mutations" the place of *any* change such or such not.

It IS another "question" entirely indeed,,, but that is why Gould insisted on a hierarchy of causation because as the notion of variation biometrically stood, anything,, other than a probablistic materialism makes; a divide:: in-biology: where, there may indeed be one a priori and hence justifiable, in a future logic of cladist works but without premeditated $knowledge$ that,,,, 'god did it'(as Aggasiz insisted the physicist is to supply should such speak in the reaction) without a aposteriori classification of the rank of mutations with distributions (noT knowing the proper form of the set of discrete differences) the defense (scientifically(sic!))is to "disallow" the question UNTIL remanded by the data.

To me this offensive behavior of biologists is only a problem when it obscures exploratory data analysis and this (lack) can only be remdied by better technical tools no matter how much criticism or memes are "thrown" at the problem. As soon as an IDist does a synthesis that no EVCer can quabble with the quid pro quotient can be divided even if infinte divisiblity remained all the while.

The possiblity that an adapative oversight caused a mistaken bound to be constrained where an invariant was is a real possiblity as nanotech might be able to have shown such by finding a limit to artifical selection that remands an equivelent statistical limit naturally. The defence in that game of theory would THEN have been that not any kind of graft is projectable but only those that show to what extent economic gains from the structure of evolutionary theory can be gain said and made a bottom line. The words species and genus would not reply sensu stricto as logos has the last word. But I would agree it is not science but instutional science and currently wrongful divisionary pedagogy that has had this position.

The minute reason in the literature seems to be over the relavance of nonadaptive traits to fitness functions but I think this is a slip of Western arrogance of the past.


This message is a reply to:
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jasonlang
Member (Idle past 2337 days)
Posts: 51
From: Australia
Joined: 07-14-2005


Message 94 of 112 (224550)
07-19-2005 12:45 AM


Neural Networks, Genetic Algorithms and Intelligent Design

Warning - this post is a bit long. Please email me if interested in discussing, refuting or fleshing out any of these ideas.

just a couple of points about neural networks and genetic algotihms, and, later, a discussion on applying Dembski's logic on "No Free Lunch theorems" to creationism itself.

the basic network design which trains input set => output set (just one of the possible network configurations) is the 'back-propagation network'. It trains an arbitrary input => output mapping.

The network evolves it's own internal solution regardless of the competence of the user who defines just the inputs and corresponding outputs. Often the solution is counter to the intentions/beliefs of the 'designer' :- the system finds the underlying logic of the problem, unknown to the 'designer'. The solution may not even be understandable to the human 'designer' (eg too complex).

This internal representation (generated from a random stating state)could be said to display 'specified complexity', though there is no formal speficiation in it's design. It also could be said to display 'irreducible complexity' in that if any one connection between 2 cells is removed, then the network as a whole won't function as 'designed'.

There is also work being done in using genetic algorithms in the training of neural networks. The weights between neural cells become the 'genes' of the algorithm. With this technique, neural networks which might have taken tens of thousands of iterations to 'converge' on a solution can take only hundreds of genetic algorithms generations to find an acceptable solution. (showing the power of evolutionary ideas) Also, this combination of NN/GA programming has 2 other benefits -

1. the network can jump to solutions which never could have been considered using only the small increments of backpropagation system.

2. the output from the neural network can be used as input into some type of fitness evaluation/environment sim, allowing us to evolve the network with defined inputs but no need for defined outputs! Also, part of this 'undefined output' could be fed back into the inputs, thus evolving a loop/memory system without the need for any 'designer' to specify how this memory works - eg undefined output and only a partially defined input. This would evolve to maximise survival, but need not be explicitly specified, or known. Also, each time we ran the same system, different systems would evolve, showing that there's more information being generated than just the fitness function could explain.

So, as far as 'Intelligent Design' in these artificial systems is concerned (which have been created by intelligent agents, i.e. us) we have absolutely no idea how they operate, even though we have 'designed' them.

Dembski and No Free Lunch
-------------------------
Dembski uses the 'No Free Lunch' theorems to 'disprove' that evolution could have occured. Basically, his argument is that NFL is just as applicable to biological evolution as it is to genetic algorithms on a computer. I think it is possible to show that NFL is just as relevant, or more so, to ID as it is to ToE.

NFL states that any genetic algorithm is equally good as any other (including blind chance) when averaged over all possible fitness functions. The fitness function is comparable to the combination of the laws of physics and the environment.

So, for biological evolution, NFL could be restated as, no possible systems of evolution is better than any other, when considered over the entire spectrum of possible laws of physics and possible environments.

Notably, research has shown that NFL doesn't hold true for 'co-evolving' systems: i.e. systems in which the solutions evolve in tandem with either the fitness function or other features of the algorithm itself.

It would seem that biological systems are co-evolving systems: the fitness function changes in response to changes in the organism, landscape, form of the chromosome, etc. Systems with better evolutionary potential (eg 2 sex organisms) would have out-competed others over many generations, especially as the environment changed.

With biological systems the 'solutions' (eg genes sequences) are insepearable from the 'algoritms' (way those genes can mutate/replicate/crossover) and the 'fitness functions' (laws of physics, environment, and how genes interact), so it is clear that bioligical systems are co-evolving. The complex creatures we see today are those whose systems for evolving (eg sexual reproduction) led to more effective fitness functions, etc.

From the main Creationist viewpoint, God created all species in finalized form, and in this form they have remained ever since. It is clear that this can be expressed in the terminology of a genetic algorithm.

Implicit in genetic algorithms is a concept of starting state, and a system by which these states give rise to later states. In a standard computer GA implementation, the starting state is defined as a random sequence. In creationism, the starting state can be defined as 'Start in the form which God had in mind for you', and the 'God Algorithm' can be defined as 'procreate, but don't change - you are already perfect'. I'll leave the definition of the starting state of biological evolution to those discussing abiogenesis, though I believe it would be a state not completely random, but not completely ordered either.

It is clear that, given any particular Creation of God, that, averaged over all possible laws of physics and all possible environments the particular 'designed' being would die almost instantly, or do very poorly in all but an infintisemal environmental subset. i.e. the 'God Algoritm' would do no better than any other possible algorithm, including blind chance. This shows that NFL is just as applicable to Intelligent Design, as it is to natural evolution, maybe more so in that biological evolution is a co-evolving system, whereas Creationism is not.

The Creationist might argue that, given God choosing a different set of laws of physics, and resultant environments, he would have designed the creatures diffrently, to match. This does not, however, change the above point - the newly 'designed' creature would not survive in any of the other fitness functions (physics/environmental combinations) so NFL is still valid. This creationist argument would evoke the Anthropic principle (things are as they are, because they are the way they are), as well as the God-of-the-Gaps argument, neither of which is an explanation of anything.

So, the only Creationist way out of the NFL trap is 'co-creation' (a creationist version of the 'co-evolving' solution to GAs/biological evolution. This shows pretty conclusively that NFL is no more evidence for creation than it is for evolution.

If you read all this, good for you , this was a lot longer than i had intended.

P.S. I expect to be flamed unmercifully for any inconsistencies, factual errors, or just because ...


Replies to this message:
 Message 95 by Ben!, posted 07-25-2005 6:03 AM jasonlang has not yet responded
 Message 96 by Brad McFall, posted 07-25-2005 3:55 PM jasonlang has not yet responded
 Message 97 by jasonlang, posted 07-27-2005 2:58 AM jasonlang has not yet responded

  
Ben!
Member (Idle past 333 days)
Posts: 1161
From: Hayward, CA
Joined: 10-14-2004


Message 95 of 112 (226119)
07-25-2005 6:03 AM
Reply to: Message 94 by jasonlang
07-19-2005 12:45 AM


Re: Neural Networks, Genetic Algorithms and Intelligent Design
Hey,

Just stumbled across your message... the best way to get a reply from someone is to reply to their message directly. That way they get a notification of a direct reply. Especially when you're posting in a rather old thread, to somebody who isn't visiting the board every day. :)

As for your post... you address a lot of issues, but I prefer to focus on single issues rather than address tons of issues in one post; the replies (and replies to replies) just get unmanageably long, in my experience.

Anyway, I wanted to strongly disagree with your assesment of neural networks. Artificial neural networks are designed in at least three crucial ways:

1. Choice of input (and for that matter, output)
Without doing this (or if doing it poorly), your network learns poorly--if at all.

2. Learning mechanism
There are some autonomous learning mechanisms (such as Hebbian learning), but the most "popular" (backpropogation) is COMPLETELY design-oriented. There's an external teacher, for goodness sake.

3. Network architecture
Different networks excel in solving different types of problems. If you choose the wrong architecture, you may not even get a workable solution. One excruciatingly simple example of this is that of the two-layer perceptron; if the input/output sequences are not "linearly separable", the network will fail to learn. Solving XOR is a classic example of this.

As a final note, I would love it if you can post some references to networks working with genetic algorithms. I read a paper done by collaborators of Dr. Jeff Elman (someone whose work I personally hold in very high esteem), and I thought it was a really interesting start. The paper was at least a few years old, and I'd be interested to check out any articles that you might recommend.

Thanks!
Ben


This message is a reply to:
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Brad McFall
Member (Idle past 3967 days)
Posts: 3428
From: Ithaca,NY, USA
Joined: 12-20-2001


Message 96 of 112 (226277)
07-25-2005 3:55 PM
Reply to: Message 94 by jasonlang
07-19-2005 12:45 AM


Re: Neural Networks, Genetic Algorithms and Intelligent Design
Wolfram thinks it is all about only the "size" of the inputs but he also thinks that renormalization is the way to handle infinities relative to photons. I doubt that that is merely cardinal.

This message is a reply to:
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jasonlang
Member (Idle past 2337 days)
Posts: 51
From: Australia
Joined: 07-14-2005


Message 97 of 112 (226644)
07-27-2005 2:58 AM
Reply to: Message 94 by jasonlang
07-19-2005 12:45 AM


Re: Neural Networks, Genetic Algorithms and Intelligent Design
In reply to message 95 by ben

> Anyway, I wanted to strongly disagree with your assesment of
> neural networks. Artificial neural networks are designed in at
> least three crucial ways:

Nowhere in my original post do I claim that artificial NNs are not designed, I actually use the word design several times myself.

What I meant to question was how far 'intelligent design' can be taken, given that the intelligent agent (us) in no way needs to understand what is happening internally in the network - a 'black box' situation.

I also stated is that they could be shown to exhibit both specifed complexity and irreducible complexity, but that, in this context, this cannot be taken any evidence of an 'intelligence' designer, due to the automated nature of the training process, which, ultimately defines the network.

> 1. Choice of input (and for that matter, output)
> Without doing this (or if doing it poorly), your network learns > poorly--if at all.

Choice of input/output is related to a real-world problem the human is trying to solve. If we specify a poor set of inputs/outputs then effectively we have asked the network to solve the wrong problem.
In this case we say the network has 'failed' to learn, when in fact it has learned exactly what it was given (if the network is sufficiently large). It may be that this solution doesn't generalize well due to being unrepresentative of the real-world data.

What's important is that the inputs in the training set need to be differentiable for each respective output (whether this is mathematically identical to 'linear seperability' is something I've not looked into, but would suspect to be true), and that the training set needs to be broad enough to cover all input eventualities.

The specific numerical values of the inputs and outputs are to a certain extent irrelevant. If, for example, one or more of the input values is scaled by some factor (consistent over the entire training set), then the resulting trained networks will compensate accordingly. So, there is an ability to compensate for form of input, as long as relevant information can be extracted.

This extraction of relevant information (wheat :)) from the irrelevant (chaff ;)) is automated in the BP learning process. The human designer need not know what is relevant/irrelevant when selecting input/output pairs for the training set. Trial and error could conceivably get it right, or we could make the input literally every piece of information avalable and let the NN sort out which factors actually matter, though this of course would be very slow to train.

> 2. Learning mechanism
> There are some autonomous learning mechanisms (such as Hebbian > learning), but the most "popular" (backpropogation) is COMPLETELY > design-oriented. There's an external teacher, for goodness sake.

The true designer/teacher in the system could be said to be the input/output data, not the human, because the system will learn based on the i/o pairs regardless of what the human thinks is going on. I'd hardly call a list of numbers an 'intelligent' designer, though. And anyway, what are the odds that any one human knows precisely what data is in the complete training set, for non-trivial examples?

> 3. Network architecture
> Different networks excel in solving different types of problems. > If you choose the wrong architecture, you may not even get a
> workable solution. One excruciatingly simple example of this is > that of the two-layer perceptron; if the input/output sequences > are not "linearly separable", the network will fail to learn.
> Solving XOR is a classic example of this.

I think linear seperability is an issue for bigger networks too, but they represent higher-dimensional spaces to be partitioned (related to number of independent inputs) and a larger number of lines to partition the space (related to number and arrangement of cells).

The 'extra lines' of the 3 neuron XOR-solving network allow it to further partition the 2D search space, thus solving the XOR problem.

This article cites some research projects related to evolving network architectures (see section 2: pages 2 - 4) :-

http://citeseer.ist.psu.edu/cachedpage/634490/1

Evolved network architectures can apparently outperform hand-written ones. It wouldn't take a very complex genetic algorithm to evolve from one neuron to the 3 neurons (not counting inputs) required for the XOR function, and the user of such a NN-GA wouldn't have to even know what the final architecture was.

This message has been edited by jasonlang, 07-28-2005 10:53 AM


This message is a reply to:
 Message 94 by jasonlang, posted 07-19-2005 12:45 AM jasonlang has not yet responded

Replies to this message:
 Message 98 by mark24, posted 07-27-2005 3:48 AM jasonlang has responded

  
mark24
Member (Idle past 4129 days)
Posts: 3857
From: UK
Joined: 12-01-2001


Message 98 of 112 (226647)
07-27-2005 3:48 AM
Reply to: Message 97 by jasonlang
07-27-2005 2:58 AM


Re: Neural Networks, Genetic Algorithms and Intelligent Design
Jason,

Why are you replying to yourself?

You don't even put the name of the person you are replying to at the top of your post, making it impossible to follow any kind of developed argument.

Mark


There are 10 kinds of people in this world; those that understand binary, & those that don't

This message is a reply to:
 Message 97 by jasonlang, posted 07-27-2005 2:58 AM jasonlang has responded

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jasonlang
Member (Idle past 2337 days)
Posts: 51
From: Australia
Joined: 07-14-2005


Message 99 of 112 (226886)
07-27-2005 7:56 PM
Reply to: Message 98 by mark24
07-27-2005 3:48 AM


Re: Neural Networks, Genetic Algorithms and Intelligent Design
whoops sorry was meaning to reply to msg 95 not 94, sorted now thanks

This message has been edited by jasonlang, 07-28-2005 10:59 AM


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CK
Member (Idle past 3062 days)
Posts: 3221
Joined: 07-04-2004


Message 100 of 112 (322880)
06-18-2006 11:32 AM


Bump - so what is happening at the moment?
Came across this old thread - ID supporters check out message 1 and then let know what's going on.

Edited by CK, : No reason given.


Replies to this message:
 Message 101 by CK, posted 07-13-2006 5:09 AM CK has responded

  
CK
Member (Idle past 3062 days)
Posts: 3221
Joined: 07-04-2004


Message 101 of 112 (331373)
07-13-2006 5:09 AM
Reply to: Message 100 by CK
06-18-2006 11:32 AM


Crashfrog the all-seeing
Crashfrog writes:

23-Jan-2005 03:43 PM IP Logged
...tumbleweeds....
I predict that this thread will comprise entirely of "bumps" and "hello? Anybody posting here?" messages.

Is this thing on? Anyone want to tell us what cutting edge work IDers are upto at the moment?

Edited by CK, : No reason given.


This message is a reply to:
 Message 100 by CK, posted 06-18-2006 11:32 AM CK has responded

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CK
Member (Idle past 3062 days)
Posts: 3221
Joined: 07-04-2004


Message 102 of 112 (443035)
12-23-2007 2:01 PM
Reply to: Message 101 by CK
07-13-2006 5:09 AM


it's back!
So it's 2007 coming into 2008 - any ID's willing to step up and take a stab at what's set out in post 1?

Roll up roll up!


This message is a reply to:
 Message 101 by CK, posted 07-13-2006 5:09 AM CK has not yet responded

  
Motorhead
Junior Member (Idle past 4836 days)
Posts: 2
Joined: 01-30-2008


Message 103 of 112 (452340)
01-30-2008 3:58 AM


There is no new developments in ID, since it simply is religion and nothing more.

I can't believe people actually have to ask, there is no debate. Creationism/ID is not science, and no matter how hard they try it never will be, period.


Replies to this message:
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Blue Jay
Member (Idle past 1632 days)
Posts: 2843
From: You couldn't pronounce it with your mouthparts
Joined: 02-04-2008


Message 104 of 112 (453948)
02-04-2008 8:25 PM
Reply to: Message 103 by Motorhead
01-30-2008 3:58 AM


Motorhead, be careful with blanket refutations like that. There are recent "scientific" developments in ID. There are people out there who use the scientific method to obtain results in support of their idea. The problem I often run into is that their results do not exclude alternative interpretations (which is a requirement for forming a theory). However, some of them come up with stuff that I have trouble refuting with my primitive knowledge.

One such example comes to us from John Baumgardner, PhD, from the Institute for Creation Research (ICR). It's called RATE (Radioisotopes and the Age of The Earth), and consists of several papers dealing with geological dating techniques. It concluded in 2005. That's about the most recent real research I've seen. It's supposed to be definitive proof that radiometric dating doesn't work. I don't know enough about geology or spectrometry to actually refute it. Maybe y'all could take a look at it and tell me what you think.

http://www.icr.org/rate/

My understanding is that John Baumgardner (PhD) for the ICR had reputable spectrometry centers date several samples of rocks from the Grand Canyon, and that the dates produced varied wildly, even between samples that were supposed to be from the same geologic stratum.

A man named Kirk Bertsche, claiming to be an AMS physicist, made a sharp rebuttal, claiming that the variation in dates were due unavoidable contamination sources, but Dr Baumgardner turned it around and said that Kirk Bertsche was clearly a novice. It then becomes a scenario of credibility--"who do you believe: me or him?"--and isn't actually about the subject at hand. What I find intriguing about this tactic is that Dr Baumgardner has made it explicitly clear that his purpose in life is to tear down the theory of evolution. Does he expect us to just overlook this bias in determining credibility?

I haven't heard much about this project since then, so I don't know if it's already been refuted. And, I don't know if it fits your (Silent H's) criterion of "recent." And, I'm not an ID proponent, so I'm pretty sure I don't fit your criterion for posters, either. Still, I'd like some feedback from other people.

Edited by bluejay, : No reason given.


This message is a reply to:
 Message 103 by Motorhead, posted 01-30-2008 3:58 AM Motorhead has not yet responded

Replies to this message:
 Message 105 by RAZD, posted 02-04-2008 10:29 PM Blue Jay has responded

  
RAZD
Member (Idle past 339 days)
Posts: 20714
From: the other end of the sidewalk
Joined: 03-14-2004


Message 105 of 112 (453971)
02-04-2008 10:29 PM
Reply to: Message 104 by Blue Jay
02-04-2008 8:25 PM


My understanding is that John Baumgardner (PhD) for the ICR had reputable spectrometry centers date several samples of rocks from the Grand Canyon, and that the dates produced varied wildly, even between samples that were supposed to be from the same geologic stratum.

This is easy to do for someone that knows what they are doing. Basically you are providing false information about the samples. See

http://www.talkorigins.org/indexcc/CD/CD014_1.html

for information on similar misrepresentations.

However age doesn't really have anything to do with ID and there are a number of threads in the Dates and Dating forum.

www.evcforum.net/cgi-bin/Threads.cgi?action=tf&f=3 -->www.evcforum.net/cgi-bin/Threads.cgi?action=tf&f=3">http://www.evcforum.net/cgi-bin/Threads.cgi?action=tf&f=3

Enjoy.


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by our ability to understand
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This message is a reply to:
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