Posted: Jan 22, 2011 2:28 pm
by Царь Славян
Same shit all over again. It's like you pick out a single sentence and ignore the rest. ID is a cheap trick to avoid the first amendment to the constitution, so you can sneak religious bullshit into public school. You intentionally avoid naming the designer in order to achieve this goal. Problem is, this tactic was exposed ages ago and it's not going to work. You aren't fooling anyone.
Then please do what I asked you to do.

You don't know if an invisible designer designed snowflakes. A supernatural designer. An extremely technologically superior designer we don't currently know how to detect might be doing the design. Any observation is compatible with a design claim and therefore unfalsifiable. Deal with it.
Exactly I DO NOT KNOW that. And precisely therefore, I DO NOT INFER design.

It's called the design INFERENCE, not design PROOF.

If you actually spent a second researching ID claims you would have known that, but you didn't, so you are clueless about a SCIENTIFIC THEORY you are criticisig.

The point of teh design INFERENCE is to present a REASON to INFER design. Get it? What we need to have, is a method that would give us reason to call a particular object designed. If using our method the results come in negative, as in, there is no reason to call an object designed, then we do not infer design.

Yes, an invisible pink unicorn could have still designed it. But then again, an invisible pink unicorn can do anything. But since we have no reason to ascribe anything to an invisible pink unicorn, we don't do it.

The same with design inference, if we have reason to infer design, we infer it, if we don't then we don't. And that there makes ID scientific because it can be falsified, namely there can be presented some observations that would give us reason to say that an object could be accounted for with something else.

Your fucking idiotic claim that "proteins need to bind to gtp to leave the nucleus" is a manifest demonstration of this total lack of knowledge you suffered from. I'm just happy I could contribute a little to your education.
Not proteins but RNA. And that's true in eukaryotes.

No, I asked you for evidence that ALL proteins need to bind to GTP to be considered functional. The paper you provided was a demonstration of your failure to understand the relationship between GTP, mRNA and proteins.
Your subsequent attempt at obfuscation further exposed your lack of knowledge that the Ribosome was found outside the cell nucleus.
I presented you what I considered relevant. If you disagree, then that's your porblem.

How about YOU learn the fucking language of probability theory, and supply it with a fucking proper understanding of evolutionary genetics?
I already know it, otherwise I wouldn't be telling you to learn it.

A straight out fucking lie.
Nope, and I'll do it again.

Okay, here we go again. For everyone to see. Point by point.

The ev program was modified from version 3.67 to version 3.69 so that there is a new parameter that allows one to select between the three possible methods for handling ties. The program will automatically upgrade older versions of the parameter file (evp) by adding this parameter.
Again, the same thing, he modifies teh special rule to be a new parameter, so still fine tuning the fitness function to produce a goal. This is still the place where teh intelligent agent introduces information into the program.

The ev paper did not make this claim since the phrase "complex specified information" was not used. It is unclear what this means. Shannon used the term "information" in a precise mathematical sense and that is what I use. I will assume that the extra words "complex specified" are jargon that can be dispensed with. Indeed, William A. Dembski assumes that information is specified complexity, so the term is redundant and can be removed.
This is why it's painfull to read what this guy writes. He doesn't even know what Specified Complexity is, and thinks that it's just a bunch of redundant words.

This statement represents a fundamental misunderstanding of the paper. The phrase 'for free' does not appear in the paper. The claim in the ev paper is that the information appears under replication, mutation and selection, commonly known as 'evolution'. It is not for free! Half of the population DIES every generation! In the standard example given in the paper, to gain 4 bits required the (virtual) deaths of some 32 organisms x 704 generations = 22528 deaths. On average that's 22528/4 = 5632 deaths per bit. Note that theoretically one could get 1 bit of information with only 1 binary decision. So the evolution is, not surprisingly, a rather inefficient information generating mechanism. No biologist has ever claimed any differently!
Note that "from scratch" does not mean the same thing as "for free". "From scratch" refers (obviously) to the initial condition of the genome which is random in this case so that Rsequence = 0 bits. That is, there is no measurable information in the binding sites at the beginning of the simulation. "For free" would mean "without effort", and the paragraph above demonstrates that there is quite a bit of effort and (virtual) pain for the gains observed.
For free of from scratch is irrelevant. A better and more precise statement would be, that Schneider claims to get more information from his program than random chance would produce in the same period.

The No Free Lunch theorems are not relevant to the problem, so Dembski is using misdirection. Indeed this is obvious from inspection of the ev program and its results: it works as claimed. A careful worker would not make this mistake because they would take the time to understand the theorem before citing it.
The NFL theorems are relevant to the problem since we are dealing with algorithms here. And the NFL theorems claim that no algorithm outperforms any other averaged over all fitness functions. The reason for that is that the algorithm itself doesn't produce any information, it's comming from the fitness function.

This is not unreasonable because it happens the same way in nature. For example, if a bacterium has severe mutations in 5 ribosome binding sites, then that means that 5 proteins will not be made. Is this fatal? Not necessarily. Suppose that the 5 proteins code for processing 5 different sugars. If the sugars are not in the medium that the bacterium swims in then it will make no difference. But when the bacterium comes to a solution where one of the sugars is available, it will be unable to eat. If that is the sole carbon source, it will starve (surely a 'mistake'!) and bacteria that have mutations that correct a site or already have a correct site will survive. A simple way to account for this is to count the number of mistakes. It may be that a highly beaten up genome (with 100 mistakes) is pretty much as badly off as one with only a few mutations, so maybe one should take the logarithm of the number of mistakes. But a logarithm is a monotonic function of its argument, so this will not change the selection order and therefore would not affect the evolution (other than wasting computer cycles). Surely it is not reasonable to say that a creature with 5 mistakes will survive better than one with 2 so to match the natural situation we should pick a monotonic function. That's what I did in the paper.
Yes it's the same thing in nature. So the nature is set up to find such solutions by evolution. Fine.

So the answer to "Who or what determines the number of mistakes?" is: Just as in nature, the number of genetic control systems that if controlled would give an advantage determines the number of mistakes.
So, in nature the fitness function of nature decides, in a computer program, the fitness function of teh program decides. OK.

I generally do not find 'fitness' to be a useful concept. In the ev program there is no fitness function and the word 'fitness' does not appear in the paper. Unlike most biologists I dispense with the concept of a fixed 'fitness function'. A 'fitness landscape' is too rigid since it does not describe the effects the organism itself may have and it does not account for a changing environment (In addition, fitness is generally depicted as 2 dimensional, which causes severe conceptual problems, see ccmm). At best there is only 'relative instantaneous fitness' in a changing environment. That is, whoever makes the fewest mistakes in the current environment is likely to survive.
Well you can call it relative instantaneous fitness, but it's commonly known as the fitness function. Calling it any other way doesn't make it into something else.

Counting of the number of mistakes matches what happens in nature, as described above. I only claim that the ev simulation matches what happens in nature in essential points. No smuggling occurs.
Yes, that's what happens in nature. But this program was set up to perform this way. So the question is, was nature also?

If Dembski finds that this produces information, then he will understand that the simulation shows that information can be generated in nature solely by replication, mutation and selection. That is information as mathematically defined by Claude Shannon can be generated by Darwinian evolution.
No, because Schneider is the one who put the information into the fitness function for the algorithm to extract it.

Blind assertion.
We all await the evidence.
It's in the paper. Deal with it.

We could ask ourselves "What is the probability that the genomes of extant life would fall on a hierarchical tree of life?"
For example, Human are postulated to descend from a common ancestor we whare with Chimpanzees. Chimpanzees and Humans are postulated to descend from a common ancestor we whare with Gorillas. Etc. etc.
So we look at the sequenced genomes for a line of organisms we postulate are related by common descend in a specific order, and we calculate the probability that their genomes sequences should happen to randomly align with this postulated tree of life. We go on and do this for every genome of every organism we have sequenced, and we happen to find that their genomes fall exactly as expected on this postulated evolutionary this tree of life we derived from comparative anatomy, biogeography, developmental biology, embryology and paleontology.

What are the fucking odds that the genomes of every organism we sequence, should happen to fall in perfectly with the predicted evolutionary tree of life? Incomprehensibly infinitesimal. (Go back and find the fucking paper if you want the actual numbers, I can't be bothered doing all your work for you).

There it is, the statistical test that demonstrates common descent. Evolution happened. GET OVER IT.

** I should add here that the actual statistical test is a little more complicated than the way I have explained it. They also compared the accepted evolutionary model with different scenarios like multiple independent origins with convergent evolution etc.
Read the actual paper.
That doesn't mean that any of the organisms are related. Yeah, it's a small probability that they would all align. That's true, but from that it does not follow that they are all related. Maybe they were designed that way?

No, I don't belive people came from rocks. I don't know how life began, but I have never even seen a hypothesis that suggests people sprang out of rocks.
I didn't say sprang from rocks. But minerals melted from rocks, and slowly formed first self replicating molecule and over billions of years formed a human. So basicly, people came from rocks. That's what some people believe.

Combination? Please elaborate...
Combination is when you take two things, like two statements and combine them together.

Here's an example.

a.) I went to school today.
b.) I walked down the road.
c.) I went to school today and I walked down the road.

See, I didn't equivocate these two statements. I didn't say they were the same. I simply combined them into one larger statement. There you go, you learned something new today!