Information and Genetics

Fred:Do you deny the fact that tree rings do, in fact, confirm - accurately - the precise years of catastrophic events? When I was little, they had a cross section of a tree trunk in Jesse Jones park, a park in southeast Texas. You could see the precise years - and count them - when hurricanes struck. It was right there, and clearly visible to the naked eye. Anybody who can count can quite clearly match it up. If there was some big "tree ring fraud", don't you think that some nice forest ranger would have exposed it by now?Finally, about your "tree++" argument. First off, as was pointed out, you can simply expose the tree to different growth conditions in its life, and it will code that information by how much it grows in its rings. However, you seem obsessed that there has to be intent to leave information, to actually leave that information. That is nonsense. Police work would be physically impossible if that were true. Do you think a bank robber means to leave his footprint at the crime scene, or a murderer leave a drop of blood under the victim's fingernails? Of course not. There was no intent involved. It was a side effect of things that happened. When a large tree falls, it fells the underbrush beneath. Flying over a forest, you can use gaps in the woods to determine where large trees have fallen. That's information. Did the tree mean to give you information? Of course not.I could go on for weeks here... information is left by processes *all the time* without intent.------------------
"Illuminant light,
illuminate me."

My apologies; I misinterpreted the intent of bringing up tree rings in reference to a code, and was thinking that it was in reference to the fact that the information present in tree rings makes clear a much older age than YECs allow (the standard discussion about tree rings). After rereading the initial post on the subject, that clearly isn't the case.Trying again at understanding what you're trying to claim, it would appear that you're trying to argue that information that is able to represent something else is a "code", and that such a thing cannot come into existance without design. Is this correct? (added in to make sure that I'm getting it right this time).If that is your belief, I think you should check out programs, starting from Tierra up through AvidaTierra, the first, began with a "primitive" self replicator, and let it go from there. The initial self-replicating code was just a short program that copied itself. However, through random modification and the simple selective forces of A) space the program takes up, and B) how much CPU time it gets, all sorts of novel forms arose, from parasites who would modify other programs to copy themselves (like a virus) to pieces of code that were far more efficient than the original copying program. No one designed these things; they came about on their own, and in the end had essentially no resemblance to what was initially put in.Since the initial release of Tierra, programs have taken it one step further: starting with random data. While it takes huge amounts of computer time before anything self-replicating comes about, invariably random chance leads to a very simple self replicator. Usually, it's fairly hard even to describe the first ones as much of a self replicator - it's generally more of a cyclic cascade (something akin to stable formations in cellular automata). However, eventually a true replicator invariably forms. No matter how poor or inefficient of a self-replicator, the process always launches into the afore-mentioned spread of different forms of artificial life.

I'm sorry, but life is an adaptive self-sustaining cycle. To term it as having a "goal" involves assuming intelligent design - you're assuming what you're trying to prove, which is a logical fallacy. And yet, adaptive self-sustaining cycles exist everywhere in nature - just not with the particularly highly adaptive structure that life has developed. As examples, an unadaptable self-sustaining cycle will occur if you randomly modify bits in a computer chip's program memory space - eventually, it will get a loop that will jump back to an earlier point, and keep looping (in enough time, however, cascading effects can occur, but that's another story). An adaptive self-sustaining cycle is something such as a large fire (or, for a more extreme example, the sun's fusion); you can destroy a small part of it (such as stomping out a patch of dry leaves in a fire), but if any of it remains, it "fixes" the damaged area back to the cyclic mode (in the case of fire, the heat from the fire enables the breaking of bonds in the fuel for oxidation, which creates more heat... etc). It can manage a level of adaptation to adversity. Cycles range from almost no adaptive ability to extreme adaptive ability.In short... you're defining life in a way that already assumes what you're trying to prove here. That's faulty. Adaptive complex cycles exist everywhere, with varying degrees of adaptive ability. Life is just one that has a particularly high level of ability to adapt. There is only a "goal" if you artificially insert intelligence into the picture.Your analogy of a computer program is faulty because it doesn't add in any of the things that we see in reality. It doesn't have other computer programs competing for memory and CPU space. It doesn't have "archived" records of simpler versions of the programs currently running on the system, with older backups showing the more distant records. The equations don't help the programs get more CPU and memory. Etc. If it was like that, *then* it would be like reality.------------------
"Illuminant light,
illuminate me."

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Secondly, you only want to use the word "goal", and you are reluctant to stay away from the definition of "result". A self sustaining cycle has the goal of maintaining the cycle.

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So fire has the goal of maintaining the fire? Nuclear fusion has the goal of maintaining nuclear fusion? That's a rather twisted definition of "goal".

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Not quite sure how this is relevant. I am not arguing that the different DNA systems can't change, I am arguing that they cannot come about naturally. You could technically argue that the Sun has apobetics, but this is only due to its' inherent physcial properties. The DNA's origin had little, if anything, to due with its' inherent physio-chemical bonding abilities.

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And what do you base that last line on? Your inherent assumption of a designer, correct? Please understand: We view both of these as having the same reason behind their existance: to quote you, "inherent phyiscal properties". You consider adaptive cycles like the sun's fusion forming from gravitational compression of a cloud of gas, or a fire spreading across a whole forest from a single lightning strike as being due to inherent physical properties of the universe - but not DNA and life. We (those who believe in abiogenesis) disagree. Namely, because, from our viewpoint, it fits 100% perfectly into observed phenomina and the principles of chemistry. You may disagree. But please realize that your disagreement is due to your interpretation of the available evidence, and not due to some sort of inherent property of life. The fact is, clearly observable adaptive cycles exist, and can form from much simpler phenomina. The only thing in question is whether *this* particular adaptive cycle did.

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While computer programs and the DNA are information systems, the purpose behind the existence may be very different. For example, the purpose of a computer program may be to solve equations, to store information, etc.. We can draw inferences about what its' purpose is by what it does. In the case of the DNA, living organisms obey their instincts to survive which is controlled by the DNA. We could say then that the DNA is designed to survive and reproduced.

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You really ignored what I said there. Your standalone computer program example doesn't reflect the real world. Your standalone computer program example would correspond to a world where people never reproduced, where nothing - not microevolution, not macroevolution, etc - occured. Where there was no past history of similar forms, getting more different the deeper you dig. All of these things are false in this world that we live in.If our world was like your computer programmer example, of course, scientists would believe in a designer. They *did* believe in a designer, until they realized that the world does not fit into the model that you presented for your theoretical computer program. Organisms *do* change as they reproduce - even creationists acknowledge this (they just assume limits on this ability). They *do* form different, quite similar forms, which do get more different the deeper you go (creationists have many arguments with this, and tend to focus on the 1% of examples that aren't perfect in this manner but are well explained for other reasons, ignoring the fact that they have 99% to go in addition to refuting the explanations for the 1% - you can't just refute the special cases, you need to get the general case!)

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In the origin of life event, however, there was no natural organizing force. There is no tendency for random chemicals to align themselves in such a way as to make life possible.

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In the origin of a star, there is no organizing force needed more complex than gravity (as easily represented in particle physics simulations). In the origin of a fire, there needs be no more complex of a force than a single input of some raw energy. That energy can come from one of innumerable natural sources of energy, as you may well know (if you want, we can trace back a couple... ).

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How then can material processes create a non-material reality, like information (or at least the type of information Gitt is talking about).

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That's back to something that was already discussed: Gitt makes an artificial distrinction between types of information, because we know very well that processes other than life leave information behind. For example, small creeks and rivers which are based on snow-melting runoff desposit seasonal layers (varves). That's information. A volcanic eruption leaves behind a layer of ash. That's information. A meteor leaves behind a crater. That's information. Etc. Gitt is merely defining as distinct what he wants to prove is distinct - it's circular. I have just presented examples of processes that self-organize to adaptive self sustaining cycles from simpler situations (I can get you plenty more if you'd like). Why do you draw this artificial distinction when it comes to life?

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For example, today a definite information system is present in the DNA that can be understood by the sender (the parent) and recipient (offspring).

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Would you, for example, describe fire as sending a message from the sender (a chemical reaction) to the recipient (other flammable molecules)? Or would wou describe fusion as sending a message from the sender (four hydrogen atoms merging into a helium atom) to the recipient (other hydrogen atoms which are not yet at a temperature capable of allowing fusion)? You're reliant on the assumption that there's something more "special" here than just chemistry for your "message" analogy. Please understand that the people you are debating with view the reactions in DNA as merely complex chemistry. You are assuming that there is some sort of "message" in the DNA distinct from the carrier (the DNA itself). We disagree.

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However in the origin of life event, there was no tendency for chemicals to align themselves in a way that produced life. There was no basis for this pattern or organization within the matter (like in stars and ice), but rather it had to be imposed on the matter.

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First off, you're repeating a common creationist mistake about abiogenesis - that there was some sort of special "event" in which life occured. Supporters of abiogenesis typically do not believe this. The standard view for abiogenesis involves a natural energy source (such as an oceanic geothermal vent) that provides highly reducable chemicals into the system - in addition to lots of simple carbon-based matter. In such an environment, addition polymerization is quite a simple process. Some carbon chains will be more likely to be stable in the long term than their predecessors, and those will accumulate. If one were to become functionalized in a way that was likely to functionalize others, in its particular high-energy environment, it would tend to functionalize much of the remaining molecules. If other functional groups tend to, say, give it more ideal properties for remaining close to the entrance to the vents, or to be able to help functionalize molecules that had drifted further way, these would be likely to spread more. Etc. There is no particular "moment" - and in fact, in the beginning, it can hardly be viewed as "self-replication", just simply increasing the likelyhood of molecules like themselves forming in the vent. It's not really a stretch. Polymerization and functionalization occur every day in rather simple conditions in oil refineries and chemical plants. In fact, apart from things like platinum catylists designed to speed up the reactions, you'll find that the conditions inside a refinery are quite similar to those in a deep sea vent - except that the vent has a much wider variety of chemical possibilities to work with.

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If you are saying that I need to give a relevant computer analogy to natural selection, then I misunderstood your last post, and I apologize.

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That is correct - no problem, though. You gave a computer analogy before, but it wasn't a fair analogy, because it doesn't describe the way things are observed in real life.

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However, as you say, the computer program could change. I am not arguing with this. However the language convention used by the computer system could not have resulted by soley naturally processes, because the convention involves 'forward thinking' or preestablished knowledge.

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Not true. You should read about the progress that has occurred in alife thusfar. Self replicating behavior has occurred in random sets of executing data. And it's hardly "front-loading". All the person who writes the alife program does is write an environment in which code can execute - i.e., a "virtual machine". The code that's running is as random as grabbing marbles from a bag. You could, of course, say that this model represents one in which God creates a universe, and then abiogenesis occurs on it's own.

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For example, a Ducthman would not understand the meaning of the word 'eraser'. I would know it because I use the English language. Similarly the genetic code works this way. Once an entity can make sense of it and use it, then it is able to replicate, maintain the DNA, etc.. However if there was a time when the DNA code did not exist, then the matter could not act in a way to produce life, because it would not be acting by the rules of the DNA language convention. In fact, the DNA language convention would not even be present, so no information could be understood.

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If you're trying to argue that DNA is irreducibly complex, that's not true. There are many much simpler self-replicators than DNA, such the SunY replicator (only 3 subunits long!), and even bovine spongiform encephalopathy (which is just a malformed prion). Of course, the earliest versions need not even be true self-replicators, only catalysts that tend to encourage the formation of more chemicals roughly "like" them.

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Saying that the DNA code could result from inherent physical properties of matter would be like saying that random chemical reactions between iron oxide and plastic could produce a formatted floppy disk

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Corrected analogy: First, we need to assume that floppy disks can spread themselves and reproduce. Then would be like saying that reactions between iron oxide and plastic could produce plastic with bits of iron oxide embedded in them which tend to encourage more reactions of a roughly similar kind - somewhat closer to spreading and being able to reproduce, but hardly there. And that things that are more similar to floppy disks encourage more reactions similar to them, so that (as an example) if the iron was deposited in a way that was easily magnetized, it would be more likely to occur... etc. Before long, it's close enough to a floppy disk that it can spread fairly effectively, and outcompete simpler forms of floppy disks.... (I could go on, but I think you get the picture).------------------
"Illuminant light,
illuminate me."

Well, it depends on what you define the ability to be a "true self-replicator", as every self replicator needs input material. BSE requires a very specific type of input for "replication" - namely, a normal prion. More advanced self replicators have more leeway in their inputs; even more advanced ones become more like cells, and have the ability to break down all sorts of chemicals into things that they can use to replicate. In fact, it's a good example of why there's no single "event" for the creation of life.I always find it amazing how simple chemical reactions can lead so well toward the creation of life. For example, phospholipids inherently form into bilayer sheets; when disturbed, these sheets "roll up" into little bubbles. In short, a self-replicator which can produce phospholipids (or produce chemicals which can produce phospholipids, etc) is likely to end up an ur-cell by gaining a protective coating - allowing it to have regulated internal contents, to migrate more easily in the currents, to resist damage, etc. Of course, without surface proteins to help enable the transfer of "food" from outside the cell, it would remain dormant like a spore until its coating was damaged, when it would be able to reproduce again - but it's still an immediate advantage to the replicator on several fronts.------------------
"Illuminant light,
illuminate me."[This message has been edited by Rei, 09-08-2003]

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While it is no surprise they have found life in the back smoke-rooms of college laboratories (kind of like how the cult movie Rocky Horror Picture Show found a following despite being one dumb movie), in the real world of engineering they are not taken seriously by anyone I know

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Like MIT's AI lab? Which publishes the Artificial Life Journal, which includes papers on things like commercial applications which have begun using alife (for example, virus research. They've had some spectacular success in merging the two disciplines). Do you feel the same about alife's cousin, artificial evolution systems, which are employed in everything from aircraft engine design to vehicle modelling? Hell, I even employed one to determine whether strings are related in a piece of software for work Of course, this part of AE is more into the "natural selection" part and not abiogenesis, since when used in commercial applications, noone wants to wait for it to start. However, in research, abiogenesis has occurred in a number of systems.Of course, in even most commercial AE systems, more "information" is developed on its own throughout the course of the development. An aircraft engine may, for example, end up over the course of time twisting its skin in a way that it creates a new air bypass, even though the ability to just create a new bypass wasn't expected to either be needed, and wasn't expected to be done. Research-oriented projects often have even more impressive effects; I should track down the one (you can dl it and run it for yourself) that I saw a few years ago in which creatures only have the ability to create and adjust "muscles", "joints", and "bones" - and then impose different selective factors on them - and watch as the creatures develop legs, fins, tails, whatever, to jump, swim, or otherwise deal with whatever environmental challenges you give them. None of that is coded in - only the most basic structures.But, back to abiogenesis...

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Even in a few remote cases where they produced a workable FPGA algorithm, invariably the algorithm was highly inefficient and a noise problem.

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Huh? How did you get FPGAs into it? Yes, I've read about one case where an alife (actually, AE) system was used to program an FPGA, but usually alife is done in software.

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They do not emulate evolution because they do not permit extinction

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False. Utterly false. They do not *hard code* extinction - that would be front-loading. Extinction happens on its own. In *every* genetic algorithm, entire lines frequently go extinct. If the system doesn't contain enough lifeforms, the entire system can go extinct (I've had this happen in a couple ones that I've written) from parasitism, predation (if applicable), too much "energy" input into the world (i.e., stable organisms can't form or remain alive), etc.

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they invoke unrealistic truncation selection

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Which one are you describing in this way? There are dozens of types of genetic algorithms. Usually the ones designed to optimize a "product", used in commercial applictions do, but only some of the ones that are more research-oriented do. Some alife setups compete organisms head to head, some put them in a virtual "world" to do whatever they will (enabling them to interact or not), some evaluate them individually and compare results, etc. Plus, this has no effect on abiogenesis.

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and they require intelligence to stop the program if they produce anything useful.

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Actually, nothing needs to stop the program. It can keep going forever. Depending on when you look at it, you'll see different things. Of course if you want to look at what it has done, *go ahead*. But you don't have to stop it at specific times for it to keep functioning. The only thing that is "taboo" in alife (well, at least when it comes to research) is modifying what is going on after it starts. Observe all you want, but never change anything. A properly designed research alife system declares what is "given" (i.e., whether it starts with a simple organism or whether it starts with just random garbage, etc), and then lets it go and sees what happens.

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Even given these non-naturalistic conditions, programs like Tierra and Avida still could not produce a new programming language no matter how long you run them.

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First off, if you're going to define DNA in the same category as a "programming language", you have to accept that the universe itself is one. I.e., a 4 hydrogen atoms and extreme heat placed in a location leads to a helium atom and lots of energy released. It's no more of a stretch than calling DNA a programming language, where you have more of things on the "function call" level. Things like "If this gene is being activated, produce this protein". It's far more complex, but coded in the basic programming language that is our universe.Alife systems which model abiogenesis start with a world no more complex than our universe. While I am unaware of anyone that has modeled the *same* rules as our universe (that would take a ton of CPU), they're no more complex. The most common case is to model what is called a "virtual machine" - a computer inside a computer, so that you have a controlled operating environment that won't mess up the outside operating environment. The initial "primordial soup" in such simulations is random instructions. Given enough time, with environmental "input" (i.e., toggling random bits, shifting chunks of data around randomly, etc), one virtually always encounters first cascading effects, then self replicators, then competition between replicators, etc. Parasitism and predation typically also become the norm. The first step takes the longest, of course.------------------
"Illuminant light,
illuminate me."

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Yes, I do feel the same. This is at best an exaggeration, and at worst pure baloney. Perhaps you can tell us specifically what role a GA played in the design of an aircraft engine?

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Let me repeat. If an MIT graduate was applying for an engineering position at my company (I have 20+ years designing sophisticated systems for IBM, EMC, and McDATA), and he suggested GAs as an effective tool for engineering, he would either be escorted to the door, or encouraged to dismiss silly ideas and enter into the real world of engineering. I prefer the latter - first attempt to de-program the poor lad, ie undo the brainwashing he received from those colledge professors who live in la la land.

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I hate to be blunt, but: Wake Up, Fred. Take a look at genetic algorithms and engineering:"genetic algorithms" engineering - Google SearchAicraft? How about Stanford's aircraft design group, vibration control in NASA, engine design in NASA, engine diagnostics in NASA, industry-funded studies at Michigan State University on engine optimization (crashworthiness, weight, and other factors (mostly for automobiles, but some parts apply to aircraft engines as well)), Virginia Polytechnic's development of arrangements for composite panels in aircraft, most wing design (based on the principles introduced by Hicks and Henne)... you know, I get the feeling that you have *no clue* how widespread these things are. Hell, where I work, there is a laboratory about 20 feet away from me where about 5 people work on studying components of the brain that are sliced out of MRI images by neural nets which optimize themselves via genetic algorithms. As I mentioned, *I* wrote a quick GA for a piece of software that I was working on for work for string comparisons. Why did I use a GA? Because *I* couldn't figure out any sort of simple algorithm to do the sort of optimization that I needed, but AE does a superb job at it. (The case is that of string comparisons between two unlike strings - for example, while it's easy to say that "ABCDEF" is one change off from "ABCDEG", and a harder, but still feasable algorithm can determine that "AB CD EF" is two changes off from "ABCDEF", how do you write an algorithm that can know how to tell that "CEEFAB" is representative of only two changes from "ABCDEF" (moving CDEF before AB, and then shifting the D up one letter)? The only answer that doesn't take a week and a dozen headaches to program is a genetic algorithm. Given two long strings, there is no way that a human would figure out the simplest difference between parts of it. But the genetic algorithm does a spectacular job.Hey, you want Boeing? Let's see if I can find a copy of that computerworld article that I read a couple years ago... here's a copy: Forbidden"General Electric Co. used genetic algorithms as part of a hybrid artificial intelligence solution to improve bottom-line performance in the design of the Boeing 777's jet engines." (they mention many other companies that have used GAs, and how they did it - Citicorp, Swiss Bank, Cemex, Deere & Co, GM, etc.)

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As I mentioned in my prior post, GAs are really just trial&error experiments and only rarely would provide benefits based on what an intelligent source can glean from findings of the GA

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Not true at all, as I just discussed. My program interrupts the GA after 1,000 runs, and takes whatever it has at that point. All commercial GA's work in some manner to the effect of this. While in GAs oriented more toward resesarch and bacteriological studies typically let them compete freely (which allows, in cases, less fit algorithms to survive, but in the general case the more fit ones survive), commercial applications rarely let less efficient algorithms survive for very long. Commercial algorithms typically operate in much more constrictive environments, akin to having a bunch of rats in cages, testing to see how fast they got through a maze, and then bred based on which ones got through the maze the fastest. As a consequence, commercial algorithms are generally immune to parasitism and predation, and seldom ever go backwards. The downside is that it can reduce effective parallelism.

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To say that they show that random change + selection can create complex information without an intelligent agent present is pure nonsense.

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Deny reality all you want. Here's a couple more research-oriented ones, since I've covered commercial pretty well:
http://www.his.atr.co.jp/~ray/pubs/fatm/node10.html
Boris FX | Sapphire and http://www.his.atr.co.jp/~ray/pubs/fatm/node9.html
http://www.his.atr.co.jp/~ray/pubs/fatm/node12.html
http://www.his.atr.co.jp/~ray/pubs/fatm/node13.htmlHmm, there's one I should track down to insert here... one where they were modelling viral and bacteriological properties in software for research on the aforementioned virii and bacteria... they used it to help them explain why certain irrelevant traits on the virii, and on certain species of bacteria (but less frequently in others) were sweeping through populations whenever there was an adaptation made that was a notable step forward in survivability to the environment that they were in. Can't remember the name of it, though.... there was also another one that I tried out before, which was like Karl Sims's block evolution, but had been done in a much larger environment and with much more complex models being able to develop. They had videos on their website, too, so I could just show you that. Really amazing stuff The key thing to remember when reading this is: These projects here (which are just a tiny handful that I quickly gathered - there are thousands of them out there) started with only incredibly simple "organisms". All of the complexity that you see *developed*. It was not programmed in - it developed completely on its own, due to the particular selective factors involved in the different programs.

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I did not mean to imply they hard-coded extinction. They do not permit extinction in that the simulations are often configured to retry ad infinitum. I thought evolution of our planet is limited to ~3-4 billion years?

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In a large population, short of an extreme catastropic event (which few AE systems do, unless they're looking to study the effect of catastrophic events on genetic diversity, etc) or starting conditions inhospitable to life, global extinction is virtually impossible. Now, individual lines go extinct all of the time, only to be replaced by other divergences from a surviving line.

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You really didn't say anything here to help your argument. Because "Some alife setups compete organisms head to head" does not mean they did not invoke truncation selection. In other words, this is a non sequitur.

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Define what you mean by truncation selection. I would define truncation selection not to be "head to head" selection, but evaluating all individual elements in the population and throwing out the weakest ones. This is common in commercial systems, but rarer in research systems - it reduces parallelism. Head to head (competing groups of two) is better, but still isn't a "free for all" like real life.

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No it's an incredible stretch. It's called equivocation, as I predicted would be the only option available to the committed naturalist

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Oh please then. Explain why the rules that define how things behave in the universe are not a "programming language", but the rules which define what proteins are made are a programming language. Vague statements of denial don't cut it.BTW, real programming languages work like this, too. If you program in BASIC, the BASIC interpreter was probably written in C. The C compiler was, originally, written in assembly. Assembly in turn obeys the rules set down in the CPU. The CPU, in turn, is dependent on the ruleset that is the natural laws of electricity.

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If this statement doesn't confirm that evolution is a religious belief, I don't know what does.

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Please explain how a world where the basic rules are set of operations such as NOP, ADD, SUB, etc are either more or less complicated than a world where the basic rules are the strong force, the electromagnetic force, the weak force, and gravity, in addition to the additional rules that quantum physics and relativity impose.------------------
"Illuminant light,
illuminate me."

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Fact is, trial&error programs in one shape or another have been around for a long time (trial&error itself has been around since the beginning of time),

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GAs are not "trial and error". They are not "exhaustive search" algorithms. GAs run much faster than an exhaustive search because they base their next stage on what worked well during the previous stage.

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Bottom line is that such programs do not emulate evolution for the reasons I previously mentioned, such as truncation selection, which does not occur in nature. I see you apparently agree truncation selection is predominant in commercial GAs. Given this, do you *still* defend commercial GAs as emulating evolution, knowing that the selection mechanisism (one of the two major tenets of evolution) is not Darwinian at all?

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There is no sharp divider. Commercial GAs are designed to run *faster* than standard evolution. They're all still GA's, however. A genetic algorithm involves determining an optimal solution through successive generations being based on what worked well in the previous generation with slight changes. Boeing could equally well have made up some Earth-analogy to their GA, where they try and make the engines like animals which can fly around and compete with each other in a virtual world - but that isn't nearly as CPU-time efficient. Regardless, it still is the exact same mechanism that leads to advances in lifeforms in a given niche: things that suit that niche better survive better. In the case of aircraft engines, the advantageous traits in the "niche" are better airflow, fuel efficiency, noise reduction, and cost. They ran the program. That's what they got. Claim all you want that humans could have done it better. GE apparently disagrees. My experience with GAs also indicates that. They do a remarkable job.

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So you are claiming that there was not an intelligent source poised to take advantage of the output of Engeneous?

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Perhaps I misunderstood you, but it sounded like you were saying that the algorithms only work with humans picking through the data and deciding what they like and what they don't like. GAs that work by rating each one individually and throwing away the worst performers do not require this, because they only ever get better. If you run it, and stop it in a week, you get one result. If you let it run another week and stop it, your result is guaranteed to be *at least as good*. It may not be better, but it's not going to be worse.

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This is frankly getting ridiculous. I don't know what you do, but you claim you "take whatever it has at that point". The cow chips are really getting deep in this thread. I'm curious as to what you do, and why you would take "take whatever it has at that point". Do you think this is how commercial GAs have been used? Do engineers, "take whatever it has at that point"? Let's all hope you answer no. If you answer no, then how can you possibly defend your claim that intelligence is not required to prune results produced from a GA?

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I am a software developer for the University of Iowa Hospitals and Clinics; in fact, stopping in here gives me something to do while I wait for brains2 to compile or test data to get backed up. We do studies of the human brain, and provide tools for others to do studies. The particular application that I was working on was an offshoot of SRBFS (SRB being a distributed filesystem being developed by BIRN (http://www.nbirn.net); SRBFS being a project to make SRB mountable). SRB contains what is known as "metadata" - descriptive tags that can be added to files. libsrbclient, being used by srbfs, needed the ability to do complex queries on this metadata. One common problem in dealing with hand-entered data is that different users phrase things differently. Thus, the ability to do a comparison which can tell how "off" from a given string whatever string the user typed in for the metadata was, is very useful.Stopping it after a given length of time - is this how commercial applications do it? YES! As I've stated several times, an algorithm that evaluates several possibilities and removes those who performed the worst, unless there is a randomness element in the evaluation, will always come up with the ones removed as being the ones that were the least "fit". As a consequence, it *always* either stays the same or gets better. Now, the downside to this method of conducting selection is that, because it lacks some of the parallelism found more in the "for research" sims and in the real world, it has more trouble coming up with the *best* answer. But its results are still very impressive, and are quite fast.In this case, we want metadata queries to be fast, but to be able to recognize different conventions of entering data. This is an ideal application for this type of GA.Likewise, our neural nets that are used for trimming out ROIs (Regions Of Interest) from the brain (these were, btw, developed before I came here) are trained for several days, and then we stop. Does it matter where we stop? No! They only ever get better. And it is worth adding that these nets don't use backtracing, so they are genetic algorithms, albeit without any parallelism.Can you see why this, what you call "truncation selection", is useful in commercial applications, but why researchers prefer the vast types of variety and forms that occur with a more "Earth-like" algorithm of an open-world with freedom to compete or not? Can you see why that type of algorithm, however, takes a lot longer to accomplish a task? Do you finally "get it"?------------------
"Illuminant light,
illuminate me."[This message has been edited by Rei, 09-09-2003]

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The first question I have for you, is 'Who is we?' (Last sentence).

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Given your focus on language, it should be quite clear in context that "we" is those who accept abiogenesis.

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If you are referring to the scientific community, then refer to my quote from Yockey above.

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I searched for "Yockey" on the page, and found nothing except for that line.

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Your fire example is of the first type of order. DNA and language is a type of the second. Also refer to the problems I listed with the origin of the code above.

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"First" and "second" order are your own constructs, which you define as "Stars, snowflakes, etc. are associated with the first type of order. Language, genetic code, etc. are associated with the second type of order-order that is not inherent to the substance in and of itself".However, this is silly. Ok, so, say, methane and oxygen and heat - the reaction is "first order", right? And DNA and ATP and sugars is "second order", right? Ok, what about platinum and long hydrocarbon chains? First or second? Branched chains - first or second? What if the hydrocarbons are functionalized with a carboxyl group, or an amino group - first or second? What about both? But wait! We're now talking about a reaction between a platinum catalyst and an amino acid! Want me to make a steady progression from a reaction with a platinum catalyst to something else?Do you understand? There Is No Cutoff Between Organic Chemistry And Inorganic Chemistry. This has been known since urea was synthesized. Organic chemistry is the same as regular chemistry - you just usually deal with bigger molecules. *There Are No Orders*. There is no cutoff.

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Even if the correct nucleotides aligned in the correct order for life, this would do about as much good as trying to make a dog spell out and understand the meaning of random combinations of letters in alphabet soup.

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Um... if they form life, they've *formed life*. You're saying that it wouldn't have meaning. That's right - it *doesn't have meaning*! It's just alive. That's what life is.

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Also, for hydrothermal vents, thermodynamics, etc., refer to my links above.

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Your thermodynamics post shows that you have precisely zero understanding of thermodynamics. Take your argument to apply to an ice cube tray in the freezer. What is happening to the water in the ice cube tray? Why, it's losing entropy! But you just argued (if I read you correctly) that a system cannot become more ordered than the environment around it! Your argument ignores the most basic principles of thermodynamics. A closed system cannot become more ordered. Just like your freezer is not a "closed system", neither is a geothermal vent. Non-closed systems are constantly becoming more ordered throughout the universe .

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Are you referring to ribozyme experiments? If so, take a look at the links for the RNA origin of life I have listed above. I don't know too much about computers, so if you are referring to some type of computer program then I have no idea.

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No. I'm talking about alife. Do you not know what alife is? Check out a book on it from your local library. You'll find it quite interesting, even if you don't believe that the models demonstrate that organic evolution is possible. (BTW, if you come to that conclusion, please come in and discuss why you do!)

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Reproduction requires some type of code. A code cannot come about by chance.

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Ah, so BSE was a miracle from God? Gee, thanks God! Humans really wanted Mad Cow Disease, thanks for answering our prayers! (ok, I'll turn the sarcasm tag off... ).------------------
"Illuminant light,
illuminate me."

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Here is the important question: If this GA truly emulates evolution as you have clearly implied, then why do GAs only permit uphill movement on the fitness terrain?

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As I mentioned, commercial applications only allow "uphill" movement so that their result only ever gets better - results that go "downhill" are "killed". Of course, this comes at the expense of parallelism. If you want systems that allow the organisms to do whatever they want in competing with each other, we need to start discussing the more research-oriented applications. It's your call.

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I never claimed "humans could have done it better'

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Perhaps I'm misinterpretting you, but you stated:"As I mentioned in my prior post, GAs are really just trial&error experiments and only rarely would provide benefits based on what an intelligent source can glean from findings of the GA. "Naturally, commercial GAs are evoled for a "purpose", with a "goal" that determines their selection - that is what they're there for! However, there is no "gleaning" that needs to be done - you simply take whatever "organism" rated the best when you've run the GA for long enough. You don't have to review it, to pick out pieces of information or, anything. When we train our ANNs (neural nets, without backtracing (which itself is really just an additional layer on top of a standard GA)) here, you *don't need to do anything* apart from commit your results to CVS. Simply by coding the selective factor that you want to optimize, successive random changes in the net optimize it for that.

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You know, GAs really boil down to souped up trial&error experimentation."

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You know, evolution really boils down to souped up trial&error experimentation.Amazing how that works.

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After the specified length of time has been reached, do engineers "take whatever it has at that point"?

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YES. How many times do I have to tell you this? Let's try five more. YES. YES. YES. YES. YES. You don't need to "glean" a d*mn thing. Because it only ever gets better, you merely need to run it for a while, and you have a good result. If you run it for longer, you have a better result. That is because they lack different niches, all have the same selection factor, etc - as was stated, that is what commercial applications do.Look, if you don't believe someone who *does this in her place of work*, I don't know what will convince you. Would you like me to direct you to an ANN package that you can train yourself? Would that do it for you?

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you are committed to naturalism so much you cannot see that GAs do not emulate what occurs in nature

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Commercial GAs emulate *precisely* what evolutions accept as occuring in nature, with the following exceptions.1) There is no randomness in the selective factors. This is done to speed up the process.
2) All "organisms" are subject to the exact same selective factors. For obvious reasons.
3) Algorithms may or may not lack specific features sometimes found in life forms, such as the ability to "breed" organisms, to shift or replicate sections of "DNA", etc. This depends on what the algorithm is trying to accomplish.None of these apply to research systems. Research systems typically proceed through the exact same mechanisms that scientists attribute to evolution. The only thing that varies in the world is the "phyiscs" - i.e., instead of gravity, magnetic forces, quantum effects, etc, the laws of the universe may involve varying numbers of dimensions of polygonal blocks, "executable statements", or all sorts of other exotic possibilities.------------------
"Illuminant light,
illuminate me."

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When engineers at GE set up the commercial GA to aid in producing a more efficient compressor, were they determined to use the result no matter what it produced? Yes or No.

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I was not there, but if they were sane, yes. I'm not understanding what is so hard about this to grasp for you. If you were playing blackjack, and you got your hand - and you had the option to trade in your hand as many times as you liked, with the guarantee that the hand that you got back would never be more than 21, and would always be at least as good as the hand that you traded in - would itA) be reasonable to accept whatever hand you've got after a number of tries, or
B) intensely scrutinize each hand to determine whether you like it or not?The new result of most commercial GAs is *always* as good or better than the previous version - as a consequence, there is no reason that you wouldn't like the later version more than an earlier version, and thus, no reason not to just let it run.

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John Madden Playstation emulates football *precisely*, except in the passing and running

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If that statement were true, it would demonstrate kicking 100% successfully. Commercial GAs demonstrate one part. Research GAs demonstrate all parts. How many times do I have to say this to you?Notice that you keep refusing to comment on research GAs. Could it be that you don't want to touch them?

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GAs clearly do not emulate this mechanism because they employ truncation selection (where animals are ranked by fitness and selected at some threshold

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Incorrect. Most commercial GAs use it because it is faster than non-truncation selection. They don't have to, to function - and research GAs generally don't use it.

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No, Rei has made it quite clear he beleives GAs emulate biological evolution.

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*Research* GAs do. Commercial GAs show applications for it, but employ speedups because we don't want to wait 4.5 billion years. What is so hard about this for you to grasp?

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The principiles being used are no different than ellaborate trial&error expirments scientists/engineers have been doing for centuries.

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You are not grasping the difference. Commercial GAs work on the previously best functioning "trials". In this manner, evolution - as evolutionists view it - IS trial and error.

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Unable to support this point? I have supported it over and over again. All that is required is ONE example where a GA produced useful information without intelligent source to realize it, ie put it to use.

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So, you don't think that learning how to trace out sections of the brain (what we do here) is useful? What do you think we have to do with them, talk to them really nicely to get them to run, or manipulate them? We run the program, giving it the ANN and the brain to trim. End of story. It produced something useful. All we had to do was give it the selection rules (in this case, letting there be a wide variety of sample brains that it is randomly assigned to trim from, and evaluating the accuracy of its trim).Now, before we go any further, you need to decide: Do you want to discuss commercial GAs, or research GAs? If you want to discuss commercial GAs (I.e., producing useful things for humanity), you need to accept the fact that engineers do use speedups (such as "truncation selection") for precisely that purpose - speeding things up. If you want to discuss research GAs which do not use this method of selection (and, as a consequence, usually aren't used in commercial applications because of their lower speed, but often produce fascinating results), then say so. Research GAs have even been used in studies of the spread of genes in viral and bacterial populations.------------------
"Illuminant light,
illuminate me."

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The reason folks that Rei refuses to give the sane answer of 'No' to my question is that he knows it paints his position into a corner

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The reason that Rei refuses to give the ridiculous answer of 'No' to your question is that she knows that the answer is 'Yes'. Did you even look at the analogy that I presented? If you had such a choice in blackjack, would you not pass your cards in and let it shuffle them around for quite a while using those rules, and accept whatever is passed back? Because if you wouldn't, you're crazy.

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GE requires intelligence for the information it produces to be realized

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Unless you're talking about people taking the plans that it spits back and building them in the real world instead of in a simulation, you're completely wrong.There is something wrong here. I am not understanding at all what part of this you're not understanding. Why is this such a difficult concept to you? GAs produce finished products - in this case, a finished design. What about this do you not understand?I completely see this as you trying to claim that, if water runs downhill, then there has to be an intelligence there for it to be at the bottom when it's been given enough time to run downhill. To put it into your analogy.

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1) Like commercial GAs, they cannot produce useful information outside the presence of already existing information

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Please explain, given the sample GAs that I presented (in the long-long-ago, before you took us off on this incredulous side tangent) are not producing useful information. Inventing the concept of parasitism, developing physical traits on land and on water and using them to defeat/destroy their competitors, and scores apon scores of other things - that's not "useful information" to the organisms? Tell me, is the ability to walk on land useful to you? Is the ability to steal your blood useful to a flea? How many examples do you want?

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2) They do not emulate evolution in nature because they typically invoke truncation selection

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Neither tierra nor avida evoke truncation selection. You must have incredibly poor reading ability. The only "influencing" tierra does to them is, for each organism in a block of memory space, gives it an amount of CPU time proportional to its size (effectively in parallel). The organisms are free to do whatever they want with that CPU. Avida works in a similar manner. BTW, you've only read about one particular type of GA (the virtual-machine GAs)? So, you haven't read about anything like polyworld or Karl Sims' works? Among others? I'm starting to wonder if you've read more than 2 pages about the topic you're arguing about - a topic that you're arguing about with someone who actually uses them at work.

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They assume positive mutations that increase the genetic information such that the wild-type is more viable than the parent type in a normal environment

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What on earth are you talking about? Non-"truncation selection" systems don't "evaluate" the fitness of the organisms. They just let them run on their own.

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The assumed positive mutation rate is unrealisticly too high

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Again, what on earth are you talking about? They don't define positive or negative mutations - they let them change randomly (and in some GAs, interbreed - in fact, in some tierra-like GAs, breeding wasn't defined, but a type of retroviral insertion style of genetic transfer developed on its own ).Research GAs are used in drug resistance studies, population studies... they've even been used to determine whether a type of "greedy" gene could be used to wipe out a particular species of mosquito from the Earth, although this particular case (unlike the others) hasn't been confirmed as accurate by testing (for obvious reasons ). Why is this so hard for you to understand (apart from your obvious lack of knowledge on the subject)?------------------
"Illuminant light,
illuminate me."

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Do you actually think that a design team of any kind will be "determined to use the result no matter what"? I have preformed a lot of software design and we frequently throw out the result of the design efffort when we realize it isn't going to be suitable.

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Why do engineers produce prototypes? To find out what is wrong with a design and correct it for one thing.

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Perhaps there is a difference here because I work with GAs whose final products are software, not hardware. If the hardware people have properly designed their fitness algorithm, then it will work perfectly no matter when you take it. Any changes you do to it will just make it work. If I understand what you're suggesting, you're suggesting that the fitness algorithm doesn't function completely accurately - correct? You see, in software GAs like I work with, that's not a problem - perhaps it is in hardware, that you can't model everything completely and need to do "guesswork".Of course if the fitness algorithm isn't perfect, you're going to get an imperfect result. But, if your fitness algorithm is, then it is very unlikely that you can make the results of the GA better by hand-tweaking.------------------
"Illuminant light,
illuminate me."

If Fred is arguing against the intelligence that sets up the environment in which the GA runs, then he is arguing against Physics in the real-world counterpart. Because, you're basically coding a universe when you write a GA - you code the equivalent of what would be physical laws.It seemed, however, that he was arguing that there is some intelligence needed at the finished product. However, the GAs do complete with finished products; in our case with ANNs, we simply take the ann file that is produced and use it as input to the tracing program.------------------
"Illuminant light,
illuminate me."