Not because they’re terrorists or black-and-white thinkers, as claimed. A simple computer program shows the limits of creating information by chance:
Engineers are more likely to be creationists because they are familiar with what it takes to design complex things for specific tasks. Which is exactly what we see in the biological world. Additionally, engineers who work with computers know about randomized methods, which include evolutionary algorithms. We are aware of their significant limitations…
Let’s set my evolutionary algorithm a simple, fundamental task — to count by ones…
Exponential is bad news. Exponential means it took the evolutionary algorithm twice as long to count to 10 as it did to count to 9.
Let’s put exponential on a cosmological scale. The heat death of the universe is projected to occur in 10106 years. This is well beyond the lifetime of anyone who’ll even remotely know we existed. Seems like a lot of time, but not for exponential doubling!
If we generously say that a step of P’‘ runs in a nanosecond, which is nine decimal places to the right of the dot, then the universe will undergo heat death before the evolutionary algorithm can evolve a program that counts from 0 to 500. And it takes even longer if the program must start from 1 instead of 0. To go up to 501 doubles even that. Completely impossible.
Eric Holloway, “The Salem Hypothesis: Why engineers view the universe as designed” at Mind Matters News (June 7, 2022)
Takehome: Engineers doubt chance evolution because a computer using an evolution-based program to do simple tasks would be chugging away well past the heat death of our universe, as Eric Holloway demonstrates.
Note: The hypothesis was named in honor of Talk.origins contributor Bill Salem.
You may also wish to read:
Dawkins’ Weasel program vs the information life acquires en route To demonstrate what is wrong with fully naturalist assumptions like those of Richard Dawkins’ Weasel program, I developed Weasel Libs, modeled on Mad Libs. When we apply a Mad Libs “epigenetic” approach to Dawkins’ claims about how life’s information can be created, we quickly see a glaring flaw. (Eric Holloway)
i am a mechanical engineer with a decent IT background, so it would be weird, if i won’t comment on this …
I as an engineer, I have no doubt that life on Earth was created. I would stake my life on it. I know what i see and i can only laugh in any biologist’s face … The only question is, how it was done.
Biologists can claim what they want … they are dead wrong … they are so wrong, they even don’t realize how wrong they are … because they never made anything … they don’t know what they are talking about … the problem with biologists is, that their unqualified claims mislead lay people …
The Salem “logic” is typical pop psych, like Dunning-Kruger or “bullies are insecure”. I’m tired of that crap. Life doesn’t work that way.
Engineers are designISTs because engineers are designERs. We know the power and the limits of design. We know that a bug-free product is impossible, so we recognize that the self-debugging process of life can’t be 100% perfect. Even so, we also recognize that it’s infinitely beyond anything we can design.
The closest we can come to self-debugging is a mechanism that improves with wear, like the sleeve-valve engine. But it’s still not self-repairing or self-checking like every cell in the world.
Polistra
obviously, it is close to perfect. Some species have been around for hundreds of millions of years. Can you imagine anything man-made working for 100 years without any outside intervention /maintenance/repair ?
I could, if i was a fairy tail writer or a Darwinist (which is basically the same)
PS: the fact that such species still exist, is the ultimate proof of design.
I am also an Engineer and agree with you both. Materialists often try to point to “poor design” as some sort of “evidence” against ID. But we have quashed that argument often. Here is one example:
https://thopid.blogspot.com/2021/09/the-bad-design-argument.html
Yes, close to perfect. The real secret is that a mechanism with analog negative feedback doesn’t have to be close to perfect. A well-designed loop can factor out some imperfections, and life has an infinite number of loops guarding loops.
Later thought: Computers do have one self-checking feature, the parity bit on memory. But it doesn’t try to fix the error, just warns when something is wrong.
Polistra,
As to parity bit on memory,
I have a better example, and it is somewhat closer to what a cell has to deal with…
Let me quote from a debate on Quora.com
Keyword: Checksum
Someone asked a question about how reliable is the windows file copy process.
Someone replied:
Dawkins’ weasel program is a failure in the grand scheme. Meaning that sentence cannot just be randomly inserted in any book and expect to be coherent. “Four score and seven years ago, methinks it is like a weasel”, doesn’t sound like the makings of an inspirational speech. “Friends, Romans, Countrymen, methinks it is like a weasel!”, would have the audience scratching their heads.
Engineering is a fine profession but engineers are not scientists. Engineers use – but did not invent – algebra or geometry. Neither Newtonian mechanics nor Maxwell’s equations were discovered by engineers. The strange realities of relativity or quantum theories were not revealed by engineers.
Engineers build on and from what is already known. Where lives depend on them getting it right, they cannot afford to do anything else. Science, on the other hand, is about exploring the unknown with all the uncertainty that entails.
Biologists generally accept the theory of evolution, in spite of its imperfections and shortcomings as the best account we have at this time of how life has diversified and flourished on Earth. A significant number of engineers attack the theory with a vehemence that suggests that they fear it somehow poses a threat to their most fundamental religious beliefs. If they were truly as scientific in their approach as they claim then they would be asking themselves why this should be. What possible threat can the theory of evolution pose to engineering?
Seversky
and where comes the knowledge from ? :)))
We discussed this before, without engineers, there won’t be any science.
Without engineers, there won’t be a sheet of paper.
Look around you … every single thing you look at is the product of an engineer.
Go to any lab. Every single thing in that lab is the product of an engineer.
You heard about Large hadron collider ? There are lots of scientists working there. But who built the collider ? Scientists or engineers ?
Are you saying, that engineers don’t know anything and have to ask scientists how to design things ?
Are you saying, that without scientists there won’t be engineers ? Or what are you trying to say ?
In fact, without engineers there won’t be a thing.
“Evolution” is not merely a proven false theory like many others but it is also the atheistic Bible.
Sadly, many misguided theists accept this proven false theory which cannot be said about atheists and religious teachings.
Engineers, including the scientist sub branch, have an edge seeing through the nonsense. That’s all.
Seversky
the theory is stupid… that is the threat… these scientists spread stupid ideas … no surprise that the theory was developed by natural science graduates … it is unbelievable, that in 21st century it is still being taught in universities… seriously, this is unbelievable….
I said it before, but let me repeat it:
In 21st century!, this theory claims, that sophisticated fully autonomous self-navigating flying systems somehow self-designed, with no help from engineers.
The theory is as stupid as it gets …
PS: let me remind you what Alon Musk said in 2021 about self-driving cars (self-driving cars much easier than flying systems, because flying systems have to move in 3 dimensions.)
The article starts:
Alon Musk:
“Didn’t expect it to be so hard,” … if i wouldn’t know who Elon Musk is, i would think he is a biologist.
seversky is clueless. There isn’t any scientific theory of evolution. Evolutionary biologists don’t even know what determines biological form.
Evolutionism, the untestable claim that blind and mindless processes produced the diversity of life, threatens everyone. Mainly because it is one big lie. That means it amounts to child abuse when forced on children.
Further evidence that seversky is clueless: Approaching Biology from a Different Angle:
Martin_r @ 1 –
And yet ID supporters insist that tat question is not something ID can ask.
Bob O’H- Grow up. ID is not about the how because we don’t have to know how before determining intelligent design is present. But ID does NOT prevent anyone from trying to figure out the how.
“And yet ID supporters…”
See, for Bob and his tribe, this has nothing to do with scientific inquiry. It’s just about opposition, opposition, opposition.
Andrew
Bob O’H
ID is a science project with a well-defined scope. If you want to go beyond that, it’s a different project.
Seversky
It spite of its imperfections and shortcomings we have been told that there are no weaknesses in the theory of evolution and it is more certain than gravity.
ET & SA: take up your concerns with martin_r.
Hi Bob, my only concern is that you continually misrepresent ID and science.
.
Bob, no one cares if you believe ID. What we want is for you to stop lying about it to the public.
“What we want is for you to stop lying about it to the public.”
to wit:
Of course the problem with Bob O’Hara’s honestly admitting that he statistically ‘tortures data until it confesses’ is that data, like people, will confess to anything you want if you torture it/them long enough.
UB at 22,
Lying about what? Who is this “we” and who put you in charge of speaking for others?
My program shows evolution is not weak, it just doesn’t work. If you think evolution does, add your idea to the program and see if it solves the exponential blow up. This is a great way to make ideas about evolution concrete.
On the other hand, it is trivial for a programmer to avoid the exponential blow up. This is because the programmer understands the code, whereas no matter what evolution operator you add, the operator never understands the code. That’s the fundamental difference between a mind based explanation for the origin of species versus a evolution explanation.
EricMH
Could you explain in a bit more detail what the program is doing and why it is exponential?
The goal is to count numbers.
So, you start with 0 or 1 and there are 8 possible numbers. So, evolution randomly mutates the first number until it gets the second. Then it mutates 8 numbers again until it gets the third.
Why is that exponential? Let’s say it takes 10 min to get the first number. The second would be 10 and also the 3rd.
Why isn’t that 30 minutes and not 1 million minutes?
EricMH,
Several design disciplines are discovering generative design applications as described here:
https://www.aem.org/news/generative-design-solving-design-challenges-with-artificial-intelligence
How does Evolutionary Informatics view such technology?
-Q
Querius at 27,
A strange article. The wording is off. The goal is the best solution, the best piece of hardware, not ‘thanks to the cloud and some software and we get all these choices.’ No, they don’t. In order to save time and money, and weight, the best answer is always the best answer. No one chooses other answers in engineering or anything else. Weird.
Generative design basically takes a set of specifications, constraints, or parameters to generate a set of possible solutions. There are often multiple solutions left after AI filtering. This is because there’s often no “best” answer, but rather there are answers based on different trade-offs.
https://www.generativedesign.org/01-introduction
Applications are typically for mechanical design, although I’m aware of the technology being used for city planning, construction, and other disciplines, including architecture.
In this example, you can see the trade-offs between several solutions:
https://www.generativedesign.org/01-introduction/01-02_generative-design
Often results can look very “organic” since biological structures such as bones often optimize on light weight. Manufacturing of these shapes would be impossible without additive manufacturing (aka 3D printing). Comparing some of this technology to bones, one can appreciate the dynamic responses of biological systems, for example, bones grow and thicken internal spicules along stress lines.
I’d suggest that the intelligence is programmed into the software, which is then applied to the problem with successive iterations. Intelligence is embedded in the process rather than in individual specific solutions.
But my original question in 27 is an honest one.
-Q
seversky:
Engineers build on and from what is already known.
So do all scientists.
they cannot afford to do anything else. Science, on the other hand, is about exploring the unknown with all the uncertainty that entails.
What BS. I could come up with any number of engineers who were more creative and radical than most scientists. Example: Claude Shannon almost singlehandedly (coming after Hartley and Norbert Weiner started the work) established information theory, with an MSEE and BS in math. He eventually earned a PhD in math but as a masters project single handedly demonstrated Boolean algebra as the future basis of computational hardware, and so established ‘switching theory’ (an archaic term) in the most important masters thesis of the past 200 years.. Example #2: R.E. Kalman, EE originator of the Kalman filter, a tour de force of applied mathematics absolutely unforeseen by mathematicians. It was so radical that he decided to bypass all of the IEEE section journals and possible resistance there and published the first related paper in a mechanical engineering journal. http://www.cs.unc.edu/~welch/kalman/
Example #3 Yours truly, demonstrating as original work applying epistemic logic and game theory that continuous random variables can be identified with self information and Shannon entropy, in progress, here: https://drive.google.com/file/d/1lTgCo3LU1MvworkBPZFZQuOA30ZrFr_C/view?usp=sharing
@SA the evolutionary algorithm is not evolving the number sequence itself. It is evolving a program that generates the number sequence.
If I modify the program to keep the previous solution population, so it’s not starting from scratch each time, the exponential time increase is still there. This gets to your scenario. Here’s the data from the modified experiment.
256.0
1773.0
21625.0
18121.0
30959.0
311653.0
348966.0
1293912.0
3225339.0
2318573.0
2920256.0
11101407.0
The reason why it gets exponentially more difficult is because the programs get bigger, and with bigger programs there are more ways to get things wrong. Additionally, more junk is accumulated as evolution progresses, which makes the problem even more difficult.
A correct solution looks like this:
.+.+.+.+.+.+.
The ‘+’ increments a counter, and the ‘.’ outputs the counter value. So the above program generates the following sequence: 0, 1, 2, 3, 4, 5, 6, 7
To evolve to the 8 sequence, the evolutionary algorithm just needs to insert another ‘+.’ in the appropriate position.
On the other hand, look at the best solution the evolutionary algorithm found for the 7 sequence:
.<+<.+.+.+[.+[[.+<.+[+-.+-[
Most of those characters are junk. They are valid commands, but contribute nothing to the solution, or are fixing mistake commands.
@Groovamos #30
Sure, engineers can become scientists, but they definitely don’t learn the scientific method as part of an engineering degree.
You really had to pick a nit with Seversky in order to flash your “creds”, didn’t you?
Please let us see the results of the peer review of your “paper” when available.
Querius at 29,
Software has no intelligence. It can be given instructions to sort things given certain parameters but it has no intelligence, meaning human-like intelligence. Before this technology, what did human engineers do? Nothing? And this “knowledge” did not come from machines but human beings. Engineers don’t have time to sort through 200 or more “answers.” Again, prior to this, human engineers worked it out on their own. This is an assistive technology, not a replacement for human thought.
PK at 32,
Nonsense. They can learn whatever they want on their own. A degree in engineering is not fire and forget. Good engineers keep on learning.
Eric @31 – thanks. Good explanation.
The group is criticized for having no expertise or credentials.
A poster references his background and academic study.
He is then criticized for “flashing his creds”.
But that won’t even be good enough until there’s peer-review by the credentialing team.
Is there a scientific method? UC Berkeley doesn’t think so- How Science Works
Pater Kimbridge at 32, “Sure, engineers can become scientists, but they definitely don’t learn the scientific method as part of an engineering degree.”
HUH? What in the world are you talking about? Engineers not only rigorously ‘test’ scientific theories, day in and day out, to see if they really work, but they make a scientific theory get down off its throne, ‘scrub the floors’, and then ‘fire’ the theory if it won’t do the work.
And the theory of evolution has been ‘fired’:
Relatd @33
Software can indeed employ “artificial intelligence” to respond to inputs/stimuli. The “intelligence” includes the capacity to “learn,” which means it’s programmed to create or modify rules of response and then evaluate the outcomes.
For example, how familiar are you with a Chess program called Alpha Zero?
https://www.chessjournal.com/alphazero/
Alpha Zero taught itself chess in about four hours of playing against itself and now has the highest Elo rating in the world. Here’s a link to a preprint technical paper on the subject:
https://kstatic.googleusercontent.com/files/2f51b2a749a284c2e2dfa13911da965f4855092a179469aedd15fbe4efe8f8cbf9c515ef83ac03a6515fa990e6f85fd827dcd477845e806f23a17845072dc7bd
Yes, engineers often don’t have time to “do it right,” but they always have time to “do it over.” Very few designs spring into existence fully formed and complete, but are usually the result of many iterative improvements. Be assured that I’m not suggesting that generative design can replace engineers, but I agree that engineers can use generative design as a tool, especially if the generated designs are filtered down to perhaps six or fewer.
EricMC @25,
I completely agree! But my question remains. How does Evolutionary Informatics view generative design technology?
-Q
Querious at 39,
Software can’t learn anything. Not like people do. Take chess. Put in all possible moves and responses, develop a feedback loop and it just has the answer in memory. Yes, programs exist that can do trial and error and correct errors, but if it’s not programmed in, it can’t do anything.
I suggest you walk into a room filled with engineers and say “… engineers often don’t have time to “do it right,” That’s just nonsense. Engineers sent men to the moon in the late 1960s.
Engineers have no time to deal with [fake word] designs. You don’t seem to understand that. Decades of work has led to aircraft like the SR-71. A lot of testing went into that before actual prototypes flew.
And another thing. I am tired of the Global Cabal of Relabelers and Repackagers whose only job is to come up with fake words and fake terms to give people the illusion we’re living in “the future.”
One more thing. There’s no such thing as “Additive” manufacturing. Fake and more fake. So instead of making a mold and pouring hot metal and then machining it (grinding down any imperfections), parts can be constructed in a device that avoids some steps. Engineers still have to figure it all out before it goes through that process.
I’ve seen designers design things and they have to know about materials, stresses and other things. The head designer can then pick the best handful of candidates. The engineers can then select the best way to manufacture whatever it is and choose the best, most suitable materials. But 200 or more? No. Not ever. Not in civilian applications.
Querius,
i don’t know what is your eduction, but i had a quick look at the Autodesk’s article.
Of course, as a mechanical engineer, i am familiar with Autodesk products.
As to Autodesk’s Generative-design software feature:
It is just another example of AI hype …
You know, Autodesk has to sell its products, they have to add new fancy features all the time …
But i doubt this AI feature will be ever used in real life …
Have you noticed that ‘alien’ motorcycle’s swingarm ? It is a grotesque … moreover, that part (that swingarm) can be only manufactured using a metal 3D printing … i am pretty sure, that the metal 3D-printing of that swingarm will cost more than the whole motorcycle… From what i could understand, and i personally can see why, that swingarm can be manufactured ONLY using metal 3D printing … you can’t use molds, or any other mass production technology – because of swingarm’s ‘alien’ shape …
This is it – in real life, this software feature has a very very very limited use (basically, it is useless) … But good for Autodesk to have such a software feature … they even claim that “it is going to revolutionize manufacturing over the next decade.”… LOL
PS:
Relatd
Good point … just have a look at the Autodesk’s article …
😆 Engineers are much more scientists than any biologist. Evolutionary biologists (for more than 100 years now) write fiction and poetry about origin of life and evolution while engineers build everything we see around.
@Querius
Generative technology definitely has a place. I understand logistics planning makes heavy use of multiobjective optimization techniques, which generate the Pareto front of solutions with different tradeoffs.
AIs like Alpha Zero are very powerful, and can beat the top humans (and other chess engines).
However, in all these cases, the downside is the inefficiency. Algorithms have to check thousands, millions or billions of solutions to reach the level of humans checking just a few solutions. So, such techniques only work when the problem domain has been constrained enough for brute force search.
Information is the reduction in options, and constraining the problem domain to be searchable is a matter of reducing the number of options. That is the role of the human engineers. We create the information that makes these algorithms effective by reducing the search space to a manageable size. There is no way to replace the information produced by engineers using an algorithm.
The future of AI technology is going to be this hybrid between humans constraining the problem domain, and the algorithms brute force searching for solutions within the constraints. Humans do smart things slowly, and computers do stupid things quickly. The idea will be to figure out what are the smart slow things to hand off to humans, and the stupid fast things to hand off to algorithms.
For example, to get rid of the exponential explosion, the evolutionary algorithm can be constrained to only add the “.” and “+” characters to the end of the solutions. This constraint, of course, requires intelligence, since the constrainer has to understand the program pattern of ‘”.+.+.+.” and how it generates the count sequence.
Regarding the scientific method, software developers exercise the scientific method every single day many times to debug their programs. Bugs often are non obvious, and we have to form hypotheses and falsify or confirm these hypotheses. We also have to infer logical laws and causes to find the root cause for the bug. Additionally, we often use the scientific statistical toolbag in this debugging. Software engineers are lucky, since we can step through our programs to see the behavior in real time. Other engineering disciplines have to be even more rigorous and insightful in their use of the scientific method, since bridges and rockets don’t have debuggers you can attach to the finished product 🙂 So, I would say engineers use the scientific method much more frequently than scientists, and are much more aware of how the scientific method works. Finally, our use of the scientific method has to actually work. Scientists just need to get their peers and grant committee to accept their claims, the claims don’t actually have to work in the real world.
Scientific method and the engineering design process, are so similar it’s a distinction without a difference.
Eric upthread
Don’t think so, Eric. Your program is a model. To be able to claim evolution doesn’t work, your model needs to bear some resemblance to reality.
No one is claiming that “evolution” doesn’t work. Eric needs to be more careful with his wording. The claim is that evolution BY MEANS OF BLIND AND MINDLESS PROCESSES doesn’t work.
As for reality, no one knows how evolution by means of blind and mindless processes “works”.
“The claim is that evolution BY MEANS OF BLIND AND MINDLESS PROCESSES doesn’t work.”
It should be obvious now.
Yes, but we have to also understand that Intelligent Design is NOT anti-evolution. Evolution by means of telic processes, ie intelligent design, is still evolution. Evolution by means of telic processes works, as exemplified by genetic algorithms. Genetic algorithms are goal-oriented programs that utilize a targeted search to solve problems.
ET @47,
You’re right in specifying a qualification. It’s Darwinian evolution in tiny increments by random mutations filtered by natural selection that doesn’t seem to work.
Martin_r @41,
The largest users of additive manufacturing are in medical and aeronautical industries. According to an online course I once took in the subject from Deloitte University, there are several technologies commonly employed. One example, used in the class showed how supply chains are changing in some cases. One of the examples they provided involved the U.S. military. To service the rotor of a type of helicopter, a special tool is required. Rather than fill up the supply channel with these tools, they issue 3D printers in the field, where additional tools are printed on demand.
AI is indeed used to generate 3D honeycomb patterns in parts for the purpose of reducing weight while maintaining strength. The employment of finite element modeling (aka FEM/FEA) to determine stresses has been used for many decades in mechanical engineering. An architect neighbor of mine fed it my deck cover design to make sure it could support a heavy man walking across it. These data can show exactly where something needs to be beefed up. 3D FEM was used in the 1980s to optimize stratified ignition in the shape of automotive cylinders.
I’d agree with you that engineers use technologies as they do any other tool, whether its a 3D printed prototype or CAD/CAM/CAE software.
EricMH @43,
What the Alpha Zero AI does is not simply a “brute force attack” against a chess position, and it doesn’t trim branches of unpromising lines as do typical chess programs, but rather it develops rules and priorities by trial and error. These types of rules enable AI routines to “recognize” general types of shapes in a photograph such as kitten or a boat.
I completely agree with you regarding the use of the scientific method for debugging software or finding design flaws or limitations.
Out of curiosity, have you ever tried simulating an ecosystem using software? I’d suggest that stable ecosystems are also evidence for design. Optimization for the survival of only one specific organism is likely to “crash” an ecosystem, causing a devastating loss in carrying capacity. It seems that any ecosystem must be harmonized to sustain life (for example, think of what the introduction of rabbits did in Australia or what kudzu did in the southern USA).
-Q
As Michael Behe said:
ET @ 47
The reason I say “evolution” instead of “Darwinism” or “random processes” is that all evolutionary mechanisms are random processes + natural selection. Nothing outside of that is taken seriously, e.g. saltationism, lamarkianism, and so on. Plus, Dawkins makes a pretty good mathematical argument in The Blind Watchmaker why nothing besides random incrementalism can work for evolution. So there is no real distinction.
These are all the genetic mechanisms I’ve run across:
1. random insertions, deletions, and mutations of nucleotides
2. gene duplication
3. meiosis
4. horizontal gene transfer
On top of that is only natural selection, where fit offspring reproduce, and unfit offspring are eliminated.
The second part of evolution is the relationship between genotype and phenotype. Dawkins type weasel examples neglect this difference, but my algorithm faithfully reproduces this aspect of evolution. Genetic mechanisms operate on the genotype (the program code in my algorithm), and natural selection operates on the phenotype (the program output in my algorithm).
So Fred @ 46, this is the reason my algorithm is representative of the power of evolution. My algorithm includes all of the above. I’ve not run across any other aspects of evolution that will significantly change the algorithm operation. If you know of any, please mention them. Otherwise, we can consider my algorithm to work or fail insofar as evolution works or fails. In fact, this was the original motivation behind evolutionary algorithms, the mathematical issues brought up during the Wistar Symposium in 1967. John Holland, the inventor of the genetic algorithm, specifically cites the Wistar Symposium as the reason for his interest in genetic algorithms. Where participants like Murray Eden and Schutzenberger saw mathematical difficulties and impossibilities in evolutionary theory, John Holland saw evidence of evolution’s spectacular power. Holland then invented the “schema theorem” to explain how evolution could be so effective.
Many decades of research into evolutionary algorithms hence, we’ve seen Holland’s anticipation completely squashed (and the schema theorem disproven). There is nothing special about evolutionary algorithms that can explain how biological evolution can overcome the difficulties brought up during the Wistar Symposium. In fact, they tend to be bottom of the pile in terms of tools engineers reach for to solve problems. My algorithm is a good example of this failure. So, at this point, evolutionary theory has been put to the test in real time in the make or break world of commercial software, and has found very wanting. There is no reason to subsequently believe that some magic makes evolutionary theory work in biology.
On the other hand, as my example also very clearly indicates, the Wistar Symposium mathematical problems are easily eliminated when a mind is involved in the solution creation process. So, the obvious implication is that a mind is involved in the biological creation process as well.
Finally, if any evolution theory die hards think I missed some magical operator that makes evolution work, all you have to do is add it to my code, or tell me here in chat to add it, and we can see if it’s the missing piece to this puzzle. No need to have decades of drawn out speculative debates online. We can test evolutionary theory easily on the computer and come to a conclusive answer.
Taken seriously? Is that your argument? There isn’t anything about Intelligent Design that is anti-evolution. Intelligent Design is OK with organisms being designed with the information and ability to evolve and adapt:
And in “Not By Chance”, Spetner responds to “the Blind Watchmaker” thesis. For example, duplications, followed by building it a binding site, and then changing the duplicate for some new function, isn’t justifiable as a blind watchmaker mechanism. Transposons carry within their sequence the coding for two of the enzymes required for the gene to move around.
.
On top of that there is artificial selection. And we see what that can do in a relatively short time.
The link between genotype and phenotype is with the traits. Traits such as eye color and shape. Detached or attached earlobes. Cleft chin. Dimples. In his book (English title) “Why is a Fly not a Horse?”, the prominent Italian geneticist Giuseppe Sermonti, tells us the following: Chapter VI “Why is a Fly not a horse?” (same as the book’s title):
I doubt your algorithm does as you say as no one knows what determines biological form. We know it isn’t DNA. DNA controls and influences development but that only means it determines whether or not development doesn’t have any issues.
Querius,
you seem to be familiar with terms like 3D printing, FEM, CAD, CAM, and so on. That is why i have asked you what is your education. You sound like an engineer.
However, i have to insist on what i wrote before, this GENERATIVE-DESIGN technology has a very very very limited application. Basically, you confirmed it. It very reminds me of so called evolutionary/genetic algorithms (EA/GA). These also have a very very very limited application. I think, this AI GENERATIVE-DESIGN technology is another fancy [fake] word for EA/GA (like Relatd pointed out)
But again, EA/GA is nothing new too. It just another fancy word for optimization algorithm.
Of course, i can’t entirely judge from one Autodesk PR article, but from what i could understand, i am pretty sure it is still about the same (EA,GA, GENERATIVE-DESIGN, optimization algorithm).
Please don’t get me wrong, i am not against any additional engineering tool, i am just saying, all these technologies have very very limited use in real life engineering (unlike FEM, CAD, CAM etc.) that is why i called it “another AI hype”. Because lay people (e.g. Seversky) may think, that you take a computer with a proper AI software, you put in some variables and it will design a cheetah-robot for you.
EricMH,
Let me add to yours … in my debates with Darwinists, EA/GA were mentioned very often. Darwinian debaters claimed that “look, even engineers use evo/genetic algorithms. People here at UD know that i am a mechanical engineer. I never heard of EA/GA, i never used EA/GA. I heard of optimization algorithms. You may say, that i never heard of EA/GA or never used them (as an engineer) because i am backwards. Few years ago, i made my own survey. I got in touch with some international robotic companies dealing with humanoid robots design (including Boston Dynamics). I have asked a very simple question “if their engineers use EA/GA when designing robots”. I have received some answers … I won’t name the companies, i don’t have the permission, it was a private communication.
Anyway, here is what they replied:
A company from Spain:
A company from Italy – in this case i talked to 2 engineers, both of them are also academics (university professors)
A company from France:
PS: Boston Dynamics did not reply, and i urged it a few times. No reply. The funny thing is, they even have a robot named “DARWIN”
https://www.romela.org/darwin-dynamic-anthropomorphic-robot-with-intelligence-2/
Antenna Design using Genetic Algorithms
ET,
At that time (when i did my survey) i was also looking for real life products engineered using EA/GA … the antenna you have mentioned was the only thing i was able to find.
Scientific American did an article about 20 years ago (2003?) titled “Evolving Inventions”. Read it.
ET,
One more thing… you post very often that ID folk is not anti-evolution. I personally don’t believe that a humming bird or a honey bee or a blue whale or a cheetah evolved from some common ancestor … from engineering/design point of view, i am pretty sure these species were designed from scratch.
Of course, there seems to be some sort of built-in adaptation, but the question is, to what extent could species adapt … do you believe that e.g. wings are result of this built-in adaptation ?
How are you defining “evolution”? Evolution is more than universal common descent.
Michael Behe:
Also Michael Behe:
🙂 Ask for scientific evidences to see if you get an answer.
PS: I think “genetic algorithms” are a kind of a hoax. Nobody knows all the details of the cell therefore nobody can explain(or programm) what they don’t understand.
ET at 60,
Evolution: Human beings are here by accident. That’s it.
ET at 58,
Inventions don’t “evolve.” Never have. Things are made to satisfy a usually urgent need.
Martin_r at 54,
The Global Cabal of Relabelers and Repackagers have one goal: to make people believe they are in living in “the future.” Everything being designed and built today is based on hundreds of years of knowledge. And I’ll say it again, there is no such thing as Artificial Intelligence. No machine has human-like intelligence just programs created by human beings. I doubt the chess playing AI could tell me how to tie my shoes. Machines, including computers, are stupid. Totally stupid unless a human being creates programs for them.
ET at 56,
Seriously? Let’s go the even more complicated route? I don’t think so.
ET,
Besides the antenna, I would expect, that you will show me more real life products engineered using EA/GA. Instead of that, you have referred me to some article … you start sounding like a Darwinist… anyway, . i will have a look at that article …
Martin_r,
My educational background is scientific, but my vocational background is primarily in industry. I’ve had the privilege of interacting with many engineers in many different disciplines worldwide. Plus, I read a lot.
Yes, the biological world screams design to engineers who recognize the mind-boggling technologies and capabilities of biological systems. They realize that shooting bullets randomly at a Tesla will never result in design innovations. Bullets can only destroy things. But if you’re in a Tesla being swept down a river in a flood and can’t get the window open to exit, bullets may open a window, destroying it save your life.
Engineers understand the importance of knowing the specifications and constraints of any project. They are intimately and sometimes painfully familiar with their experiences dealing with trade-offs and compromises.
Specifications include performance, time, cost, reliability, manufacturability (including common parts, and tolerance costs and stacking), testability, manufacturing yield, flexibility under changing conditions (temperature, humidity, pressure, dust, mud, corrosion), robustness, repairability, upgradability, usability, compatibility, and “charm.” I’m sure I missed other factors. This is one reason why designs improve by successive approximation after being subjected to random use and abuse.
An important point is that hyper-optimization and over-specialization makes an organism, an ecosystem, a business, an entire economy, or an individual career fragile and subject to extinction. Even academics realize this as they learn more and more about less and less until they know everything about nothing. (grin)
Examples in biology include ecological and agricultural monocultures, and also the risks associated with a lack of genetic diversity in specific organisms. Introducing cats, rats, wild hogs, and a host of other invasive species can devastate an ecosystem, which leads to my observation that the survival of an ecosystem may be at odds with the success of any component species.
AI, machine learning, and generative design are programmed to develop and apply rules to an environment along with instant feedback. Also, parametric technologies embed a specified range of variation into a design. The intelligence is already programmed/designed in to generate different configurations, but they mimic the behavior of intelligence when their behaviors are actually an extension of intelligence.
My best example of AI is in well-programmed chatbots (or trollbots) that mimic human communication and pass the Turing test. Here at UD, there are a number of contributors that might indeed actually be trollbots, judging from their pattern of abusive comments, lack of new information, and vacuous responses.
-Q
Querius at 67,
“…they mimic the behavior of intelligence when their behaviors are actually an extension of intelligence.”
Machines have no behaviors. Your microwave has no behaviors.
Machines are not an extension of intelligence. They have nothing that was not programmed in.
“Computer. Tell me how to tie my shoes.” You’ll get nothing.
Relatd @68,
You keep saying the same thing. Are you familiar with the Turing test?
Have you tried asking your question to Alexa or Siri?
Maybe you’re simply choking on the term, artificial intelligence. Maybe “simulated intelligence” or “projected intelligence” would be more acceptable.
Didn’t you look at the link I provided you to Alpha Zero?
https://www.chessjournal.com/alphazero/
Artificial intelligence is not the same as human intelligence just as an “iron horse,” a term used for a steam locomotive in the early 1800s, is not the same as a biological horse. But an iron horse does the work of a biological horse. We even compare artificial horses using the term “horsepower,” and we also use “candelas” to compare artificial light sources with that of wax candles.
-Q
Turing test? No comprende. It’s not applicable. Something I have not said yet is this: Some companies want to get rid of workers, especially highly paid workers, so they buy automation/computers that can design/build things for them. Get rid of people, and make more money.
But as that happens, who will buy anything from Target?
Martin_r
Applications for genetic algorithms.
A company I worked for used them for programming FPGAs.
And there is Product-form design model based on genetic algorithms
Relatd:
No, that is evolutionism, ie the claim that life’s diversity arose via blind and mindless processes.
To say that ID is anti-evolution means it argues against things like anti-biotic resistance. That it argues against descent with modification. It doesn’t.
Relatd:
Clueless. They went the route that worked.
Relatd:
The Scientific American article refutes you. Reality refutes you.
Relatd:
Umm, that they have what was programmed into them means it is an extension of the intelligence of the programmer.
ET @75,
Exactly! Anyone who has ever done any programming would know this.
The information, logic, computations, and scope of responses that a program is capable of, exists first in the mind of the programmer, who articulates it in a form that is followed by a microprocessor, whether it’s in a military guidance system or a programmed sale on the stock exchange or a red flag in a tax return.
I don’t think anyone seriously proposes that such programs might “evolve” through random changes in the bits even after being filtered by a natural selection mechanism.
-Q
So you worked with algorithms …but you forgot to mention :
1.Repeated fitness function evaluation for complex problems is often the most prohibitive and limiting segment of artificial evolutionary algorithms. …
2.Genetic algorithms do not scale well with complexity.
3. Goal and randomness don’t fit together.
Ok. Me think like a weasel algorithms another darwinian “evidence” for evolution. What they call “genetic algorithms” is nothing more than a numerical method with no relation with complexity that exists in the cell . Darwinists tried to escape the insuperable problem of existence of information with another trick trying to mingle Darwin’s randomness with functional information and achievement of a goal that wasn’t there 🙂 but just happened . Indeed algorithms work in a limited class of problems but have nothing to do with the complexity of the cell .
The point is that genetic algorithms exemplify evolution by means of telic processes.
ET,
like i said, you sound like a Darwinist, you keep referring me to some articles.
Please show me physical products (like the antenna) engineered using an evo/genetic algorithm.
My apologies. I thought that you could read. You clearly don’t know how to use the internet. My bad.
Relatd
Touche.
ET argues with some scientific articles. I am sorry to say it again, but he sounds like a Darwinist.
Relatd
Well said. I would like to know, if Dr. Behe believes that humans are here by accident …
Relatd
as to AI hype:
"The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work"
https://www.theguardian.com/technology/2018/jul/06/artificial-intelligence-ai-humans-bots-tech-companies
AI joke:
How to start an AI startup
1. Hire a bunch of minimum wage humans to pretend to be AI pretending to be human
2. Wait for AI to be invented
Wow. Willful ignorance is not an argument. Looking at Martin_r and Relatd
Novel design of a dual-frequency power divider using genetic algorithms
Whoops! an invention that evolved! Add that to the antenna that also evolved.
Martin_r:
Unlike you and Relatd, Behe understands what “evolution” means. You 2 don’t seem to have a clue.
Sensor Data Processing Using Genetic Algorithms
Genetic algorithms are used to derive designs of automobiles that satisfy constraints such as low fuel consumption.
In robotics, genetic algorithms are used to provide insight into the decisions a robot has to make. For instance, given an environment, suppose a robot has to get to a specific position using the least amount of resources. Genetic algorithms are used to generate optimal routes the robot could use to get to the desired position.
Even a spreadsheet typically contains formulas to calculate values in other columns. Such spreadsheets are visually and mathematically indistinguishable from generated ones. BUT . . .
The intelligence to create them ultimately traces back to an intelligent agent, the ultimate SOURCE of information.
-Q
ET at 73,
Engineers have been doing work like this for decades and the people in charge want to take away their jobs so they can give it to machines and pocket the money. Clueless.
How will anyone buy anything from Target?
ET at 87,
More fiction. I think most people reading have no idea how actual engineering and design works in the real world. It is now possible to create a realistic image of a new truck design, project it and then invite prospective buyers in to get their views. In one case, a pickup truck was rejected because the grille looked “too girly.” The engineers and designers had to translate that into English so they could make the necessary changes, which they did. Producing a grille that was more manly.
Replace engineers with programs and Target will go out of business.
ET,
i don’t want to escalate this conversation, but you keep confirming what i wrote earlier. Look at all your examples … all of it, it is just an optimization of existing things …
Like i said, EA/GA just another word for optimization algorithms. It has nothing to do with inventing new things from scratch. Basically, it has nothing to do with everyday engineering, the use of EA/GA is very very limited like i pointed out earlier. (see my post about robotics companies survey)
One more note regarding the antenna…. no EA/GA will tell you, then you need an antenna to receive a signal… first you have to invent the antenna (including materials the antenna is made of). Then, eventually, you can optimize the shape of that antenna.
Moreover, as far as i know, this antenna was designed for NASA spacecraft. That means, it is a single piece(s). No mass production. It is very possible, when there would be a need to manufacture such an antenna in large amounts, engineers would revert to more simple antenna design to lower the production costs, and ignore EA/GA results (and still have a pretty good antenna)
ET,
and one more thing regarding the materials (e.g. the NASA antenna is made of)
The cell is an engineering marvel… no doubts … but what amazes me, is how the cell creates all the needful hi-tech materials at body temperature (e.g. bones, ceramic teeth)… no blast furnace is needed… no material suppliers are needed … the cell creates everything, a complete product … this is an engineering SCI-FI … look at 3D-printers … if you want to print something, you need to add a filament …
Another firm that I’m familiar with designed high-voltage electrical insulators for transmission lines. I’m sure most people know what I’m talking about.
There are several materials available for the core, which come only in certain diameters, there are several available disks or cups that can be made from insulating materials, the lengths are in increments of the disks or cups, and there are also several styles of end connectors available.
Each combination and its dimensions have different electrical properties. What this company did was create a program that accepted a customer’s specifications and their routine provided approximations closest to their specifications that they could choose from, along with their prices.
This is an example of “artificial intelligence” from the 1980s. It’s called AI because you can’t tell whether the output was generated by a human engineer or a program.
-Q
Martin_r- Learn how to do an internet search.
The antenna’s design is one that works. No one will redesign it if it needs to be mass produced.
Relatd- engineers are required to write the GAs.
Martin_r at 93,
Most 3-D printers that people can afford are junk. The stated resolution is low. The build area is small. The imperfections in the form of visible layers preclude making quality consumer products. Good 3-D printers cost thousands and are way beyond the budgets of most people. Even well-financed companies have to use these sparingly since all costs to operate it need to be factored in.
Martin_r @93,
I share your admiration for the astounding complexity within a cell and the instructions used for it to grow and maintain its interior structures. The cell certainly uses additive rather than subtractive technologies (such as cutting, milling, and turning) and doesn’t require melting anything at high temperatures.
As to additive manufacturing, you might be interested in exploring some of these technologies, including photopolymerization:
https://www.sciencedirect.com/topics/engineering/additive-manufacturing-technology
The materials being used have also progressed significantly although the “grain” and orientation (based on its shape) certainly need to be taken into consideration. I’ve been particularly impressed by carbon-fiber impregnated materials and the ability to blend from one material into another.
-Q
Querius,
additive manufacturing vs. 3D-printing, what is difference ?
I can’t see any at the first sight.
I personally consider the cell as a very advanced 3D-printer. And i am not the only one. A time ago, i watched a TED talk, and to my surprise, this guy Riccardo Sabatini (obviously a Darwinian scientist) thinks the same:
https://www.ted.com/talks/riccardo_sabatini_how_to_read_the_genome_and_build_a_human_being/transcript
Martin-r @99,
AM is supposed to be a generic term covering a variety of technologies to contrast with material subtraction. 3D printing is one such AM technology, but the terms are now often used interchangeably. There are seven processes recognized by ISO:
https://youtu.be/_0dSVAEIixk?t=21
Here’s a fun example of the use of powder bed technology for an inconel exhaust manifold.
https://www.youtube.com/watch?v=4jbn0ah3u9E
Inconel is an extremely tough alloy when compared with stainless steel.
The cell is essentially a biosynthesis lab and fabrication center that’s fantastically more complex than anything humanity has ever created. And information is central to the processes within the cell.
-Q
Querius,
thank you for clarification.
I see there is a lot of progress in this field. Nice stuff.
Now, when you look at this high advanced human made technology, it still looks like a child play. Seriously, the theory of evolution occurs to me like a hoax, or a conspiracy. How can an mentally healthy educated 21st century person think, that the cell with all what it can, is a product of some blind unguided process ? The cell is an engineering marvel … i seriously doubt, that it ever will be reverse-engineered.
Martin_r @101
You’re most welcome. I’ve had many conversations with engineers on the subject who use AM for their work or projects. Applications go well beyond engineering. For example . . .
– An art director in the film industry once described how they laser scan an actor’s head and then 3D print it, so that makeup artists can try various experiments without requiring the actor to sit for them hours at a time.
– In the scientific press, one can read about 3D printing a liver using live cells, and calcium phosphate to print bones (the tiny perforations in the result promotes bone attachment to the prosthesis). I’m sure this is still experimental, but I know it’s been done with metal prosthetics.
In the course, I once took in the subject, I was amazed to learn that the crossover between AM and traditional injection molds was much higher than I’d ever imagined: about 100,000 units!
Yes, exactly! The more we learn about cells, the more complex and out-of-reach the biotechnology appears, which always the opposite of what’s expected. Consider that biologists once named the undifferentiated substance that filled cells “protoplasm.”
-Q