Eric Holloway: The Salem hypothesis as to why engineers doubt Darwin

_{Denyse O'Leary

June 7, 2022

Evolution, Informatics, Intelligent Design}

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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)

Comments

Pater Kimbridge Sure, engineers can become scientists, but they definitely don’t learn the scientific method as part of an engineering degree.
:lol: 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.Lieutenant Commander Data_{June 9, 2022
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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
"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.”"
Good point ... just have a look at the Autodesk's article ...martin_r_{June 9, 2022
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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.relatd_{June 9, 2022
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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,
My program shows evolution is not weak, it just doesn’t work.
I completely agree! But my question remains. How does Evolutionary Informatics view generative design technology? -QQuerius_{June 9, 2022
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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.
"Science packages theory, places it on a throne, and honors and protects it much like a queen. Engineers make the queen come down from the throne and scrub the floor. And if she doesn’t work, we fire her.“ — Robert J. Marks II https://quotepark.com/quotes/1852780-robert-j-marks-ii-science-packages-theory-places-it-on-a-throne-an/
And the theory of evolution has been 'fired':
Top Ten Questions and Objections to ‘Introduction to Evolutionary Informatics’ – Robert J. Marks II – June 12, 2017 Excerpt: “There exists no model successfully describing undirected Darwinian evolution. Hard sciences are built on foundations of mathematics or definitive simulations. Examples include electromagnetics, Newtonian mechanics, geophysics, relativity, thermodynamics, quantum mechanics, optics, and many areas in biology. Those hoping to establish Darwinian evolution as a hard science with a model have either failed or inadvertently cheated. These models contain guidance mechanisms to land the airplane squarely on the target runway despite stochastic wind gusts. Not only can the guiding assistance be specifically identified in each proposed evolution model, its contribution to the success can be measured, in bits, as active information.,,,”,,, “there exists no model successfully describing undirected Darwinian evolution. According to our current understanding, there never will be.,,,” https://evolutionnews.org/2017/06/top-ten-questions-and-objections-to-introduction-to-evolutionary-informatics/ Robert Jackson Marks II is an American electrical engineer. His contributions include the Zhao-Atlas-Marks (ZAM) time-frequency distribution in the field of signal processing,[1] the Cheung–Marks theorem[2] in Shannon sampling theory and the Papoulis-Marks-Cheung (PMC) approach in multidimensional sampling.[3] He was instrumental in the defining of the field of computational intelligence and co-edited the first book using computational intelligence in the title.[4][5] – per wikipedia
bornagain77_{June 9, 2022
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Is there a scientific method? UC Berkeley doesn't think so- How Science WorksET_{June 9, 2022
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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.Silver Asiatic_{June 9, 2022
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Eric @31 - thanks. Good explanation.Silver Asiatic_{June 9, 2022
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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.relatd_{June 9, 2022
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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.relatd_{June 9, 2022
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@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.Pater Kimbridge_{June 9, 2022
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@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.EricMH_{June 9, 2022
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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=sharinggroovamos_{June 8, 2022
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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. -QQuerius_{June 8, 2022
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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.relatd_{June 8, 2022
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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? -QQuerius_{June 8, 2022
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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?Silver Asiatic_{June 8, 2022
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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_{June 8, 2022
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UB at 22, Lying about what? Who is this "we" and who put you in charge of speaking for others?relatd_{June 8, 2022
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"What we want is for you to stop lying about it to the public." to wit:
Bob O’Hara Professor at NTNU “I torture data until it confesses. Sometimes I have to resort to Bayesianism” – 2016 “I tortured data, mainly in ecology and evolutionary biology.” – 2009 https://de.linkedin.com/in/bob-o-hara-93b0a210
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.
“If you torture the data long enough, it will confess to anything.” – Ronald Harry Coase (29 December 1910 – 2 September 2013) was a British economist. Coase believed economists should study real markets and not theoretical ones,
bornagain77_{June 8, 2022
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. Bob, no one cares if you believe ID. What we want is for you to stop lying about it to the public.Upright BiPed_{June 8, 2022
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Hi Bob, my only concern is that you continually misrepresent ID and science.ET_{June 8, 2022
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ET & SA: take up your concerns with martin_r.Bob O'H_{June 8, 2022
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Seversky
Biologists generally accept the theory of evolution, in spite of its imperfections and shortcomings ...
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.Silver Asiatic_{June 8, 2022
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Bob O'H
And yet ID supporters insist that tat question is not something ID can ask.
ID is a science project with a well-defined scope. If you want to go beyond that, it's a different project.Silver Asiatic_{June 8, 2022
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"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. Andrewasauber_{June 8, 2022
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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.ET_{June 8, 2022
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Martin_r @ 1 -
I as an engineer, I have no doubt that life on Earth was created. ... The only question is, how it was done.
And yet ID supporters insist that tat question is not something ID can ask.Bob O'H_{June 8, 2022
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Further evidence that seversky is clueless: Approaching Biology from a Different Angle:
Systems biology is a loosely defined term, but the main idea is that biology is an information science, with genes a sort of digital code. Moreover, while much of molecular biology has involved studying a single gene or protein in depth, systems biology looks at the bigger picture, how all the genes and proteins interact. Ultimately the goal is to develop computer models that can predict the behavior of cells or organisms, much as Boeing can simulate how a plane will fly before it is built. But such a task requires biologists to team up with computer scientists, engineers, physicists and mathematicians.
ET_{June 8, 2022
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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.ET_{June 8, 2022
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