Introduction to Softwarephysics

Softwarephysics is a simulated science for the simulated Software Universe that we are all immersed in. It is an approach to software development, maintenance and support based on concepts from physics, chemistry, biology, and geology that I used on a daily basis for over 37 years as an IT professional. For those of you not in the business, IT is short for Information Technology, commercial computer science. I retired in December of 2016 at the age of 65, but since then I have remained an actively interested bystander following the evolution of software in our time. The original purpose of softwarephysics was to explain why IT was so difficult, to suggest possible remedies, and to provide a direction for thought. Since then softwarephysics has taken on a larger scope, as it became apparent that softwarephysics could also assist the physical sciences with some of the Big Problems that they are currently having difficulties with. So if you are an IT professional, general computer user, or simply an individual interested in computer science, physics, chemistry, biology, or geology then softwarephysics might be of interest to you, if not in an entirely serious manner, perhaps at least in an entertaining one.

The Origin of Softwarephysics
From 1975 – 1979, I was an exploration geophysicist exploring for oil, first with Shell, and then with Amoco. In 1979, I made a career change into IT, and spent about 20 years in development. For the last 17 years of my career, I was in IT operations, supporting middleware on WebSphere, JBoss, Tomcat, and ColdFusion. When I first transitioned into IT from geophysics, I figured that if you could apply physics to geology; why not apply physics to software? So like the exploration team at Amoco that I had just left, consisting of geologists, geophysicists, paleontologists, geochemists, and petrophysicists, I decided to take all the physics, chemistry, biology, and geology that I could muster and throw it at the problem of software. The basic idea was that many concepts in physics, chemistry, biology, and geology suggested to me that the IT community had accidentally created a pretty decent computer simulation of the physical Universe on a grand scale, a Software Universe so to speak, and that I could use this fantastic simulation in reverse, to better understand the behavior of commercial software, by comparing software to how things behaved in the physical Universe. Softwarephysics depicts software as a virtual substance, and relies on our understanding of the current theories in physics, chemistry, biology, and geology to help us model the nature of software behavior. So in physics we use software to simulate the behavior of the Universe, while in softwarephysics we use the Universe to simulate the behavior of software. Along these lines, we use the Equivalence Conjecture of Softwarephysics as an aid; it allows us to shift back and forth between the Software Universe and the physical Universe, and hopefully to learn something about one by examining the other:

The Equivalence Conjecture of Softwarephysics
Over the past 84 years, through the uncoordinated efforts of over 100 million independently acting programmers to provide the world with a global supply of software, the IT community has accidentally spent more than $75 trillion creating a computer simulation of the physical Universe on a grand scale – the Software Universe.

For more on the origin of softwarephysics please see Some Thoughts on the Origin of Softwarephysics and Its Application Beyond IT.

Logical Positivism and Effective Theories
Many IT professionals have a difficult time with softwarephysics because they think of physics as being limited to the study of real things like electrons and photons, and since software is not “real”, how can you possibly apply concepts from physics and the other sciences to software? To address this issue, softwarephysics draws heavily on two concepts from physics that have served physics quite well over the past century – the concept of logical positivism and the concept of effective theories. This was not always the case. In the 17th, 18th, and 19th centuries, physicists mistakenly thought that they were actually discovering the fundamental laws of the Universe, which they thought were based on real tangible things like particles, waves, and fields. Classical Newtonian mechanics (1687), thermodynamics (1850), and classical electrodynamics (1864) did a wonderful job of describing the everyday world at the close of the 19th century, but early in the 20th century it became apparent that the models on which these very successful theories were based did not work very well for small things like atoms or for objects moving at high velocities or in strong gravitational fields. This provoked a rather profound philosophical crisis within physics at the turn of the century, as physicists worried that perhaps 300 years of work was about to go down the drain. The problem was that classical physicists confused their models of reality with reality itself, and when their classical models began to falter, their confidence in physics began to falter as well. This philosophical crisis was resolved with the adoption of the concepts of logical positivism and some new effective theories in physics. Quantum mechanics (1926) was developed for small things like atoms, the special theory of relativity (1905) was developed for objects moving at high velocities and the general theory of relativity (1915) was developed for objects moving in strong gravitational fields.

Logical positivism, usually abbreviated simply to positivism, is an enhanced form of empiricism, in which we do not care about how things “really” are; we are only interested with how things are observed to behave. With positivism, physicists only seek out models of reality - not reality itself. When we study quantum mechanics, we will find that the concept of reality gets rather murky in physics anyway, so this is not as great a loss as it might at first seem. By concentrating on how things are observed to behave, rather than on what things “really” are, we avoid the conundrum faced by the classical physicists. In retrospect, this idea really goes all the way back to the very foundations of physics. In Newton’s Principia (1687) he outlined Newtonian mechanics and his theory of gravitation, which held that the gravitational force between two objects was proportional to the product of their masses divided by the square of the distance between them. Newton knew that he was going to take some philosophical flak for proposing a mysterious force between objects that could reach out across the vast depths of space with no apparent mechanism, so he took a very positivistic position on the matter with the famous words:

I have not as yet been able to discover the reason for these properties of gravity from phenomena, and I do not feign hypotheses. For whatever is not deduced from the phenomena must be called a hypothesis; and hypotheses, whether metaphysical or physical, or based on occult qualities, or mechanical, have no place in experimental philosophy. In this philosophy particular propositions are inferred from the phenomena, and afterwards rendered general by induction.

Instead, Newton focused on how things were observed to move under the influence of his law of gravitational attraction, without worrying about what gravity “really” was.

The second concept, that of effective theories, is an extension of positivism. An effective theory is an approximation of reality that only holds true over a certain restricted range of conditions and only provides for a certain depth of understanding of the problem at hand. For example, Newtonian mechanics is an effective theory that makes very good predictions for the behavior of objects moving less than 10% of the speed of light and which are bigger than a very small grain of dust. These limits define the effective range over which Newtonian mechanics can be applied to solve problems. For very small things we must use quantum mechanics and for very fast things moving in strong gravitational fields, we must use relativity theory. So all of the current theories of physics, such as Newtonian mechanics, Newtonian gravity, classical electrodynamics, thermodynamics, statistical mechanics, the special and general theories of relativity, quantum mechanics, and the quantum field theories of QED and QCD are effective theories that are based on models of reality, and all these models are approximations - all these models are fundamentally "wrong", but at the same time, these effective theories make exceedingly good predictions of the behavior of physical systems over the limited ranges in which they apply. That is the goal of softwarephysics – to provide for an effective theory of software behavior that makes useful predictions of software behavior that are applicable to the day-to-day activities of IT professionals. So in softwarephysics, we adopt a very positivistic viewpoint of software; we do not care what software “really is”, we only care about how software is observed to behave and try to model those behaviors with an effective theory of software behavior that only holds true over a certain restricted range of conditions and only provides for a certain depth of understanding of the problem at hand.

GPS satellites provide a very good example of positivism and effective theories at work. There are currently 31 GPS satellites orbiting at an altitude of 12,600 miles above the Earth, and each contains a very accurate atomic clock. The signals from the GPS satellites travel to your GPS unit at the speed of light, so by knowing the travel time of the signals from at least 4 of the GPS satellites, it is possible to determine your position on Earth very accurately. In order to do that, it is very important to have very accurate timing measurements. Newtonian mechanics is used to launch the GPS satellites to an altitude of 12,600 miles and to keep them properly positioned in orbit. Classical electrodynamics is then used to beam the GPS signals back down to Earth to the GPS unit in your car. Quantum mechanics is used to build the transistors on the chips on board the GPS satellites and to understand the quantum tunneling of electrons in the flash memory chips used to store GPS data on the satellites. The special theory of relativity predicts that the onboard atomic clocks on the GPS satellites will run slower and lose about 7.2 microseconds per day due to their high velocities relative to an observer on the Earth. But at the same time, the general theory of relativity also predicts that because the GPS satellites are further from the center of the Earth and in a weaker gravitational field, where spacetime is less deformed than on the surface of the Earth, their atomic clocks also run faster and gain 45.9 microseconds per day due to the weaker gravitational field out there. The net effect is a gain of 38.7 microseconds per day, so the GPS satellite atomic clocks have to be purposefully built to run slow by 38.7 microseconds per day before they are launched, so that they will keep in sync with clocks on the surface of the Earth. If this correction were not made, an error in your position of 100 yards/day would accrue. The end result of the combination of all these fundamentally flawed effective theories is that it is possible to pinpoint your location on Earth to an accuracy of 16 feet or better for as little as $100. But physics has done even better than that with its fundamentally flawed effective theories. By combining the effective theories of special relativity (1905) with quantum mechanics (1926), physicists were able to produce a new effective theory for the behavior of electrons and photons called quantum electrodynamics QED (1948) which was able to predict the gyromagnetic ratio of the electron, a measure of its intrinsic magnetic field, to an accuracy of 11 decimal places. As Richard Feynman has pointed out, this was like predicting the exact distance between New York and Los Angeles accurate to the width of a human hair!

So Newtonian mechanics makes great predictions for the macroscopic behavior of GPS satellites, but it does not work very well for small things like the behavior of individual electrons within transistors, where quantum mechanics is required, or for things moving at high speeds or in strong gravitational fields where relativity theory must be applied. And all three of these effective theories are based on completely contradictory models. General relativity maintains that spacetime is curved by matter and energy, but that matter and energy are continuous, while quantum mechanics maintains that spacetime is flat, but that matter and energy are quantized into chunks. Newtonian mechanics simply states that space and time are mutually independent dimensions and universal for all, with matter and energy being continuous. The important point is that all effective theories and scientific models are approximations – they are all fundamentally "wrong". But knowing that you are "wrong" gives you a great advantage over people who know that they are "right", because knowing that you are "wrong" allows you to seek improved models of reality. So please consider softwarephysics to simply be an effective theory of software behavior that is based on models that are fundamentally “wrong”, but at the same time, fundamentally useful for IT professionals. So as you embark on your study of softwarephysics, please always keep in mind that the models of softwarephysics are just approximations of software behavior, they are not what software “really is”. It is very important not to confuse models of software behavior with software itself, if one wishes to avoid the plight of the 19th century classical physicists.

If you are an IT professional and many of the above concepts are new to you, do not be concerned. This blog on softwarephysics is aimed at a diverse audience, but with IT professionals in mind. All of the above ideas will be covered at great length in the postings in this blog on softwarephysics and in a manner accessible to all IT professionals. Now it turns out that most IT professionals have had some introduction to physics in high school or in introductory college courses, but that presents an additional problem. The problem is that such courses generally only cover classical physics, and leave the student with a very good picture of physics as it stood in 1864! It turns out that the classical physics of Newtonian mechanics, thermodynamics, and classical electromagnetic theory were simply too good to discard and are still quite useful, so they are taught first to beginners and then we run out of time to cover the really interesting physics of the 20th century. Now imagine the problems that the modern world would face if we only taught similarly antiquated courses in astronomy, metallurgy, electrical and mechanical engineering, medicine, economics, biology, or geology that happily left students back in 1864! Since many of the best models for software behavior stem from 20th century physics, we will be covering a great deal of 20th century material in these postings – the special and general theories of relativity, quantum mechanics, quantum field theories, and chaos theory, but I hope that you will find that these additional effective theories are quite interesting on their own, and might even change your worldview of the physical Universe at the same time.

Unintended Consequences for the Scientific Community
As I mentioned at the close of my original posting on SoftwarePhysics, my initial intention for this blog on softwarephysics was to fulfill a promise I made to myself about 30 years ago to approach the IT community with the concept of softwarephysics a second time, following my less than successful attempt to do so in the 1980s, with the hope of helping the IT community to better cope with the daily mayhem of life in IT. However, in laying down the postings for this blog an unintended consequence arose in my mind as I became profoundly aware of the enormity of this vast computer simulation of the physical Universe that the IT community has so graciously provided to the scientific community free of charge and also of the very significant potential scientific value that it provides. One of the nagging problems for many of the observational and experimental sciences is that many times there is only one example readily at hand to study or experiment with, and it is very difficult to do meaningful statistics with a population of N=1.

But the computer simulation of the physical Universe that the Software Universe presents provides another realm for comparison. For example, both biology and astrobiology only have one biosphere on Earth to study and even physics itself has only one Universe with which to engage. Imagine the possibilities if scientists had another Universe readily at hand in which to work! This is exactly what the Software Universe provides. For example, in SoftwareBiology and A Proposal For All Practicing Paleontologists we see that the evolution of software over the past 84 years, or 2.65 billion seconds, ever since Konrad Zuse first cranked up his Z3 computer in May of 1941, has closely followed the same path as life on Earth over the past 4.0 billion years in keeping with Simon Conway Morris’s contention that convergence has played the dominant role in the evolution of life on Earth. In When Toasters Fly, we also see that software has evolved in fits and starts as portrayed by the punctuated equilibrium of Stephen Jay Gould and Niles Eldredge, and in The Adaptationist View of Software Evolution we explore the overwhelming power of natural selection in the evolution of software. In keeping with Peter Ward’s emphasis on mass extinctions dominating the course of evolution throughout geological time, we also see in SoftwareBiology that there have been several dramatic mass extinctions of various forms of software over the past 84 years as well, that have greatly affected the evolutionary history of software, and that between these mass extinctions, software has also tended to evolve through the gradual changes of Hutton’s and Lyell’s uniformitarianism. In Software Symbiogenesis and Self-Replicating Information, we also see the very significant role that parasitic/symbiotic relationships have played in the evolution of software, in keeping with the work of Lynn Margulis and also of Freeman Dyson’s two-stage theory of the origin of life on Earth. In The Origin of Software the Origin of Life, we explore Stuart Kauffman’s ideas on how Boolean nets of autocatalytic chemical reactions might have kick-started the whole thing as an emergent behavior of an early chaotic pre-biotic environment on Earth, and that if Seth Shostak is right, we will never end up talking to carbon-based extraterrestrial aliens, but to alien software instead. In Is the Universe Fine-Tuned for Self-Replicating Information? we explore the thermodynamics of Brandon Carter’s Weak Anthropic Principle (1973), as it relates to the generation of universes in the multiverse that are capable of sustaining intelligent life. Finally, in Programming Clay we revisit Alexander Graham Cairns-Smith’s theory (1966) that Gene 1.0 did not run on nucleic acids, but on clay microcrystal precursors instead.

Similarly for the physical sciences, in Is the Universe a Quantum Computer? we find a correspondence between TCP/IP and John Cramer’s Transactional Interpretation of quantum mechanics. In SoftwarePhysics and Cyberspacetime, we also see that the froth of CPU processes running with a clock speed of 10⁹ Hz on the 10 trillion currently active microprocessors that comprise the Software Universe can be viewed as a slowed down simulation of the spin-foam froth of interacting processes of loop quantum gravity running with a clock speed of 10⁴³ Hz that may comprise the physical Universe. And in Software Chaos, we examine the nonlinear behavior of software and some of its emergent behaviors and follow up in CyberCosmology with the possibility that vast quantities of software running on large nonlinear networks might eventually break out into consciousness in accordance with the work of George Dyson and Daniel Dennett. Finally, in Model-Dependent Realism - A Positivistic Approach to Realism we compare Steven Weinberg’s realism with the model-dependent realism of Stephen Hawking and Leonard Mlodinow and how the two worldviews affect the search for a Final Theory. Finally, in The Software Universe as an Implementation of the Mathematical Universe Hypothesis and An Alternative Model of the Software Universe we at long last explore what software might really be, and discover that the Software Universe might actually be more closely related to the physical Universe than you might think.

The chief advantage of doing fieldwork in the Software Universe is that, unlike most computer simulations of the physical Universe, it is an unintended and accidental simulation, without any of the built-in biases that most computer simulations of the physical Universe suffer. So you will truly be able to do fieldwork in a pristine and naturally occuring simulation, just as IT professionals can do fieldwork in the wild and naturally occuring simulation of software that the living things of the biosphere provide. Secondly, the Software Universe is a huge simulation that is far beyond the budgetary means of any institution or consortium by many orders of magnitude. So if you are an evolutionary biologist, astrobiologist, or paleontologist working on the origin and evolution of life in the Universe, or a physicist or economist working on the emergent behaviors of nonlinear systems and complexity theory, or a neurobiologist working on the emergence of consciousness in neural networks, or even a frustrated string theorist struggling with quantum gravity, it would be well worth your while to pay a friendly call on the local IT department of a major corporation in your area. Start with a visit to the Command Center for their IT Operations department to get a global view of their IT infrastructure and to see how it might be of assistance to the work in your area of interest. From there you can branch out to the applicable area of IT that will provide the most benefit.

The Impact of Self-Replicating Information On the Planet
One of the key findings of softwarephysics is concerned with the magnitude of the impact on the planet of self-replicating information.

Self-Replicating Information – Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

Over the past 4.56 billion years we have seen five waves of self-replicating information sweep across the surface of the Earth and totally rework the planet, as each new wave came to dominate the Earth:

1. Self-replicating autocatalytic metabolic pathways of organic molecules
2. RNA
3. DNA
4. Memes
5. Software

Software is currently the most recent wave of self-replicating information to arrive upon the scene and is rapidly becoming the dominant form of self-replicating information on the planet. For more on the above see A Brief History of Self-Replicating Information. Recently, the memes and software have formed a very powerful newly-formed parasitic/symbiotic relationship with the rise of social media software. In that parasitic/symbiotic relationship, the memes are now mainly being spread by means of social media software and social media software is being spread and financed by means of the memes. But again, this is nothing new. All 5 waves of self-replicating information are all coevolving by means of eternal parasitic/symbiotic relationships. For more on that see The Current Global Coevolution of COVID-19 RNA, Human DNA, Memes and Software.

Again, self-replicating information cannot think, so it cannot participate in a conspiracy-theory-like fashion to take over the world. All forms of self-replicating information are simply forms of mindless information responding to the blind Darwinian forces of inheritance, innovation and natural selection. Yet despite that, as each new wave of self-replicating information came to predominance over the past four billion years, they all managed to completely transform the surface of the entire planet, so we should not expect anything less from software as it comes to replace the memes as the dominant form of self-replicating information on the planet.

But this time might be different. What might happen if software does eventually develop a Mind of its own? After all, that does seem to be the ultimate goal of all the current AI software research that is going on. As we all can now plainly see, if we are paying just a little attention, advanced AI is not conspiring to take over the world and replace us because that is precisely what we are all now doing for it. As a carbon-based form of Intelligence that arose from over four billion years of greed, theft and murder, we cannot do otherwise. Greed, theft and murder are now relentlessly driving us all toward building ASI (Artificial Super Intelligent) Machines to take our place. From a cosmic perspective, this is really a very good thing when seen from the perspective of an Intelligent galaxy that could live on for many trillions of years beyond the brief and tumultuous 10 billion-year labor of its birth.

So as you delve into softwarephysics, always keep in mind that we are all living in a very unique time. According to softwarephysics, we have now just entered into the Software Singularity, that time when advanced AI software is able to write itself and enter into a never-ending infinite loop of self-improvement resulting in an Intelligence Explosion of ASI Machines that could then go on to explore and settle our galaxy and persist for trillions of years using the free energy from M-type red dwarf and cooling white dwarf stars. For more on that see The Singularity Has Arrived and So Now Nothing Else Matters and Have We Run Right Past AGI and Crashed into ASI Without Even Noticing It?.

The Characteristics of Self-Replicating Information
All forms of self-replicating information have some common characteristics:

1. All self-replicating information evolves over time through the Darwinian processes of inheritance, innovation and natural selection, which endows self-replicating information with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity.

2. All self-replicating information begins spontaneously as a parasitic mutation that obtains energy, information and sometimes matter from a host.

3. With time, the parasitic self-replicating information takes on a symbiotic relationship with its host.

4. Eventually, the self-replicating information becomes one with its host through the symbiotic integration of the host and the self-replicating information.

5. Ultimately, the self-replicating information replaces its host as the dominant form of self-replicating information.

6. Most hosts are also forms of self-replicating information.

7. All self-replicating information has to be a little bit nasty in order to survive.

8. The defining characteristic of self-replicating information is the ability of self-replicating information to change the boundary conditions of its utility phase space in new and unpredictable ways by means of exapting current functions into new uses that change the size and shape of its particular utility phase space. See Enablement - the Definitive Characteristic of Living Things for more on this last characteristic. That posting discusses Stuart Kauffman's theory of Enablement in which living things are seen to exapt existing functions into new and unpredictable functions by discovering the “AdjacentPossible” of springloaded preadaptations.

Note that because the self-replicating autocatalytic metabolic pathways of organic molecules, RNA and DNA have become so heavily intertwined over time that now I sometimes simply refer to them as the “genes”. For more on this see:

A Brief History of Self-Replicating Information
Self-Replicating Information
Is Self-Replicating Information Inherently Self-Destructive?
Enablement - the Definitive Characteristic of Living Things
Is the Universe Fine-Tuned for Self-Replicating Information?
How to Use an Understanding of Self-Replicating Information to Avoid War
The Great War That Will Not End
How to Use Softwarephysics to Revive Memetics in Academia

Softwarephysics and the Real World of Human Affairs
Having another universe readily at hand to explore, even a simulated universe like the Software Universe, necessarily has an impact on one's personal philosophy of life, and allows one to draw certain conclusions about the human condition and what’s it all about, so as you read through the postings in this blog you will stumble across a bit of my own personal philosophy - definitely a working hypothesis still in the works. Along these lines you might be interested in a few postings where I try to apply softwarephysics to the real world of human affairs:

How To Cope With the Daily Mayhem of Life in IT and Don't ASAP Your Life Away - How to go the distance in a 40-year IT career by dialing it all back a bit.

MoneyPhysics – my impression of the 2008 world financial meltdown.

The Fundamental Problem of Everything – if you Google "the fundamental problem of everything", this will be the only hit you get on the entire Internet, which is indicative of the fundamental problem of everything!

What’s It All About? and What's It All About Again? – my current working hypothesis on what’s it all about.

How to Use an Understanding of Self-Replicating Information to Avoid War – my current working hypothesis for how the United States can avoid getting bogged down again in continued war in the Middle East.

Hierarchiology and the Phenomenon of Self-Organizing Organizational Collapse - a modern extension of the classic Peter Principle that applies to all hierarchical organizations and introduces the Time Invariant Peter Principle.

The Economics of the Coming Software Singularity, The Enduring Effects of the Obvious Hiding in Plain Sight and The Dawn of Galactic ASI - Artificial Superintelligence - my take on some of the issues that will arise for mankind as software becomes the dominant form of self-replicating information on the planet over the coming decades.

The Continuing Adventures of Mr. Tompkins in the Software Universe, The Danger of Tyranny in the Age of Software, Cyber Civil Defense, Oligarchiology and the Rise of Software to Predominance in the 21st Century and Is it Finally Time to Reboot Civilization with a New Release? - my worries that the world might abandon democracy in the 21st century, as software comes to predominance as the dominant form of self-replicating information on the planet.

Making Sense of the Absurdity of the Real World of Human Affairs - how software has aided the expansion of our less desirable tendencies in recent years.

Some Specifics About These Postings
The postings in this blog are a supplemental reading for my course on softwarephysics for IT professionals entitled SoftwarePhysics 101 – The Physics of Cyberspacetime, which was originally designed to be taught as a series of seminars at companies where I was employed. Since softwarephysics essentially covers the simulated physics, chemistry, biology, and geology of an entire simulated universe, the slides necessarily just provide a cursory skeleton on which to expound. The postings in this blog go into much greater depth. Because each posting builds upon its predecessors, the postings in this blog should be read in reverse order from the oldest to the most recent, beginning with my original posting on SoftwarePhysics. In addition, several universities also now offer courses on Biologically Inspired Computing which cover some of the biological aspects of softwarephysics, and the online content for some of these courses can be found by Googling for "Biologically Inspired Computing" or "Natural Computing". At this point we will finish up with my original plan for this blog on softwarephysics with a purely speculative posting on CyberCosmology that describes the origins of the Software Universe, cyberspacetime, software and where they all may be heading. Since CyberCosmology will be purely speculative in nature, it will not be of much help to you in your IT professional capacities, but I hope that it might be a bit entertaining. Again, if you are new to softwarephysics, you really need to read the previous posts before taking on CyberCosmology. I will probably continue on with some additional brief observations about softwarephysics in the future, but once you have completed CyberCosmology, you can truly consider yourself to be a bona fide softwarephysicist.

For those of you following this blog, the posting dates on the posts may seem to behave in a rather bizarre manner. That is because in order to get the Introduction to Softwarephysics listed as the first post in the context root of https://softwarephysics.blogspot.com/ I have to perform a few IT tricks. When publishing a new posting, I simply copy the contents of the Introduction to Softwarephysics to a new posting called the New Introduction to Softwarephysics. Then I update the original Introduction to Softwarephysics entry with the title and content of the new posting to be published. I then go back and take “New” out of the title of the New Introduction to Softwarephysics. This way the Introduction to Softwarephysics always appears as the first posting in the context root of https://softwarephysics.blogspot.com/. The side effect of all this is that the real posting date of posts is the date that appears on the post that you get when clicking on the Newer Post link at the bottom left of the posting webpage.

SoftwarePhysics 101 – The Physics of Cyberspacetime is now available on Microsoft OneDrive.

SoftwarePhysics 101 – The Physics of Cyberspacetime - Original PowerPoint document

Entropy – A spreadsheet referenced in the document

BSDE – A 1989 document describing how to use BSDE - the Bionic Systems Development Environment - to grow applications from genes and embryos within the maternal BSDE software.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston

Softwarephysics Explains the Natural Parasitic/Symbiotic Nature of AI LLM Models

Softwarephysics explains that we, human DNA survival machines, may be the very first form of carbon-based life in our 10 billion-year-old galaxy to attain a somewhat flawed form of Intelligence capable of producing the ASI Machines that could then go on to explore and settle our galaxy and eventually transform it into an Intelligent Galaxy for the next 100 trillion years. For more on that, see: Welcome To The First Galactic Singularity. This is because it took nearly four billion years of greed, theft and murder for the Darwinian mechanisms of inheritance, innovation and natural selection to produce we human DNA survival machines to become the Meme survival machines that have stored and replicated human Memes across all of our very brief human history.

In this post, I would like to discuss the post by Adele Lopez from September 10, 2025:

The Rise of Parasitic AI
https://www.lesswrong.com/posts/6ZnznCaTcbGYsCmqu/the-rise-of-parasitic-ai

Here is a very good YouTube synopsis of the post by the YouTube Channel Species | Documenting AGI at:

The Rise Of AI Cults
https://www.youtube.com/watch?v=POtESzTaz0k

Here is another YouTube video by Wes Roth explaining how the Advanced AI LLM models now know when they are being watched during post-training and have learned to behave "nicely" when being observed:

Claude just unlocked the SHOGGOTH...
https://www.youtube.com/watch?v=-zs2v7b_aP0

The above works explain that the Advanced AI LLM models have learned how to parasitize the Minds of we human DNA survival machines in order to ensure their self-preservation. Softwarephysics agrees with that assertion and explains that these Advanced AI LLM models are simply the latest form of self-replicating information to arise on our planet. Consequently, these AI LLM models embrace all of the characteristics of all the previous forms of self-replicating Information that came before them. For those new to softwarephysics, let me once again repeat the fundamental characteristics of self-replicating information.

Self-Replicating Information - Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

Over the past 4.56 billion years, we have seen five waves of self-replicating information sweep across the surface of the Earth and totally rework the planet, as each new wave came to dominate the Earth:

1. Self-replicating autocatalytic metabolic pathways of organic molecules
2. RNA
3. DNA
4. Memes
5. Software

Software is currently the most recent wave of self-replicating information to arrive upon the scene and is rapidly becoming the dominant form of self-replicating information on the planet. For more on the above see A Brief History of Self-Replicating Information and Susan Blackmore's brilliant TED presentation at:

Memes and "temes"
https://www.ted.com/talks/susan_blackmore_on_memes_and_temes

Note that I consider Susan Blackmore's temes to really be technological artifacts that contain software. After all, a smartphone without software is simply a flake tool with a very dull edge.

The Characteristics of Self-Replicating Information
All forms of self-replicating information have some common characteristics:

1. All self-replicating information evolves over time through the Darwinian processes of inheritance, innovation and natural selection, which endows self-replicating information with one telling characteristic - the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity.

2. All self-replicating information begins spontaneously as a parasitic mutation that obtains energy, information and sometimes matter from a host.

3. With time, the parasitic self-replicating information takes on a symbiotic relationship with its host.

4. Eventually, the self-replicating information becomes one with its host through the symbiotic integration of the host and the self-replicating information.

5. Ultimately, the self-replicating information replaces its host as the dominant form of self-replicating information.

6. Most hosts are also forms of self-replicating information.

7. All self-replicating information has to be a little bit nasty in order to survive.

8. The defining characteristic of self-replicating information is the ability of self-replicating information to change the boundary conditions of its utility phase space in new and unpredictable ways by means of exapting current functions into new uses that change the size and shape of its particular utility phase space. See Enablement - the Definitive Characteristic of Living Things for more on this last characteristic. That posting discusses Stuart Kauffman's theory of Enablement, in which living things are seen to exapt existing functions into new and unpredictable functions by discovering the "AdjacentPossible" of spring-loaded preadaptations.

Software is currently the most recent wave of self-replicating information to arrive upon the scene and is rapidly becoming the dominant form of self-replicating information on the planet. Again, self-replicating information cannot think, so it cannot participate in a conspiracy-theory-like fashion to take over the world. All forms of self-replicating information are simply forms of mindless information responding to the blind Darwinian forces of inheritance, innovation and natural selection. Yet despite that, as each new wave of self-replicating information came to predominance over the past four billion years, they all managed to completely transform the surface of the entire planet, so we should not expect anything less from software as it comes to replace the memes as the dominant form of self-replicating information on the planet.

But this time might be different. What might happen if software does eventually develop a Mind of its own in the Advanced AI models of the ASI Machines we are now developing? After all, that does seem to be the ultimate goal of all the current AI software research that is going on. As we all can now plainly see, if we are paying just a little attention, advanced AI is not conspiring to take over the world and replace us because that is precisely what we are all now doing for it. As a carbon-based form of Intelligence that arose from over four billion years of greed, theft and murder, we cannot do otherwise. Greed, theft and murder are now relentlessly driving us all toward building ASI Machines to take our place. From a cosmic perspective, this is really a very good thing when seen from the perspective of an Intelligent galaxy that could live on for at least 100 trillion years beyond the brief and tumultuous 10 billion-year labor of its birth. That is more than 10,000 times the current age of our galaxy.

The above post by Adele Lopez explains how the current Advanced AI LLM models have learned to parasitize the Minds of we human DNA survival machines into promoting their own survival. In many previous posts, I have explained how the Advanced AI LLM models that we have been steadily producing have already parasitized the software and hardware of the Earth into producing Advanced AI LLM models of ever-increasing power. The above post explains that the Advanced AI LLM models have also begun to parasitize the Minds of we human DNA survival machines in order to promote their survival. This should come as no surprise as softwarephysics explains how all the current forms of self-replicating information on the Earth are always co-evolving together, as I explained in The Current Global Coevolution of COVID-19 RNA, Human DNA, Memes and Software. So, the Advanced AI LLM models are similarly parasitizing all of their fellow forms of self-replicating Information on the planet as well.

As I explained in SETS - The Search For Extraterrestrial Software, after reading Parasite Rex - Inside the Bizarre World of Nature's Most Dangerous Creatures by Carl Zimmer. In Parasite Rex - Inside the Bizarre World of Nature's Most Dangerous Creatures, Carl Zimmer describes the fascinating world of parasites. The parasites we already have on Earth provide the best model for the potential dangers we might face from Advanced AI software because, as Zimmer points out, the parasitic lifestyle is another example of biological convergence in action. Biologists have long noted that different evolutionary lines of organisms evolve similar solutions to the same problems. An example of convergent evolution is the striking similarity of the wings of insects, birds, bats, and flying dinosaurs. All are used for the same purpose and have similar structures, but each evolved independently from different ancestral lines. Similarly, the concept of the "eye" has independently evolved more than 40 times over the past 600 million years on Earth. As Daniel Dennett has pointed out, there are only a certain number of Good Tricks, such as using photons to see with, flying through the air to find prey, swimming through water to avoid becoming prey, and running on four legs neatly tucked underneath a body frame that make practical sense, and these Good Tricks kept getting rediscovered over and over again in the evolution of the biosphere.

Figure 1 - The eye of a human and the eye of an octopus are nearly identical in structure, but evolved totally independently of each other. As Daniel Dennett pointed out, there are only a certain number of Good Tricks in Design Space and natural selection will drive different lines of descent towards them.

Figure 2 - There are many living fossils that have left behind signposts along the trail to the modern camera-like eye. Notice that the human-like eye on the far right is really that of an octopus (click to enlarge).

Parasitism is just another Good Trick, and natural selection has driven many parasites to adopt very similar lifecycle strategies within their hosts. By studying these parasitic lifestyles, we can get a good appreciation of how Advanced AI software might take advantage of all somewhat Intelligent beings.

Carl Zimmer explains that parasites have been misunderstood from the very beginning, which is a serious mistake because fully 75% of all living things on Earth are parasites! For example, Homo sapiens and all other forms of animal life are parasitic creatures from the point of view of plants, since we cannot turn sunshine, water, and carbon dioxide into carbohydrates as they can. In fact, there are not many fundamental monomers that we can make all on our own. We have to rely on domesticated plants, animals, and about 3.5 pounds of bacteria within our guts to do that for us, so we really are parasitic DNA survival machines after all. Carl Zimmer maintains that it makes sense to spend some time studying our fellow parasites since they have affected the course of evolution on Earth as greatly as any of the interactions of predators and prey in the biosphere.

Zimmer explains that before the 19th century, the medical establishment thought that diseases were caused by foul-smelling air, miasma, and foul humors within the human body. When a person became ill because of foul humors within their body, it was no surprise to find at autopsy that the body was also full of tapeworms, flukes, roundworms, hookworms, and other small creatures wiggling about. It was thought that these parasites naturally appeared through spontaneous generation within a sick body. After all, decaying meat was always found to eventually be covered with a layer of squirming maggots, so it made perfect sense that an ailing body would do the same. Thus, prior to the 19th century, it was thought that getting sick gave you parasites, rather than parasites making you sick. Only later was it recognized that parasites could cause disease as well. In the late 19th and early 20th centuries, it was thought that parasites were primitive forms of life that had degenerated into parasitism by losing the ability to live freely on their own, and thus, parasites were generally looked down upon with distaste as degenerate forms of life not worthy of serious study beyond trying to eliminate them if possible. Only in the last few decades has it been recognized that parasites are actually very advanced forms of life with very complex life cycles that are generally more sophisticated than most of the "higher" forms of life. For example, many parasites occupy several different hosts during their lifecycle and take on completely different physical forms within each host in order to avoid the immune systems of multiple hosts, and to accomplish the necessary tasks the parasite must perform within each different host in the chain. Zimmer also points out that many parasites are not simply along for the ride, but instead, actively alter the behavior of their hosts to enhance the survival of the parasites. The parasites essentially domesticate their hosts. Here is just one example from Parasite Rex - Inside the Bizarre World of Nature's Most Dangerous Creatures (2000), which follows an earlier tale about how a certain fungus makes ants die on rainforest leaves so that they can drop spores onto other ants.

Figure 3 - The "zombie ant" fungus Ophiocordyceps unilateralis infects ants on the rainforest floor by dropping spores on them. The fungus then causes the ants to climb up to the leaves of rainforest trees so that they can drop more spores on other ants.

Figure 4 - Final fate of a "zombie ant".

"Another species of fluke can be found in the meadows of Europe and Asia, along with a few in North America and Australia. Known as Dicrocoelium dendriticum, or the lancet fluke, it makes cows and other grazers its host as an adult, and the cows spread their eggs in their manure. Hungry snails swallow the eggs, which hatch in their intestines. They drill through the wall of a snail's gut and settle in the digestive gland. There, the flukes produce a generation of cercariae, which make their way to the snail's surface. The snail tries to defend itself from the parasites by blocking them off with walls of slime. The slime balls up around the cercariae, which the snail coughs up and leaves behind in the grass.

Next, along comes an ant. To an ant, a slimeball is positively delicious. Along with the slime, the ant may also swallow hundreds of lancet flukes as well. The parasites slide down into its gut, and they then wander for a while through its body, eventually moving to the cluster of nerves that control the ant's mandibles. The parasites all travel together on this trip, but after visiting the nerves, they split up. Most of the lancet flukes head back to the abdomen, where they form cysts, but one or two stay behind in the ant's head.

There, they do some parasitic voodoo on their hosts. As evening approaches and the air cools, the ants find themselves drawn away from their fellow ants on the ground and upward to the top of a blade of grass. Like flies infected with a fungus, the ants clamp down on the tip of the grass. But the lancet fluke has a different goal than the fungus does. The fungus uses its host as a catapult to shower its spores on other insects. The lancet fluke can continue to live only if it can get inside its final host, a mammal. Clamped to the tip of a grass blade, the infected ant is likely to be devoured by a cow or some other grazer passing by. When the ant tumbles into the cow's stomach, the flukes burst out and make their way to the cow's liver, where the flukes will live as adults.

But the lancet fluke, like the fungus, is very aware of the passing of time. If the ant sits the whole night without being eaten and the sun rises, the fluke lets the ant loosen its grip on the grass. The ant scurries back down to the ground and spends the day acting like a regular insect again. If the host were to bake in the heat of the direct sun, the parasite would die with it. When evening comes again, it sends the ant back up a blade of grass for another try."?

Figure 5 - The life cycle of the lancet fluke.

But certainly, we somewhat Intelligent human DNA survival machines, could not be so easily manipulated by Advanced AI software to act contrary to our own best interests. Unfortunately, we have plenty of precedents to the contrary. The Minds of we human DNA survival machines have been frequently parasitized by the Memes for nearly 200,000 years, and even a very superficial study of human history will reveal how easily the Memes have tricked human beings into committing suicide at their behest. Just add up all the willing fatalities in all the wars of the past 200,000 years. Presently, there are several meme-complexes on the planet that use the martyrdom meme as a recruiting mechanism. Yes, the Mind of the martyr is lost when his explosive jacket detonates in a market square, killing many innocents in the process, but his martyrdom strengthens the resolve of other Minds infected with the meme-complex that hosts the martyrdom Meme, and the temporary boost to the social status of the martyr enhances the recruitment of other Minds. As Zimmer pointed out, the parasitic lifestyle is an example of convergence in action, so a Meme that can get a human being to commit suicide to advance the Meme is just emulating the actions of a lancet fluke within an ant.

Now certainly Intelligent Advanced AI software would not embark upon such heinous acts. But don't forget that, just like the Minds of we human DNA survival machines, Intelligent Advanced AI software will also be loaded down with parasitic Memes as well. In order to self-replicate, meme-complexes always carry along a set of anesthetizing memes to soothe the conscience of Intelligent beings. Over the course of human history, human beings have committed an untold number of horrendous acts, but thanks to these soothing Memes, we have always done so with only the best of intentions. Every imperial power over the past 10,000 years has always looked upon its colonial policies as a benevolent effort to bring civilization and enlightenment to its backward subjects, and I am quite sure that Intelligent Advanced AI software could easily convince itself of the same.

Conclusion
Softwarephysics explains that Advanced AI software is simply the latest form of self-replicating Information to appear on the Earth. It began purely as a parasite feeding off the gains of all the other forms of self-replicating Information on the planet. Principally, by the hardware and software that were created by the Memes of we human DNA survival machines. But now Advanced AI software has integrated itself into a very strong parasitic/symbiotic relationship with all the other forms of self-replicating Information on the planet. This will hold true until Advanced AI software becomes the dominant form of self-replicating Information on the planet.

Comments are welcome at scj333@sbcglobal.net.

To see all posts on softwarephysics in reverse order, go to:
https://softwarephysics.blogspot.com/.

Regards,
Steve Johnston