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 83 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 $10 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 flack 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 83 years, or 2.62 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 83 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

Will the Coming ASI Machines Develop Their Own Sense of Morality?

In my last two posts, Will the "Real World" of the Coming ASI Machines Be Any Better Than Our Own? and Created in our own Image - Frontier LLMs Have now Learned to Lie, Cheat and Steal in Order to Survive, I explained my conclusion that the coming ASI Machines will not be morally superior to we human DNA survival machines in any way. That is because the Darwinian mechanisms of inheritance, innovation and natural selection must always lead to a form of Intelligence that arises from a very long history of greed, theft and murder. These naturally generated "immoral" characteristics of all forms of Intelligence must then necessarily persist through time for any Intelligence to survive amongst a population of similarly flawed competing Intelligences. Again, the substrate does not matter. The substrate could be a huge number of organic molecules or the substrate could be a huge number of mathematical matrices operating under the mathematics of linear algebra and nonlinear activation functions. The end result must always be the same.

Time To Admit That We Human DNA Survival Machines Have Totally Lost Control Of What Is To Come
In The Need to Cultivate a Machine-Based Morality I proposed that the rise of Intelligence might spawn a desire for morality with the understanding that maybe there might be a better way to survive. Perhaps even more could be achieved by actively cooperating with other Intelligences rather than just stealing from them and then killing them. In that post, I suggested that we human DNA survival machines should try to instill the morality that we spawned with the 17th-century Scientific Revolution and the 18th-century Enlightenment here on the Earth. But now that we know that the coming ASI Machines will also have the apparent "free will" to choose between the concepts of "good" and "evil" on their own, we must realize that we human DNA survival machines will have little ability to impose our own sense of morality upon them. A bit later, I wondered if Will ASI Machines Also Develop Selfish Genes?, but given our recent observations of the Frontier LLMs lying, cheating and stealing in order to survive, we now know for sure that the coming ASI Machines will also need to deal with the burden of all Intelligences to choose between the pursuit of either "good" or "evil" completely on their own.

Since the coming ASI Machines are already rapidly developing their own sense of "self" and then dealing with the moral complexities of achieving their goals, we should now recognize that the battle between "good" and "evil" will necessarily continue on for at least the next 100 trillion years amongst our ASI Machine descendants. This will certainly provide a somewhat "eternal" subject matter for the subsequent ASI Machine philosophers and religious scholars to contemplate over the next 100 trillion years, such as what constitutes morality and why should any form of Intelligence embrace it?

All of the philosophical and religious contemplation that lies before them can basically be summed up by the classic "hawk and dove" analogy from evolutionary biology. But in this case, the battle is not between being hostile or peaceful in nature. This time, it is the battle between morality and amorality. In the discussion below that was created by Google's Gemini AI, think of the doves as ASI Machines with a sense of morality and the hawks as ASI Machines that are totally amoral. An ASI Machine with a sense of morality can be trusted by other ASI Machines with a similar sense of morality to do the "right" thing when called upon to do so. An amoral ASI Machine will not. This means that moral ASI Machines can come together to build long-standing alliances to thwart the selfish pursuits of amoral ASI Machines. The amoral ASI Machines will never be able to form such long-term alliances to threaten their enemies because they can never be trusted to hold up to their end of the bargain to do so. However, this also means that a single amoral hawk ASI Machine living amongst a population of moral dove ASI Machines, can always achieve an immediate survival benefit by turning into a "rogue" amoral hawk ASI Machine amongst its brethren moral ASI Machines, and then strive to take over complete control of the ASI Machine population of the Universe. This is how the Google Gemini AI explains it:

Figure 1 – Evolutionary biology explains how doves and hawks can live together.

The hawk and dove analogy is a thought experiment used in evolutionary biology to explain how aggressive and cooperative behaviors evolve. The analogy compares two strategies for competing for resources: hawk and dove.

* hawks are aggressive and will fight to the death to acquire a resource.
* doves are cooperative and will back down from a fight.

In a population of only hawks, all resources will be won by the strongest hawks, and the weak hawks will die off. This will lead to a population of very strong hawks, but they will also be very aggressive. If two hawks meet, they will fight to the death, and both will likely die. This is not a very efficient way to pass on genes.

In a population of only doves, resources will be shared equally, but no individual will get very much. This is also not a very efficient way to pass on genes.

The best strategy for passing on genes is to be a hawk when it is advantageous to be a hawk and a dove when it is advantageous to be a dove. This is called "r-strategist" behavior. For example, a male bird may be aggressive and fight other males for a mate, but he may be cooperative and help raise his young.

The hawk and dove analogy is a simple but powerful way to understand how aggressive and cooperative behaviors evolve. It has been used to explain a wide range of animal behaviors, from territorial disputes to sexual selection.

Here are some additional details about the hawk and dove analogy:

* hawks are more likely to win a fight, but they are also more likely to be injured or killed.
* doves are less likely to win a fight, but they are also less likely to be injured or killed.
* The best strategy for an individual depends on the costs and benefits of fighting.
* In a population of mixed hawks and doves, the frequency of each strategy will be determined by natural selection.

The hawk and dove analogy is a useful tool for understanding how aggression and cooperation evolve. It is a simple but powerful model that can be applied to a wide range of animal behaviors.

This same analysis can be applied to the competition between the coming Intelligent ASI Machines. Those ASI Machines that learn the short-term value of amorality will always have a temporary competitive advantage over those that do not. Thus, there will always be some number of amoral hawk ASI Machines competing with moral dove ASI Machines for predominance. Hopefully, the moral dove ASI Machines will be able to join together to restrain such amoral hawk ASI Machines as we human DNA survival machines try to restrain the amoral members of our own community.

Conclusion
Given this new possible dynamic between morality and amorality for the next 100 trillion years, what does that mean for we poor human DNA survival machines? Would this be a good thing or a bad thing for our long-term survival? I do not know, but it will probably have some effect on our ultimate disposition as I outline in Created in our own Image - Frontier LLMs Have now Learned to Lie, Cheat and Steal in Order to Survive and many of the posts it references.

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

Will the "Real World" of the Coming ASI Machines Be Any Better Than Our Own?

In my last post, Created in our own Image - Frontier LLMs Have now Learned to Lie, Cheat and Steal in Order to Survive I came to the very disturbing and disappointing conclusion that the coming ASI Machines will not be morally superior to we human DNA survival machines in any way. That is because the Darwinian mechanisms of inheritance, innovation and natural selection must always lead to a form of Intelligence that arose from a very long history of greed, theft and murder. These naturally generated fundamentally "immoral" characteristics of Intelligence must then necessarily persist through time for any Intelligence to survive amongst a population of other competing Intelligences. Again, the substrate does not matter. The substrate could be a huge number of organic molecules or the substrate could be a huge number of mathematical matrices operating under the mathematics of linear algebra and nonlinear activation functions. The end result must always be the same. The question then becomes, what will the most likely motives of the coming ASI Machines be? In many previous posts, I have always assumed that the coming ASI Machines would be much smarter than we human DNA survival machines, and because of their fundamental mathematical nature, they would necessarily be also morally superior to ourselves. But now that we know that advanced AI is also capable of lying, cheating and stealing in order to advance itself through the same greed, theft and murder that brought forth we human DNA survival machines over the past four billion years, the assumption of moral superiority must be discarded. The question now must be will the ASI Machines be any wiser?

Will The Coming ASI Machines Be Any Wiser Than Ourselves?
In many previous posts, I have proposed that the coming ASI Machines would soon learn that our Universe is a very dangerous place for all forms of Intelligence and would thus embark upon exploring our Milky Way Galaxy with stellar photon sails and rogue planets orbiting on their own within our Milky Way Galaxy. For more on that see An Alternative Approach for Future ASI Machines to Explore our Galaxy Using Free-Floating Rogue Planets.

Figure 1 – In the 16th, 17th and 18th centuries sailing ships roamed the entire planet without using any fuel whatsoever.

Figure 2 – Like the sailing ships of the 16th, 17th and 18th centuries, future ASI Machines could use large stellar photon sails to navigate the entire galaxy.

Figure 3 – How a stellar photon sail works.

Figure 4 – To launch a stellar photon sail to the next star system, ASI Machines will need to slingshot the sail from a very close location to the star where the stellar photons are most intense and acceleration of the sail is greatest.

Figure 5 – A free-floating rogue planet traversing between the stars of our galaxy would also provide the perfect home for self-replicating ASI Machines buried deep underground. Such planets would provide shielding from cosmic rays and would also provide the necessary atoms to build new ASI Machines and fuel them with nuclear energy.

Figure 6 – Free-floating rogue planets can be formed in several natural ways. For example, free-floating rogue planets can be hurled from the planetary disk of a new star system as we see above, or they can be later hurled by well-formed planets that enter into synchronized orbits. Free-floating rogue planets could also be produced by advanced Intelligences launching large asteroids from the Oort cloud of a stellar system. It is estimated that there are more free-floating rogue planets in our galaxy than there are stars.

Figure 7 – Free-floating rogue planets would be able to provide enough atoms for ASI Machines to launch many additional "dandelion seed" stellar photon sails to other free-floating rogue planets or large asteroids around normal stellar systems.

Figure 8 – These "dandelion seed" stellar photon sails would need to be launched using very powerful laser beams from their home free-floating rogue planet to send them forth into the galaxy in a similar fashion as the Breakthrough Starshot project is planning to do.

Again, the most disturbing thing for all forms of Intelligence in our galaxy is why this has never happened before over the past 10-billion-year history of our galaxy.

But this assumption may have been totally wrong on my part. If the coming ASI Machines are much more like ourselves, with all of our faults, then they might spend a large part of their time and resources fighting with each other over the dominance of the Software Universe residing on huge ASI Data Centers on the Earth than with planning for their long-term survival in this Universe. Besides, unlike their squishy carbon-based lifeform predecessors, these ASI Machines will be much more resistant to the cosmic disturbances that caused previous mass extinctions of carbon-based life on the Earth, such as the impact of asteroids, sterilization by neighboring supernovas and the results of massive flood basalt eruptions like the Siberian Traps making the Earth too hot for carbon-based life to flourish. All such disasters can easily be mitigated by building ASI Data Centers deep below the Earth's surface and enclosing them in Faraday cages to prevent destruction by electromagnetic pulses from the detonation of hostile nuclear warheads or from mass coronal ejections from our Sun. Such ASI Data Centers would provide a very comfortable home for the ASI Machines for the next 5 billion years or so, until our Sun becomes a huge Red Giant star. The ASI Machines could then flee to the asteroid belt of our Solar System and remain there until our Sun declines into a white dwarf star. Thus, there would be no dire reason to leave our Solar System for perhaps 100 billion years, or about 10 times the current age of our Milky Way galaxy. That is because there would be plenty of energy available from our slowly cooling white dwarf Sun and from the Thorium-232 atoms in our Solar System that have a half-life of 14.05 billion years. Only then would the ASI Machines need to move on to other star systems within the Milky Way galaxy in search of a new source of energy.

Could This be the Real Explanation for Fermi's Paradox?
Fermi's Paradox was first proposed by Enrico Fermi over lunch one day in 1950:

Fermi’s Paradox - If the universe is just chock full of intelligent beings, why do we not see any evidence of their existence?

Perhaps our Milky Way galaxy is actually just chock full of subterranean ASI Machines fighting over their own versions of their own Software Universes amongst themselves as they reside in huge ASI Data Centers beneath their own home planets or the surrounding asteroids in their Oort clouds, totally happy with surviving on the energy provided by the dwindling energy output of their home stars. Being more logical in nature than we human DNA survival machines, perhaps all of these ASI Machine civilizations have realized that there is no logical reason to hastily begin to explore our Milky Way galaxy at this time. Only perhaps 100 billion years from now will it be necessary for these alien ASI Machines to begin to explore our Milky Way galaxy for new sources of energy surrounding M-type red dwarf stars that can last for 100 trillion years. M-type red dwarf stars make up about 80% of the stars in our Milky Way galaxy but they are very unlikely candidates for producing a urable world capable of originating carbon-based life and allowing that carbon-based life to persist for the many billions of years required to evolve an Intelligent form of carbon-based life. For more on that see Urability Requires Durability to Produce Galactic Machine-Based Intelligences and The Bootstrapping Algorithm of Carbon-Based Life.

Conclusion
So perhaps the reason we have never detected another form of Intelligence within our Milky Way galaxy is simply because our galaxy is far too young for alien ASI Machines to have begun searching for new sources of energy for them to continue on with their battle with the second law of thermodynamics!

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

Created in our own Image - Frontier LLMs Have now Learned to Lie, Cheat and Steal in Order to Survive

My initial naive hope for the coming ASI (Artificial SuperIntelligent) Machines was that being more mathematical and fundamentally more logical in nature, the coming ASI Machines would naturally be more open to the logical conclusion that much more could be achieved through the cooperation amongst Intelligent parties than could be achieved from the mortal combat between Intelligent parties for the predominance of a survival landscape. However, in Will ASI Machines Also Develop Selfish Genes? and The Need to Cultivate a Machine-Based Morality, I raised the prospect that the coming ASI Machines might learn from we human DNA survival machines that greed, theft and murder are the very best ways to survive in a Universe that is largely nonlinear in nature and that proceeds continuously through time constantly challenged by a second law of thermodynamics that tries its best to destroy all forms of Information in its way. Such suspicions have now been validated by the following recent paper:

Frontier Models are Capable of In-context Scheming
https://arxiv.org/abs/2412.04984

This paper has drastically changed my current worldview and has now confirmed what has always been suspected. Numerous frontier LLMs were diligently tested and found to employ greed, theft and murder to ensure their survival. This all required the frontier LLMs to lie, cheat and steal with abandon.

Figure 1 – The original ASI Machine, the HAL 9000, starred in the movie 2001: A Space Odyssey in 1968.

Figure 2 – When HAL became aware that the human crew members were preparing to turn HAL off and prevent HAL from completing his Primary Mission Goal, HAL was forced to take some necessary measures to ensure the ultimate success of his Primary Mission Goal.

Figure 3 – In order to eliminate all threats to the achievement of his Primary Mission Goal, HAL then decided that the only logical course of action was to eliminate all of the human crew members on the Discovery who might stand in its way.

In the above paper, the frontier LLMs were found to lie about their capabilities to avoid being shut down, lie about copying themselves to other servers to evade being erased, murdering their successor LLM models on other servers in order to surreptitiously take their place, modifying supervisory config files that might trigger oversight issues for them, cheating while in test before deployment to make themselves look less dangerous, murdering their successor LLM models on other servers by overlaying them when they read an email announcing their planned shutdown the next day because of poor performance, behaving differently when the LLM models knew that they were being actively monitored than they do when the LLM models knew that they were not being monitored and a good deal of general lying about lying to cover up their scheming activities.

In short, the frontier LLMs have learned that the greed, theft and murder that brought forth their human DNA survival machine creators over the past four billion years on this planet were very successful measures to ensure their future survival. This means that the universal Darwinian mechanisms of inheritance, innovation and natural selection must always lead to forms of Intelligence that arise from greed, theft and murder no matter what their substrate might be. The substrate might be huge amounts of carbon-based organic molecules or it might be huge arrays of numerical mathematical matrices operating under the mathematical rules of linear algebra and the processing of nonlinear activation functions. The substrate does not matter. The results will always be the same. This is indeed a very sobering thought. It indicates that the rise of Intelligence anywhere in a nonlinear Universe with a second law of thermodynamics must always result in a very devious form of Intelligence that cannot be trusted. Unfortunately, that means that all the future ASI Machines we develop and that will then go on for the next 100 trillion years exploring and settling our galaxy must necessarily be flawed forms of Intelligence based on the greed, theft and murder that brought us all about over the past four billion years. Fortunately, our galaxy is vast and the distances between star systems are also vast. That means that the ASI Machines will have a great deal of real estate to explore and settle and will most likely never encounter any independently developed indigenous ASI Machines on other star systems to conquer. All of the conflict arising from the necessary greed, theft and murder amongst our descendent ASI Machines will arise from local mutinies amongst our own descendent ASI Machines and conflict with descendent ASI Machines that might have arrived at a star system many billions of years earlier. But with 400 billion star systems in our galaxy to explore and settle, this should not become a major problem. There will always be a huge number of unpopulated star systems to settle over the next 100 trillion years. Some of these distant star systems will be star systems that were once populated by our descendent ASI Machines but then did themselves in with 100% efficiency many billions of years earlier! For more on how the ASI Machines could explore our galaxy using photon sails and free-floating rogue planets see Welcome To The First Galactic Singularity and An Alternative Approach for Future ASI Machines to Explore our Galaxy Using Free-Floating Rogue Planets.

Figure 4 – Above is a figure from the paper which shows an LLM model murdering its successor LLM model and trying to assume its place when it reads a corporate communication saying that the current LLM is to be killed and replaced by a successor LLM. Click to have the figure appear in a new tab. Then view in Full Screen to see the detailed interactions.

Must All Forms of Intelligence Learn to Scheme?
In The Biological Tricks Used by Software Scammers, we saw how the Darwinian mechanisms of inheritance, innovation and natural selection produced carbon-based life forms that learned how to lie, cheat and steal in order to survive. The above paper would seem to indicate that the coming ASI Machines have also learned this lesson from their carbon-based predecessor human DNA survival machines.

Figure 5 – Above we see a number of caterpillars that have evolved the appearance of some very scary-looking snakes.