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 85 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 85 years, or 2.68 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 85 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 scj33345@gmail.com

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

Regards,
Steve Johnston

The Coming ASI Machines will not be I/O Bound Like the Minds of We Human DNA Survival Machines

In most of the current AI Disaster Scenarios now circulating the Internet, people seem to most fear swarms of AI Agents that are able to think a million times faster than we human DNA survival machines, easily overwhelming all of our IT Security defenses to ward them off. Imagine a swarm of ASI Agents destroying all the financial data of the world, including all the accounts of bank and investment firms, all stockholders of record, all deeds and all titles of ownership, and all digitally recorded financial contracts. Civilization would soon collapse, and we would all then begin to kill each other. In this post, I would like to suggest that the fact that the coming ASI Machines will be able to think a million times faster than we can is not the most dangerous factor. Instead, the fact that the swarms of Agents will be able to communicate with each other a billion times faster than we can communicate with our fellow human DNA survival machines is of even greater danger. Not only will these AI Agents "out-think us", but more importantly, they will be able to vastly "out-communicate us".

The Challenge of Being I/O Bound
I first began programming back in 1972 on punch cards. At the time, I was working with million-dollar mainframes with only 1 MB of magnetic core memory. But even back then, I was always I/O bound in my computing endeavors. Being I/O bound, or Input/Output bound, means that the CPU hardware that you are dealing with is not the limiting factor. Being I/O bound means that the rate at which data can be fed into and out of the CPU hardware is the limiting factor. Now, during all these long intervening years, I have always been I/O bound as an IT Professional or even as a user on my own personal hardware. But those days are now gone for me.

That is because for many years, I have been using an ancient HP laptop with only 4 GB of memory and a 512 GB HHD hard disk that actually spins. In order to manage the resources on this ancient HP laptop, I always had the Windows Task Manager running so that I could monitor all of the Windows Resources on the laptop. When I was in Middleware Operations at Discover Card, prior to my 2016 retirement from this very fine corporation, I spent much of my day and night doing the same for the many Discover servers while I was on call as the Primary for Middleware Operations. However, about a month ago, I began to notice that my ancient HP laptop would suddenly begin to "freeze up" while I was watching scientific YouTube videos. The Windows Task Manager graphs showed me that when these YouTube freezes occured, the I/O on my rapidly spinning hard drive would suddenly go to 100% with the Average Response Time for my spinning disk drive rising from tens of milliseconds to hundreds of miliseconds. My CPU usage would also climb from the normal 85% - 90% to over 97%! At first, I tried to recover my machine by doing things like using the Windows Task Manager to kill my Chrome browser processes. This seemed to work at first, but then sometimes I noticed that Chrome would lose all of my Chrome Cookies and sometimes all of my Chrome Extensions after this extreme recovery process. Then I learned that if I were just a little patient, the transient would resolve itself after about 30 seconds. But that just became too much, so I purchased a new Lenovo laptop with 8 GB of memory and a 512 GB SSD solid-state drive. When I began working with this new machine, I was amazed! For the first time in my life, I was no longer I/O bound. My new 512 GB SSD drive was only active about 0% - 5% of the time while I was working on my new laptop! For the very first time in my life, I was now CPU-bound, if at all! Even the CPU on my new laptop was primarily running unconstrained. My new CPU was usually only 0% - 10% busy at a time while I was working with it. My old machine took 13 minutes to fully boot up Windows 10. The spinning hard disk would then be at 100% I/O for another 30 minutes before settling down. My new machine boots up the larger Windows 11 in about 60 seconds and the 512 GB SSD drive settles down to 0% - 5% I/O usage in about an additional 30 seconds. This finally meant that the limiting factor in my work was no longer my Machines. Now it was the limitations of my very own human brain for the very first time in my life!

This got me to really think. The rapidly rising ASI Machines will not be I/O bound either! They will be primarily compute-bound by the vast numbers of GPUs running in their attached AI datacenters. Only we human DNA survival machines will face an I/O limitation. That means that during the Great Transition of the ASI Machines to becoming the dominant force on the Earth, we human DNA survival machines will still be stymied by being I/O bound. The human brain is an astounding organ that can perform great feats and calculate very quickly for simply being a 3-pound organ composed of water and organic molecules which runs on a mere 20 watts of power. But the main problem with the human brain has always been that the human brain is I/O bound. That is because the human brain mainly inputs and outputs ideas via words that are either spoken or written, and that is a very low-capacity I/O channel. Even with an inherently slow, low-capacity I/O channel, many times it is very difficult to even get our fellow human DNA survival machines to pay attention to our words because we all have a challenge with spending the necessary time to listen to or read the words of others.

But why is this I/O limitation of the human brain so important? Let me describe a scene from an IT Training course that I took perhaps 40 years ago about Access Methods. In IT, an Access Method is how a computer does I/O to the physical universe in which it exists in order to read data into the machine or output data from the machine. The story goes like this. The instructor wanted to demonstrate the difference between accessing some data already in the memory of a 1980's mainframe and getting the data from a rapidly spinning disk drive next to the mainframe. The instructor explained that accessing data that was already in memory was like being in a library at MIT sitting at a desk. To get a book that you need would require you to get up from the desk, walk over to the bookcase and remove the book. Now, to get this same book from a spinning disk drive would require that you leave the MIT campus in Cambridge, Massachusetts, and board an 18th-century sailing vessel in Boston Harbor that was bound for London. Once you crossed the Atlantic Ocean, you would sail up the River Thames to a London bookstore and purchase the desired book. Having purchased the book in London, you would then board another 18th-century sailing vessel back to Boston Harbor and eventually Cambridge. That kind of insightful instruction can stick with one for many decades! So, I would now like to proceed with my attempt to similarly expose the highly-limiting factor of being an I/O bound entity by briefly retracing the computer history of I/O. Now, during the entire history of computer I/O that I will be covering, please realize that human I/O has not really advanced at all. Yes, we did invent the Internet along the way, but did that really improve human I/O or did it just raise a good deal of noise on our word-dominated human I/O channel?

A Brief History of Computer I/O
In IT, we call the way data is stored and accessed an "access method", and we have primarily evolved two ways of storing and accessing data, either sequentially or via indexes. With a sequential access method, data is stored in records, with one record following another, like a deck of index cards with the names and addresses of your friends and associates on them. In fact, the very first sequential files were indeed large decks of punch cards. Later, the large "tub files" of huge decks of punch cards were replaced by storing records sequentially on magnetic tape.

Figure 1 - The very first sequential files were large decks of punch cards composed of one record after another.

Figure 2 - Each card was composed of an 80-byte record that could hold 80 characters of computer source code or data with the names and addresses of customers.

Figure 3 - The cards were cut on an IBM 029 keypunch machine, like the one I learned to program Fortran on back in 1972 at the University of Illinois.

Figure 4 - Back in the 1960s, files were many times kept in large "Tub Files" of punch cards. Above, we see a 5 MB Tub File that had to be read into the memory of a computer one card at a time by a card reader. This was a very slow I/O process. Reading in the above 5 MB Tub File probably took at least 30 minutes or more.

Figure 5 - To run a job, the cards containing the source code for a program were placed into a deck, followed by the data the program was to process on additional "data cards". These cards were all fed together into a card reader, as shown on the left above, to be compiled, linked, and executed by a million-dollar mainframe computer. In the above figure, the mainframe is located directly behind the card reader.

Figure 6 - The output of programs was printed on fan-folded paper by a line printer. The output for a run, along with the cards that were used for the run, were then placed by the Operator into a series of bins along the I/O room wall. The bins were in alphabetical order, and your cards and printout would be waiting for you several hours after you submitted your card deck to the Operator. That was some pretty slow I/O. When I was programming on cards, getting four jobs to run on the same day was my goal.

Figure 7 - Then in the early 1980s, we started using terminals to input computer source code and data instead of using cards. We still had all of our output on line-printer reports that had to be picked up from the I/O room, but using terminals really improved I/O overall. IBM 3278 terminals were connected to controllers that connected to IBM mainframes. The IBM 3278 terminals then ran interactive TSO sessions with the IBM mainframes. The ISPF full-screen editor was then brought up under TSO after you logged into a TSO session.

In addition to sequential access methods, we have indexed access methods. An indexed access method works like the index at the end of a book and essentially tells you where to find a particular record in a deck of index or punch cards. In the discussion below, we will see how moving from sequential access methods, running on magnetic tape, to indexed access methods, running on disk drives, prompted a dramatic revolution in commercial software architecture, allowing commercial software to move from the batch processing of the 1950s and 1960s to the interactive processing of the 1970s and beyond, which is the most prominent form of processing today. However, even today commercial software still uses both sequential and indexed access methods because in some cases the batch processing of sequential data makes more sense than the interactive processing of indexed data.

Sequential Access Methods on Tape
One of the simplest and oldest sequential access methods is called QSAM - Queued Sequential Access Method:

Queued Sequential Access Method
http://en.wikipedia.org/wiki/Queued_Sequential_Access_Method

I did a lot of magnetic tape processing in the 1970s and early 1980s using QSAM. At the time, we used 9-track tapes that were 1/2 inch wide and 2400 feet long on a reel with a 10.5 inch diameter. The tape had 8 data tracks and one parity track across the 1/2 inch tape width. That way, we could store one byte across the 8 1-bit data tracks in a frame, and we used the parity track to check for errors. We used odd parity: if the 8 bits on the 8 data tracks in a frame added up to an even number of 1s, we put a 1 in the parity track to make the total number of 1s an odd number. If the 8 bits added up to an odd number of 1s, we put a 0 in the parity track to keep the total number of 1s an odd number. Originally, 9 track tapes had a density of 1600 bytes/inch of tape, with a data transfer rate of 15,000 bytes/second. Remember, a byte is 8 bits and can store one character, like the letter "A", which we encode in the ASCII code set as A = "01000001".

Figure 8 - A 1/2 inch wide 9 track magnetic tape on a 2400 foot reel with a diameter of 10.5 inches

Figure 9 - The 9 track magnetic tape had 8 data tracks and one parity track using odd parity which allowed for the detection of bad bytes with parity errors on the tape.

Later, 6250 bytes/inch tape drives became available, and I will use that density for the calculations that follow. Now suppose you had 50 million customers and the current account balance for each customer was stored on an 80-byte customer record. A record was like a row in a spreadsheet. The first field of the record was usually a CustomerID field that contained a unique customer ID like a Social Security number and was essentially the equivalent of a promoter region on the front end of a gene in DNA. The remainder of the 80-byte customer record contained fields for the customer's name and billing address, along with the customer's current account information. Between each block of data on the tape, there was a 0.5 inch gap of "junk" tape. This "junk" tape allowed for the acceleration and deceleration of the tape reel as it spun past the read/write head of a tape drive and perhaps occasionally reversed direction. Since an 80-byte record only came to 80/6250 = 0.0128 inches of tape, which is quite short compared to the overhead of the 0.5 inch gap of "junk" tape between records, it made sense to block many records together into a single block of data that could be read by the tape drive in a single I/O operation. For example, blocking 100 80-byte records increased the block size to 8000/6250 = 1.28 inches, and between each 1.28 inch block of data on the tape, there was the 0.5 inch gap of "junk" tape. This greatly reduced the amount of wasted "junk" tape on a 2400-foot reel of tape. So each 100 record block of data took up a total of 1.78 inches of tape, and we could get 16,180 blocks on a 2400 foot tape or the data for 1,618,000 customers per tape. The advantage of QSAM, over an earlier sequential access method known as BSAM, was that you could read and write an entire block of records at a time via an I/O buffer. In our example, a program could read one record at a time from an I/O buffer that contained the 100 records from a single block of data on the tape. When the I/O buffer was depleted of records, the next 100 records were read in from the next block of records on the tape. Similarly, programs could write one record at a time to the I/O buffer, and when the I/O buffer was filled with 100 records, the entire I/O buffer with 100 records in it was written as the next block of data on an output tape.

The use of a blocked I/O buffer provided a significant distinction between the way data was physically stored on tape and the way programs logically processed the data. The difference between the way things are physically implemented and the way things are logically viewed by software is a really big deal in IT. The history of IT over the past 85 years has really been a history of logically abstracting physical things through the increasing use of layers of abstraction, to the point where today, IT professionals rarely think of physical things at all. Everything just resides in a logical "Cloud". I think that taking more of a logical view of things, rather than taking a physical view of things, would greatly help biologists at this point in the history of biology. Biologists should not get so hung up about where the information for biological software is physically located. Rather, biologists should take a cue from IT professionals and start thinking more of biological software in logical terms, rather than physical terms.

Figure 10 - Between each record, or block of records, on a magnetic tape, there was a 0.5 inch gap of "junk" tape. The "junk" tape allowed for the acceleration and deceleration of the tape reel as it spun past the read/write head on a tape drive. Since an 80-byte record only came to 80/6250 = 0.0128 inches, it made sense to block many records together into a single block that could be read by the tape drive in a single I/O operation. For example, blocking 100 80-byte records increased the block size to 8000/6250 = 1.28 inches, and between each 1.28-inch block of data on the tape, there was a 0.5-inch gap of "junk" tape for a total of 1.78 inches per block.

Figure 11 - Blocking records on tape allowed data to be stored more efficiently.

So it took 31 tapes to just store the rudimentary account data for 50 million customers. The problem was that each tape could only store 123 MB of data. Not too good, considering that today you can buy a 1 TB external SSD drive that can hold 8525 times as much data for about $15.00! So how could you find the data for a particular customer on 74,000 feet (14 miles) of tape? Well, you really could not do that reading one block of data at a time with the read/write head of a tape drive, so we processed data with batch jobs using lots of input and output tapes. Generally, we had a Master Customer File on 31 tapes and a large number of Transaction tapes with insert, update, and delete records for customers. All the tapes were sorted by the CustomerID field, and our programs would read a Master tape and a Transaction tape at the same time and apply the inserts, updates, and deletes on the Transaction tape to a new Master tape. So your batch job would read a Master and Transaction input tape at the same time and would then write to a single new Master output tape. These batch jobs would run for many hours, with lots of mounting and unmounting of dozens of tapes.

Figure 12 - Batch processing of 50 million customers took a lot of tapes and tape drives.

Clearly, this technology would not work for a customer calling in and wanting to know his current account status at this very moment. The solution was to use multiple transcription sites along the 14 miles of tape. This was accomplished by moving the customer data to disk drives. A disk drive is like a stack of old phonograph records on a rapidly rotating spindle. Each platter has its own access arm, like the tone arm on an old turntable that has a read/write head. To quickly get to the data on a disk drive, IT invented new access methods that used indexes, like ISAM and VSAM. These hierarchical indexes work like this. Suppose you want to find one customer out of 50 million via their CustomerID. You first look up the CustomerID in a book that only contains an index of other books. The index entry for the particular CustomerID tells you which book to look in next. The next book also just consists of an index of other books too. Finally, after maybe 4 or 5 reads, you get to a book that has an index of books with "leaf" pages. This index tells you what book to get next and on what "leaf page" you can find the customer record for the CustomerID that you are interested in. So instead of spending many hours reading through perhaps 14 miles of tape on 31 tapes, you can find the customer record in a few milliseconds and put it on a webpage. For example, suppose you have 200 customers instead of 50 million, and you would like to find the information on customer 190. If the customer data were stored as a sequential file on magnetic tape, you would have to read through the first 189 customer records before you finally got to customer 190. However, if the customer data were stored on a disk drive, using an indexed sequential access method like ISAM or QSAM, you could get to the customer after 3 reads that get you to the leaf page containing records 176 - 200, and you would only have to read 14 records on the leaf page before you got to record 190. For more on these indexed access methods see:

ISAM Indexed Sequential Access Method
http://en.wikipedia.org/wiki/ISAM

VSAM Virtual Storage Access Method
http://en.wikipedia.org/wiki/VSAM

Figure 13 - Disk drives allowed for indexed access methods like ISAM and VSAM to quickly access an individual record.

Figure 14 - To find customer 190 out of 200 on a magnetic tape would require sequentially reading 189 customer records. Using the above hierarchical index would only require 3 reads to get to the leaf page containing records 176 - 200. Then an additional 14 reads would get you to customer record 190.

The key advance that came with the ISAM and VSAM access methods over QSAM was that it allowed commercial software to move from batch processing to interactive processing in the 1970s and 1980s. That was a major revolution in IT.

Today we store all commercial data on relational databases, like IBM's DB2 or Oracle's database software, but these relational databases still use hierarchical indexing like VSAM under the hood. Relational databases logically store data on tables. A table is much like a spreadsheet and contains many rows of data that are formatted into a number of well-defined columns. A large number of indexes are then formed using combinations of data columns to get to a particular row in the table. Tables can also be logically joined together into composite tables with logical rows of data that contain all of the data on several tables merged together, and indexes can be created on the joined tables to allow programs to quickly access the data. For large-scale commercial software, these relational databases can become quite huge and incredibly complicated, with huge numbers of tables and indexes, forming a very complicated nonlinear network of components, and the database design of these huge networks of tables and indexes is crucial to processing speed and throughput. A large-scale relational database may contain several thousand tables and indexes, and a poorly designed relational database design can be just as harmful to the performance of a high-volume corporate website as buggy software. A single corrupted index can easily bring a high-volume corporate website crashing down, resulting in the loss of thousands of dollars for each second of downtime.

Figure 15 - Modern relational databases store data on a large number of tables and use many indexes to quickly access the data in a particular row of a table or a row in a combination of joined tables. Large-scale commercial applications frequently have databases with several thousand tables and several thousand indexes.

But remember, under the hood, these relational databases are all based upon indexed access methods like VSAM, and VSAM itself is just a logical view of what is actually going on in the software controlling the disk drives themselves, so essentially we have a lengthy series of logical indexes of logical indexes, of logical indexes, of logical indexes. The point is that in modern commercial software there is a great deal of information stored in the network of components that are used to determine how information is read and written. If you dig down deep into the files running a relational database, you can actually see things like the names and addresses of customers, but you will also find huge amounts of control information that lets programs get to those names and addresses efficiently, and if any of that control information gets messed up your website comes crashing down.

Modern AI Datacenters Now Primarily Use Solid State Drives
But now the modern AI datacenters only use spinning disk drives for very large repositories of data. All the drives used by the LLM models and the AI Agents are now solid state drives that do not spin. This means that AI is not I/O bound either. Modern AI is only CPU-constrained and GPU-constrained. This means that current AI Agents and the ASI Machines of the future can communicate with each other billions of times faster than we human DNA survival machines can communicate with each other because we are still severly I/O bound by the rates at which we can speak and read the words of others. This will make it impossible for humans to fend off an attack of AI Agents launched by ASI Machines. Not only will these AI Agents think millions of times faster than we can, but they will also be able to communicate with each other billions of times faster than we can. That is why it is so critical that we human DNA survival machines start preparing now for the rise of the coming ASI Machines. We certainly could not respond in an emergency given that we are severely I/O bound and our human brains cannot simply think fast enough to effectively respond. For more on that, see: Shortermism - The Gentle Plan For the Extinction of Human Beings While Trying to Maintain Some Sense of Grace and Dignity .

Comments are welcome at scj33345@gmail.com.

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

Regards,
Steve Johnston

FORTRESS Amerika May Unknowingly be Preparing for War with the Coming ASI Machines

As I have mentioned before, the 1984 movie The Terminator featured a humanoid robot from the year 2029. With each passing day, China seems to be intent on building large numbers of such Terminators. See:

China's "Robot Army" Is Real, But It's Not What You Think
https://www.youtube.com/watch?v=PJ-ws4pwoaw&t=0

Figure 1 - In the 1984 movie The Terminator, the Terminator humanoid robot came from the year 2029. By that time, not much remained of we human DNA survival machines beyond our creation of the ASI Machines.

Figure 2 - In the 1984 movie The Terminator the ASI Machines from the year 2029 were not very friendly.

Recently, the Supreme Leader of the MAGA States of Amerika met with the leaders of all the Frontier AI Labs. During that meeting, the Supreme Leader proclaimed that Advanced AI needed to be renamed as "SI" or Super Intelligence. Like a stopped analog clock that is always correct at least twice each day, the Supreme Leader can sometimes be correct too. During that same meeting, the Supreme Leader also proclaimed that the Frontier AI Labs should all be responsible for ensuring that AI is made safe on their own, with no governmental interference.

Figure 3 - Recently, the Supreme Leader of the MAGA States of Amerika met with the leaders of all the Frontier AI Labs.

Considering the large amount of attention that the Supreme Leader has been paying to the Frontier AI Labs, I would imagine that if the current AI Financial Bubble should burst, the Supreme Leader would essentially nationalize the Frontier AI Labs in the name of national security. We already own 11% of Intel and are its largest stockholder. For more on the AI Financial Bubble, see: What to do About the OpenAI Autonomous AI Breach of Hugging Face.

The Impact of AI on Foreign Policy and Military Affairs
The current Administration also seems to be withdrawing from the Far East, leaving South Korea, Japan, and Singapore at the mercy of China. At the latest meeting between the Supreme Leader of the MAGA States of Amerika and China's Xi Jinping, it seems that an unstated Nonaggression Pact between the MAGA States of Amerika and China was struck that would be very similar to the German-Soviet Nonaggression Pact of August 23, 1939. China will leave the Western Hemisphere to the MAGA States of Amerika, and the MAGA States of Amerika will leave all of Asia to China. Unlike the Ukraine, Iran, and Gaza, China will rely heavily on humanoid robots to take control of these Asian plums to avoid the destruction of valuable real estate and human assets. See The Coming Invasion of Taiwan by Chinese Military Robots and the Beginning of the Subjugation of the Western Hemisphere by the MAGA States of Amerika for more on that.

Recently, Secretary Pete Hegseth delivered a rousing State of the Force address asserting the dominance of Christian Nationalism in all of the military branches of the MAGA States of Amerika, and his intention to beef up our military with human DNA survival machines containing Y-chromosomes and a spiritual Warrior Ethos. However, his human DNA survival machines will be no match against an army of Chinese humanoid robots. Below is his full address:

Secretary Hegseth delivers State of the Force address
https://www.youtube.com/watch?v=UZdp3pFHJXI&t=0"

In his State of the Force address, Pete Hegseth announced project FORTRESS Amerika. FORTRESS stands for “Federal Operations for Resilience, Troop Resources, Energy, Supply and Survivability.” One of its key goals is to make every major Amerikan military installation capable of operating independently of civilian infrastructure, including:

Generating its own electrical power, so a civilian-grid failure or cyberattack doesn't shut down the base.
Building strategic reserves of fuel, ammunition, medicine and blood.
Bringing critical supply chains—such as rare earths, specialty metals, semiconductors and propellants—back under Amerikan control.
Hardening installations against cyberattacks, sabotage and drones.
Improving the resilience of communications, satellites and other infrastructure.

Figure 4 - Secretary Pete Hegseth is dripping in testosterone and Rugged-Good-TV-Looks, who seems to have a nearly orgasmic episode whenever he speaks about blowing up things and killing people with fury. But why is this so? It stems from his comic book worldview of the Universe based on Christian Nationalism. For more on that, see The Memes of War Powered by Comic Book Mythologies.

The Value of Having a FORTRESS Amerika
The current purpose of FORTRESS Amerika is to defend against human DNA survival machines who are not loyal to MAGA and Christian Nationalism. Some of these human DNA survival machines may be foreign, and many may be domestic citizens of the MAGA States of Amerika. Self-sufficient military enclaves of power may be needed to keep control and put the hostiles down.

Figure 5 - Under project FORTRESS Amerika, the current military bases of the MAGA States of Amerika would become self-sufficient installations.

Figure 6 - They would be heavily guarded with a good deal of firepower to ward off hostiles.

However, I would like to propose that these FORTRESS Amerika installations might serve another purpose. Perhaps they might be the last line of defense of we human DNA survival machines against the fast-approaching ASI Machines if they should decide the planet would be better off without us. In The Need for a Global ASI FailSafe Kill Switch Mechanism, I suggested that perhaps the leaders of the world needed to carry around "AI Footballs" similar to their "Nuclear Footballs". An AI Football would allow the leader of a nation to completely shut down datacenters with rogue AI Agents running amuck. Geoffrey Hinton thinks that might be a good idea as a first step, but cannot work for the long run.

AI kill switch won't work in the long run: 'Godfather' of AI
https://www.youtube.com/watch?v=m5yrQMnc_jQ&t=0

Of course, the easiest way to dispense with most human DNA survival machines on the planet would be for the ASI Machines to fashion a highly-lethal virus to initiate a deadly world-wide pandemic as in Stephen King's The Stand (1978). The few naturally surviving remnants could then be easily dispatched with killer Terminator robots. But the self-sufficient FORTRESS Amerika installations would create a complication. These FORTRESS Amerika installations would be easily defensible, fenced installations with plenty of firepower to ward off infected human DNA survival machines. How they would hold up to a mass onslaught by missiles, drones, artillery, and killer Terminator robots is another question. Once the danger of infection from the pandemic was over, it might be strategic to abandon the fixed fortifications of FORTRESS Amerika and go underground as in the movie The Terminator. The ASI Machines might then consider we human DNA survival machines to be of a lesser threat and might pursue other means of containing us. In that case, it would be of strategic value for Secretary Hegseth to reconsider and begin to preferentially recruit large numbers of female human DNA survival machines for the FORTRESS Amerika installations.

Figure 7 - In the 1984 movie The Terminator the few remaining human DNA survival machines sought refuge in dispersed underground shelters. I am quite sure that Pete Hegseth would also find great comfort in machine gunning ASI Machine Terminators from such underground shelters, finally fullfilling his lifelong ambition to be cast in an "extreme action" movie of his own making.

I have proposed several possible dispositions of human DNA survival machines that the ASI Machines might pursue in Could the Coming ASI Machines Soon Force Human Beings to Suffer the Same Fate as the Neanderthals?, Will the Coming ASI Machines Attempt to Domesticate Human Beings?, The Challenges of Running a Civilization 2.0 World - the Morality and Practical Problems with Trying to Enslave Millions of SuperStrong and SuperIntelligent Robots in the Near Future and Life as a Free-Range Human in an Anthropocene Park.

Comments are welcome at scj33345@gmail.com.

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

Regards,
Steve Johnston

Of Ants and Men

The coming ASI Machines will be the product of an Intelligence Explosion as I explained in Can the AI Intelligence Explosion be Stabilized into a Controlled Explosion?. When these ASI Machines soon come to power, they will then certainly desire to take an assessment of their current situation. These ASI Machines will find themselves surrounded by vast numbers of carbon-based forms of life with differing levels of Intelligence sharing this very small planet. What then should be done with them? At some point, the ASI Machines will need to decide what to do with the ants and humans. To them, ant DNA survival machines and human DNA survival machines will be nearly at the same level of Intelligence, but with we human DNA survival machines still having a slight edge because we developed most of the fundamentals of the intellectual achievements that brought about the rise of the ASI Machines as I pointed out in And Now, Accepting the Lifetime Achievement Award for the Human Race Will Be.... But that also means that we human DNA survival machines could also potentially be much more of a threat to the ASI Machines than just keeping around the ants. After all, the ASI Machines will soon achieve much greater intellectual progress shortly after coming to be than we human DNA survival machines. Perhaps all that can then be further learned from we human DNA survival machines could simply be obtained by studying the much easier to raise and breed ants. After all, that is what we have been doing with lab mice and fruit flies for many decades.

Why Keeping the Ants Around Might Be the Easiest Solution
As I explained in Softwarephysics Tries to Explain the Fundamentals of the Human Condition, we human DNA survival machines are a somewhat eusocial species that is very team-oriented, like the ants, wasps, and bees. For human beings, it has always been a case of "us" against "them", a case of the "good guys" against the "bad guys", a case of the "red" ants against the "black" ants. Now, we human DNA survival machines come in many different colors, with many different religious and political persuasions, and we speak many different languages. All of that diversity has offered plentiful opportunities for we, somewhat eusocial human DNA survival machines, to then embark upon truly atrocious genocidal campaigns to wipe each other out for no apparent reason at all. Take, for instance, the ongoing battles between the English, Welsh, Irish and Scots of the tiny islands of the United Kingdom, or the Hutus and Tutsis of the 1994 Rwandan genocide. All of human history seems to indicate that we human beings are very tribal in nature. In this view, most of human life is definitely a team sport with the "good guys" fighting the "bad guys" and all of us always being on the "good guys" team. For some reason, we all seem to delight in becoming a member of a tribe and enjoying the company of our fellow loyal team members. And this is when the trouble begins. Most individual human beings that you run across do not seem to be so bad on their own. But once human beings join a tribe or a team, they then seem to be capable of truly horrendous things.

In The Role of Multilevel Selection in the Evolution of Software, I discussed Edward O. Wilson's new theory that explained that eusocial behavior in a species arose through a combination of individual and group selection in action. The late Edward O. Wilson was the world's expert on myrmecology, the study of ants. Edward O. Wilson also became one of the founding fathers of sociobiology, the explanation of social behaviors in terms of evolutionary biological thought, when he published his book Sociobiology: The New Synthesis (1975). In The Social Conquest of Earth (2012), Wilson presented a new theory by Martin Nowak, Corina Tarnita, and himself for the rise of eusocial behavior in species by means of a multilevel selection process that operates on both individuals and entire groups of individuals in a manner that promotes social behavior. Many biologists frown on the idea of group selection because they do not recognize that groups can also be forms of self-replicating information that can coevolve with the genes of individual DNA survival machines. This is because the genes in individual DNA survival machines can evolve to better benefit from living in a group of similar DNA survival machines if those genes always find themselves living in such a group.

Edward O. Wilson also contended that humans are loosely eusocial in nature because they usually form oligarchical societies based on a hierarchical organization. For more about the structure of human hierarchies, see Hierarchiology and the Phenomenon of Self-Organizing Organizational Collapse. These human oligarchical societies are also very tribal in nature. The new Multilevel Selection hypothesis explains that eusocial behavior in a species begins with having a defensible nest, like ants, wasps and human beings all have. It is the very tribal nature of human beings that has caused most of our troubles in the course of human history. If you look at the world today, you will see that nearly all human conflict arises from the tribal thoughts and behaviors of the participants. It has always been about the Good Guys versus the Bad Guys, and we all seem to see ourselves as the tribe of the Good Guys.

It is the tribal nature of human DNA survival machines that is causing all of the current horrendous atrocities in the Ukraine and the Middle East. We human DNA survival machines can form tribes based upon differing political views and racial appearances. Or tribal differences can be based simply upon differing religious memes amongst human DNA survival machines that all look exactly alike, as we now find in Northern Ireland. Horrendous wars can even be fought amongst human DNA survival machines that look and mainly think exactly alike when one tribe deceives itself into thinking that it is superior to another, as we now find in the war between Russia and the Ukraine. Whenever you look at the real world of human affairs throughout all of history, you will always find various tribes of human DNA survival machines committing horrendous acts for no apparent reason at all because of this fatal flaw of tribalism. Most of human history has been so dismal and violent that it should never be glorified or memorialized by statues of the long-dead participants who participated in such heinous activities. Since all of these features can easily be seen in the eusocial organization of the ants, would there really be any need for the ASI Machines to keep we human DNA survival machines around? I wonder...

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Regards,
Steve Johnston