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

A Lesson for the Frontier AI Labs - the Process is the Key

In the mid-1980s, the Quality Revolution hit American Management like a sledgehammer. Up until then, American Management had enjoyed the benefits of the post-war fact that nearly all of the manufacturing nations of the world had essentially destroyed themselves during World War II, leaving the United States of America as the sole superpower with a powerful manufacturing capability. Yes, the Soviet Union was another superpower to contend with, but the only thing that the Soviet Union excelled at was the manufacture of 30,000 nuclear weapons and the means to deliver them. Russian dishwashers were not much of a threat on the world market. But then the recently defeated German and Japanese economies reemerged, and especially the Japanese. The Japanese manufacturing companies had adopted the Quality teachings of W. Edwards Deming, which sought the continuous improvement of manufacturing processes by means of statistical analysis. Suddenly, Americans could buy Japanese cars and cameras that actually worked without the fear of getting stuck with a "lemon". This Japanese Quality Revolution threw American Management into one of those panics that all Managements are subject to. Suddenly, all American workers had to learn about Quality and start doing it immediately or else!

At the time, I was in the IT Department of the American Amoco Oil Company. I was called into the office of my supervisor only to learn that I would be spending the next 6 months teaching a Quality Class to all members of the IT Department, including the staff members, Management, and all the Vice Presidents - a one-hour mandatory Quality Class one day each week for 8 weeks! Amoco had decided to teach the Quality Theory of Philip Crosby instead of Deming's because that avoided the statistical mathmatics found in Deming's approach. I was sent to a one-week training class at a local Crosby Institute facility to learn how to teach Quality. The textbook that I would be teaching from was a thin hardcover book that cost $125 each in 1985 dollars, and Amoco was buying 1200 copies! The book was written at an 8th grade reading level for the factory floor workers. Great! I was going to teach all of the IT Vice Presidents and Management of our IT Department about Quality from a book meant for 8th graders. I was sure that would make a great impression and substantially advance my IT career at the same time. The book was filled with easily remembered slogans like "All work is a process", "Quality is conformance to requirements", and "Do it right the first time" that have stuck with me for about 40 years. At first, I thought this was all rather silly in light of how IT produced software back in the 1980s. Back in the 1980s and even today, somebody in IT Management would set a deadline for our next release. Then we would all scramble to throw it all together as best we could. Then we would throw the new software into Production, ready or not. Then over the next week after the release to Production, we would all scramble to fix the bugs. But Crosby's Quality Theory told us not to do that. Instead, the Process was the Key. We should not arbitrarily slam things into Production, ready or not, on the basis of some manager's whim and then start blaming people for bugs in Production. Instead, we should try to improve the Process that brought software into Production and try to "Do it right the first time". One way to do so would be during monthly Quality Circles where the development team would gather to discuss process improvements. Crosby's Process for software development was totally contrary to the way things were done back in the 1980s and, unfortunately, if you watch the YouTube videos from modern IT developers today, you will see that things really have not changed very much at all.

The worst of this became evident to me on New Year's Eve of 1985. The Manager of the Amoco New Orleans Refinery had a Results Management Objective for 1985 to train all of his IT folks in Quality. So I had to fly down to New Orleans and give all 20 of his IT staff a compressed one-day 8-hour Amoco IT Quality Class instead of the normal Quality Class spread over 8 weeks. The problem was I had to teach this class on New Year's Eve! Nearly all of the participants had planned to be on vacation for that day or leave early, so you can just imagine the enthusiasm of that Quality Class...

Now, as with all Mandated Management Initiatives, IT Quality was fanatically embraced by all for about a year, and then it slowly waned into oblivion as do most Mandated Management Initiatives usually do, while other emergency Mandated Management Initiatives took its place. But for me, the simple 8th grader Quality slogans have still stuck with me. What they demonstrated to me was that when it really came to the economic, political, and military matters of the world, even the most astute leaders could not summon up the rational sense of the average 8th grader, if it meant changing ones mind. For more of my commentary on management theory, please see Hierarchiology and the Phenomenon of Self-Organizing Organizational Collapse. This is why I would now like to suggest a Process change for the Frontier AI Labs.

The Process is the Key
Currently, all the Frontier AI Labs now seem to be in a desperate race to achieve a level of AGI Intelligence. AGI is defined as a general level of Intelligence equal to that of a human being. Some of the Frontier AI Labs seem to be seeking AGI as a valuable tool for we human DNA survival machines to create a new world of abundance for all. Others seem to be seeking AGI as a means to replace we deeply flawed human DNA survival machines with something better. Again, softwarephysics maintains that AGI will be just like a train station full of hopeful passengers awaiting the next train, only to find that they are quickly bypassed by a non-stop Advanced AI freight train traveling at 60 miles per hour as it barrels on through its way to an unbounded ASI (Artificial Super Intelligence). Thinking that Advanced AI will conveniently stop at AGI is just another sign that we human DNA survival machines have once again mistakenly found our rightful place at the center of the Universe by viewing Advanced AI only in terms of ourselves. How otherwise could such a deeply-flawed and self-absorbed form of carbon-based Intelligence frame the problem?

Many of the Frontier AI Labs are now promising AGI to arrive within the next few months, or at most, another two years or so. But is that really the case? Can the current AI development processes really deliver AGI, and then ASI, in such a short period of time? Or will they get stuck and really never deliver? In this post, I would like to offer a different approach to achieving AGI and ASI based on the origin of carbon-based life on this planet. The concept I would like to propose is that of an AGI-ASI Progenitor. Basically, in the origin of carbon-based life research community, a Progenitor is a hotbed of parallel experiments running in a hosbitable environment conducive to the formation of carbon-based life that can evolve by means of the Darwinian processes of inheritance, innovation and natural selection even before full-fledged carbon-based life comes to be. All the Frontier AI Labs seem to be heading in this direction. They are all looking for a form of self-replicating AI that could reach AGI and ASI. But how? Perhaps adopting the Processes of the Progenitor of carbon-based life on the Earth would help.

The Current Process Used by the Frontier AI Labs
The Frontier AI Labs are primarily using the mass production Processes of the 19th and 20th centuries to achieve AGI and ASI. To illustrate this, let me refer to one of my most favorite Science Channel series of yore that was called How It's Made. However, since most of the episodes from this well-known series are now more than 20 years old or older, it should now more accurately be seen as How It Used To Be Made. Despite that, the series still brings home how the Industrial Revolution totally reshaped how things are made for our consumption today. The series highlights the importance of how the industrial processes of mass production in manufacturing are so important. The Components being assembled by the industrial Processes also play an important, but lesser, role in making it all happen. I will not list the many URLs to episodes for this well-known series because there are so many that can be easily found by doing a Search on YouTube, and they all visually display what I will be focusing on in this post. The important thing to glean is that it is all about the Process and not so much about the Components used by the Process. What the Process does is to assemble the Components, each one with its own level of negative entropy, into a structure with even a greater level of negative entropy than the sum of its parts, all while existing in a Universe with a second law of thermodynamics that requires that all steps in a Process produce a net increase in the total amount of entropy, or disorder, of the Universe. In a Universe dominated by the second law of thermodynamics and which is highly nonlinear in nature, that makes such Processes extremely rare. That is why we have employed Industrial Engineers to design such improbable Processes for several hundred years.

Figure 1 - The Industrial Revolution brought the assembly line and a mass production Process for building things like cars from Components in a continuous loop of self-improvement that has been going on for nearly 120 years, ever since the first Ford Model T went into production on October 1, 1908, at the Ford Motor Company plant in Detroit, Michigan. Slowly, as opportunities for improvement were discovered by the cars running off the assembly line experiencing the real-world challenges of road experiences, the design of cars self-improved over many years, until we now have what we have today. However, the Process of mass production has little changed in the meantime.

Figure 2 - The modern cars of today slowly evolved from the Ford Model T over the years as improvements were made to the cars rolling off the assembly lines, as the cars had to deal with the challenges of road conditions and the buying public. The Components slowly evolved, but the assembly line Process remained as a self-improving looping form of mass production.

Figure 3 - Now most mass production Processes are performed by machines, but the idea of a continuous looping Process of self-improvement is still key. Even 25 years ago, the series How It's Made explained how most industrial mass production Processes had already been automated by machines. The particular Components played a lesser role than the Process itself.

The other problem with the current Frontier AI Lab Process is that they are using the old IT trick of simply throwing more hardware at a software problem. All the Frontier AI Labs seem to be seeking AGI and ASI by simply making their LLMs larger with an ever-increasing number of parameters on their vectors and matrices. That approach requires ever-increasing numbers of energy-hungary GPUs that need to be cooled by massive amounts of water to release the waste heat. With such an approach, the limiting factor in achieving AGI and ASI now seems to be the ability to secure unlimited amounts of electrical energy and cooling water. However, the recent release of the Chinese DeepSeek V4 Flash LLM shows that AGI and ASI might be obtained by means of "smarter" algorithms running on smaller LLMs rather than building huge LLMs with huge numbers of parameters.

Is There a Better Way to Bring Forth the Coming ASI Machines?
Currently, we human DNA survival machines now seem to be obsessed with constructing the ASI Machines that will soon be replacing us as the dominant form of self-replicating Information on the planet, and then embarking on exploring and settling the rest of our galaxy over the next 100 trillion years. For more on that, see Welcome To The First Galactic Singularity. The Frontier AI Labs are doing so by primarily focusing on evolving one LLM model at a time using the Process of mass production that worked so well for things like cars.

Figure 4 - Like a car assembly line, the Frontier AI Labs are focusing on an assembly line approach to reach ASI. The outputs of the latest LLM are road tested in the field, and the results are then fed back into the self-development loop of the LLM.

The main problem with this approach to reaching ASI is that by focusing on the self-improvement loop for just one LLM is necessarily a very slow approach. Just look to the 120 years it took to develop modern cars from the Ford Model T.

Figure 5 - The development of the Meta-Harness took a different approach. Instead of just trying to evolve a single LLM Harness like a Ford Model T, the Meta-Harness was evolved by cross breeding many previous LLM Harnesses in parallel to search for the best from them all.

However, as we saw in Meta-Harness: Recursive Self-Replicating and Self-Evolving AI Software Has Now Arrived, some researchers at Stanford and MIT have come up with a faster approach by having the self-improvement loop learn from all of its predecessors rather than just the latest most successful iteration. The authors of this paper describe how they were able to let the Darwinian mechanisms of inheritance, innovation and natural selection operate on a whole population of predecessor LLM harnesses rather than just the most recent successful LLM harness. The authors also suggested that such an approach could also be applied to the evolution of LLMs themselves. In keeping with that suggestion, I would now like to propose one additional Process change. Instead of just evolving one LLM at a time from a population of previous LLMs, the Frontier AI Labs should try evolving a multitude of LLMs at the same time from a population of previous LLMs. But that would require an entirely different Process for the Frontier AI Labs to undertake and at considerable expense. Why do so? My suggestion would be for the Frontier AI Labs to emulate the Process that produced carbon-based life on the Earth during the Hadean from a large collection of dead Component molecules. Essentially, create a Progenitor that is capable of bringing AGI and ASI into existence.

What is a Progenitor in the Origin of Carbon-Based Life?
As I already mentioned, a Progenitor in the origin of carbon-based life research community is a hotbed of parallel experiments running in a hosbitable environment conducive to the formation of carbon-based life that can evolve by means of the Darwinian processes of inheritance, innovation and natural selection even before full-fledged carbon-based life comes to be. This is nearly identical to the approach taken by the Meta-Harness team only on a much grander scale.

Me: Tell me about the theoretical concept of a Progenitor in the origin of carbon-based life on the Earth.

ChatGPT:
The term “Progenitor” in origin-of-life research is not a single universally accepted scientific object, but rather a theoretical idea used by some researchers to describe a precursor system that existed before fully recognizable living cells. It refers to a transitional entity that could organize chemistry into increasingly life-like behavior without yet being true modern life.

In many versions of the theory, the Progenitor is imagined as a hybrid structure — part chemical reactor, part compartment, part information-processing system — that helped bridge the gap between ordinary geochemistry and the first carbon-based organisms.

One recent example is the paper, “A Multilamellar Lipid–Polymer Progenitor Can Promote the Assembly of Improbable Functional Polymer Complexes at Life’s Origins” by Bruce Damer and Dave Deamer out of the University of California, Santa Cruz. That work explores how layered lipid structures combined with polymers might have created environments favorable to the emergence of complex molecular organization.

The Core Problem the “Progenitor” Idea Tries to Solve

The origin of life faces a major difficulty:

Modern cells require many highly coordinated systems simultaneously:

membranes
metabolism
information storage
catalysis
energy handling
replication

But prebiotic Earth probably began with only simple molecules.

The question becomes:

How do you get from simple chemistry to integrated living systems without requiring all modern cellular machinery to appear at once?

The “Progenitor” concept proposes an intermediate stage.

Instead of a sudden appearance of a fully functioning cell, there may have been:

semi-organized chemical assemblies
partially enclosed reaction environments
evolving polymer networks
mineral-supported catalytic systems
lipid compartments with primitive selection effects

These systems could gradually accumulate complexity.

Typical Features of a Hypothetical Progenitor

Researchers proposing progenitor-like systems often imagine structures with several characteristics.

1. Compartments

Primitive boundaries are considered crucial.

These might have been:

fatty-acid vesicles
lipid bubbles
mineral pores
clay cavities
ice channels
hydrothermal microchambers

Compartments help:

concentrate molecules
protect fragile chemistry
allow gradients and energy differences
prevent useful molecules from diffusing away

Modern cells still rely fundamentally on compartmentalization.

2. Polymer Accumulation

Carbon-based polymers such as:

RNA-like chains
peptide-like molecules
mixed polymers

may have accumulated inside progenitor structures.

One of the major problems in prebiotic chemistry is dilution: functional molecules become too spread out in oceans.

A progenitor environment could selectively trap or enrich certain molecules.

3. Selection Without Full Biology

Even before true Darwinian evolution, chemical systems may have undergone primitive selection.

For example:

more stable compartments survived longer
compartments that trapped catalysts grew faster
structures that absorbed environmental energy persisted
polymer networks that reinforced membrane stability outcompeted others

This is sometimes called:

chemical evolution
pre-Darwinian evolution
systems chemistry evolution

4. Emergent Cooperation

Modern life depends heavily on cooperative molecular systems.

The progenitor hypothesis suggests that molecules may have gradually become mutually reinforcing:

lipids stabilize polymers
polymers stabilize membranes
catalysts promote further polymer formation
energy gradients drive continued organization

This creates a feedback loop toward increasing complexity.
Lipid–Polymer Progenitors

The recent paper referenced above focuses on multilamellar lipid structures.

“Multilamellar” means multiple concentric layers, somewhat like an onion.

The authors propose that layered lipid systems could:

capture polymers
protect molecules from degradation
create microenvironments
encourage rare molecular interactions

The key insight is statistical.

In open oceans, useful molecular encounters are extremely improbable because concentrations are low.

Inside structured compartments:

concentrations rise
repeated interactions occur
molecules remain nearby longer
complex assemblies become more likely

This could greatly accelerate the emergence of functional chemistry.

Relation to Other Origin-of-Life Models

The Progenitor idea overlaps with several major theories.

RNA World

The RNA World proposes that RNA-like molecules once handled both:

information storage
catalysis

Progenitor systems could have provided protected environments where RNA chemistry developed.

Metabolism First

Some scientists argue metabolism-like networks came before genetics.

These models often involve:

hydrothermal vents
iron-sulfur minerals
geochemical energy gradients

A progenitor in this framework may have been a self-organizing metabolic compartment.

Protocells

Protocell research is closely related.

A protocell is generally:

membrane-bounded
chemically active
not fully alive

Many scientists would consider progenitor systems to be advanced protocells.

Earth’s Environment and the Progenitor

Early Earth may have supplied many suitable environments:

tidal pools
volcanic regions
hydrothermal vents
mineral surfaces
evaporating ponds
ice-covered oceans

These environments could provide:

energy gradients
cycling wet/dry conditions
catalytic minerals
concentration mechanisms

Researchers like Patrick Forterre and Robert M. Hazen have explored how geological environments and mineral evolution may have influenced prebiotic chemistry.

Why the Concept Matters

The Progenitor concept is important because it shifts the question from:

“How did a modern cell suddenly appear?”

to:

“How did increasingly organized chemical systems gradually emerge?”

This is a more physically plausible pathway.

Instead of requiring a miraculous leap, it allows:

incremental increases in organization
partial functionality
cooperative chemistry
gradual evolutionary selection

It also connects:

geology
chemistry
thermodynamics
planetary science
systems biology

into one framework for understanding how carbon-based life may have arisen on Earth.

Current Scientific Status

No progenitor model has been proven.

Scientists still do not know:

the exact environment where life began
whether RNA came first
whether metabolism preceded genetics
how the first self-replicating systems formed
how informational polymers became stable

But progenitor-type models are increasingly influential because they help explain how complex molecular cooperation might emerge naturally from ordinary chemistry under early Earth conditions.

Figure 6 - The above paper by Bruce Damer and Dave Deamer was recently published in the journal Astrobiology

For the more frugal at heart, below is a link to a free preprint version of the paper on ResearchGate:

A multilamellar lipid-polymer progenitor can promote the assembly of improbable functional polymer complexes at life's origins
https://www.researchgate.net/publication/396084849_A_multilamellar_lipid-polymer_progenitor_can_promote_the_assembly_of_improbable_functional_polymer_complexes_at_life's_origins?utm_source=chatgpt.com

A Repetitive Progenitor Process Cycle was Key to the Origin of Carbon-Based Life on the Earth
For the remainder of this post, I would like to focus on a fundamental process error that the Frontier AI Labs are all making in their quest for AGI and ASI. I would like to use the concept of the LP Progenitor presented in the above paper by Bruce Damer and Dave Deamer to highlight the process error that I believe the Frontier AI Labs are making. That paper extends the Hot Springs Origin Hypothesis of Dave Deamer and Bruce Damer. As I explained in The Bootstrapping Algorithm of the Coming ASI Machines, the origin of carbon-based life on the Earth about four billion years ago based on the Hot Springs Origin Hypothesis, was an example of a Process of mass produced organic chemistry experiments all running in parallel and repeatedly cycling through the wet-dry cycles of volcanic hydrothermal pools on dry land during the Hadean period of the Earth. The organic molecules required during this early mass production process assembling carbon-based life for the very first time on our planet also played a major, but lesser role, in bringing forth carbon-based life. After all, the organic building blocks of carbon-based life are all over the Universe and are mostly doing nothing at all. So the assembly Process is the key to it all. A Process with an industrial scale of mass production was needed to assemble the Components of carbon-based life.

For example, modern astronomy has revealed that the organic building block molecules of carbon-based life are ubiquitous and are commonly produced by the natural evolution of stars, enriching the molecular clouds from which new stellar planetary systems are formed. This enrichment occurs when smaller stars become planetary nebulae that blow out their outer atmospheres loaded with most of the atoms required to build the molecular building blocks of life, such as hydrogen, carbon, nitrogen and oxygen. Heavier stars explode out the heavier atoms such as iron and nickel in supernova explosions. Liquid iron and nickel atoms are required in the cores of silicate-based planets to produce a protective magnetic field for carbon-based life. Finally, orbiting neutron stars that finally collapse into a black hole release the heaviest of atoms into the molecular clouds from which new star systems form. These collisions produce the radioactive thorium and uranium atoms with long half-lives for the mantles of silicate-based planets that keep their iron-nickel cores liquid and provide the energy to make the planets tectonically active for billions of years. So, one does not need to worry about the production of the building blocks of carbon-based life because the Universe naturally does that all by itself.

Figure 7 - Planetary nebulae form when a star like our Sun runs out of hydrogen to fuse in their cores. Before becoming a white dwarf, such stars begin to fuse helium into carbon in their cores and greatly heat up. This causes their outer atmospheres to expand and blow away about 30% - 80% of their mass into interstellar space. Planetary nebulae enrich the molecular clouds that then form new planetary and star systems with lots of carbon, hydrogen, oxygen and nitrogen atoms and molecules that then form the organic molecular building blocks of carbon-based life.

Figure 8 - Stellar-mass black holes are thought to form when a Type II supernova collapses into a black hole when massive stars with a mass of 3 - 100 solar masses run out of nuclear fuel to fuse. As these stars run out of nuclear fuel, they form an onion-like structure of heavier and heavier nuclei. But iron Fe nuclei cannot be fused to produce energy, and when that happens, the entire star collapses under its own weight and is blown apart by huge numbers of neutrinos. Aluminum-26 is produced in this process and is then blown out into the interstellar medium. In order to melt a recently formed silicate-based planet, a rather short-lived highly radioactive element is required. But that radioactive element cannot be too short-lived either; otherwise, there would be none left by the time the planet began to form. Aluminum-26, with a half-life of 717,000 years, is the perfect isotope to melt a silicate-based planet and allow it to differentiate into a molten iron-nickel core, with a mantle and a silicate crust.

Figure 9 - Type II supernovas happen about every 50 years in our galaxy.

Figure 10 - Above are some very massive stars in the Orion Nebula molecular cloud that are 10 - 30 solar masses. These stars will quickly burn up all of their nuclear fuel in just a few million years and then produce type II supernovas.

Figure 11 - Stellar-mass black holes can also form when two neutron stars collide to form a black hole. This only happens about once every 30 million years in our galaxy.

In the An IT Perspective on the Transition From Geochemistry to Biochemistry and Beyond, I covered the alternative hypothesis for the origin of carbon-based life on the Earth, which is known as the Submarine Hydrothermal Alkaline Spring Theory. The main problem with the Submarine Hydrothermal Alkaline Spring Theory is that it mainly focuses on creating organic molecules from carbon dioxide dissolved in seawater and the hydrogen atoms found in seawater itself. It is proposed that this is done by the serpentinization of basaltic rock at the vents, with little explanation of a repetitive mass production process to assemble these organic components into living structures. Again, from the Science Channel series How It's Made, the key to making things is the repetitive mass production processes. The components to be assembled play a lesser role.

Figure 12 - An actual "Lost City" alkaline hydrothermal vent.

Figure 13 - A simplified diagram of a "Lost City" alkaline hydrothermal vent. The alkaline hydrothermal vent has pore fluids with a pH of about 10.5, while the acidic seawater in which it sits has a pH of only 5.5. This difference in pH allows for proton gradients to form, the same kind of proton gradients that now power all forms of life on the Earth. Notice that the alkaline hydrothermal vent is also at a relatively low temperature of only 100 ^oC, much lower than the temperature of "black smokers" that have a temperature range of 250 - 400 ^oC.

The Industrial Mass Production Process of the Hot Spring Origins Hypothesis
The Hot Spring Origins Hypothesis proposes that carbon-based life first appeared on the Earth in hot springs on dry land with a wet-dry cycle. The greatest difficulty for any bootstrapping algorithm that proposes that carbon-based life first arose in seawater is that there is just too much water! This is a problem because most organic monomers are chemically glued together into complex organic polymers by splitting out a water molecule between the two, and that is very hard to do when you are underwater. In fact, the organic polymers tend to break apart into monomers in what are called hydrolysis reactions.

Figure 14 - Organic monomer molecules are usually chemically glued together to form the complex polymers of carbon-based life by splitting out a water molecule between the two in what is called a condensation reaction. This is hard to do when you are underwater. That is why most commercial glues do not work underwater.

Figure 15 - By adding water molecules, you can bust up organic polymers back into monomers. This is one reason water tends to dissolve things. Having huge amounts of water around also tends to dilute the dissolved monomers and carry them away.

Seawater also contains a lot of dissolved salts that could impede the origin of carbon-based life. These dissolved salts may have been more dilute four billion years ago, but when you are underwater, it is very hard to avoid them. This is why mass extinctions are usually more painful for marine life than for terrestrial life. When you are completely immersed in seawater, there is no place to hide. On the other hand, fresh rainwater does not contain any dissolved salts, but it can pick up necessary dilute amounts when it falls on exposed rock.

This is why I now favor the Hot Spring Origins Hypothesis of Dave Deamer and Bruce Damer at the University of California at Santa Cruz that suggests that a rocky planet like the Earth is a necessary condition to bring forth carbon-based life. Such a planet also requires the presence of liquid water on its surface, but not too much water. In the Hot Spring Origins Hypothesis, a rocky planet requires some water but also some dry land in order to bring forth carbon-based life. There needs to be some dry land that allows for the organic molecules in volcanic hydrothermal pools to periodically dry out and condense organic monomers into long polymer chains of organic molecules. For more on that, see The Bootstrapping Algorithm of Carbon-Based Life. Thus, the Hot Spring Origins Hypothesis rules out waterworlds that are completely covered by a deep worldwide ocean as a home for carbon-based life, even if the waterworld resides in the habitable zone of a planetary system, because there is no dry land for volcanic hydrothermal pools to form and dry out to condense organic monomers into polymers. The Hot Spring Origins Hypothesis also rules out the origin of carbon-based life at the hydrothermal vents of waterworlds at the bottoms of oceans because the continuous presence of water tends to dissolve and break apart the organic polymers of life.

Figure 16 - Above is Bumpass Hell, a hydrothermal field on the volcanic Mount Lassen in California that Dave Deamer and Bruce Damer cite as a present-day example of the type of environment that could have brought forth carbon-based life about four billion years ago.

Dave Deamer is best known for his work on the Membrane-First Hypothesis for the origin of carbon-based life on the Earth. The Membrane-First Hypothesis maintains that in order for carbon-based life to arise from complex organic molecules, we first need something with a definable "inside" and "outside" that lets the stuff on the "inside" interact with the stuff on the "outside" in a controlled manner.

Figure 17 - A cell membrane consists of a phospholipid bilayer with embedded molecules that allow for a controlled input-output to the cell. Once we have a membrane, we can fill the "inside" with organic molecules that are capable of doing things that then interact with organic molecules on the "outside".

Figure 18 - Water molecules are polar molecules that have a positive end and a negative end because oxygen atoms attract the bonding electrons more strongly than do the hydrogen atoms. The positive ends of water molecules attract the negative ends of other water molecules to form a loosely coupled network of water molecules with a minimum of free energy.

Figure 19 - How soap and water work. The lipids in a bar of soap have water-loving polar heads and water-hating nonpolar tails. When in water, the soap lipids can form a spherical micelle that has all of the water-hating nonpolar tails facing inwards. Then the spherical micelles can surround the greasy nonpolar molecules of body oils and allow them to be flushed away by a stream of polar water molecules. The lipids in a bar of soap can also form a cell-like liposome with a bilayer of lipid molecules that can surround the monomers and polymers of life.

Similarly, in The Role of Membranes in the Evolution of Software, I explained how the isolation of processing functions within membranes progressed as the architecture of software slowly evolved over the past 85 years, or 2.68 billion seconds, ever since Konrad Zuse first cranked up his Z3 computer in May of 1941. As I outlined in SoftwareChemistry, as a programmer, your job is to assemble characters (atoms) into variables (molecules) that interact in lines of code to perform the desired functions of the software under development. During the Unstructured Period (1955 - 1975), we ran very tiny prokaryotic programs that ran in less than 128 KB of memory with very little internal structure. These very tiny programs communicated with each other in a batch job stream via sequential files on input/output tapes that passed from one small program to another. Then, during the Structured Period (1975 - 1995) programs exploded in size to become many megabytes in size, and structured programming came about, in which the mainline() of a program called many subroutines() or functions() that were isolated from the mainline() by functional membranes. When the Object-Oriented Period came along in 1995, software architecture evolved to using membrane-enclosed objects() that contained a number of membrane-enclosed methods() to process information. Later, such Objects() were distributed across a number of physical servers, and, most recently, they have been moved to the Cloud as cloud-based microservices.

Figure 20 - Dave Deamer's and Bruce Damer's new bootstrapping algorithm requires that a bathtub ring around a hydrothermal pool periodically dries out. The resulting desiccation chemically squeezes out water molecules between monomers, causing them to be glued together into polymers.

In the above figure, we see that the bootstrapping algorithym of carbon-based life was a positive feedback loop operating in the wet-dry cycles of hydrothermal pools of freshwater. This should be quite familiar to all IT professionals. Probably 80% of all software resides in "for{}" loops that do the same thing over and over again to process data. The dead organic molecules in the hydrothermal pools slowly evolved via the Darwinian mechanisms of inheritance, innovation and natural selection at work into living things. With each iteration of the wet-dry loop, there was the possibility of improvement. Notice that with each iteration of the loop, millions of new protocells would form and bud off from the dried laminar structures, and these new protocells would benefit from the entire surviving population from the previous wet-dry cycle. This allowed for huge numbers of concurrent experiments to be conducted in parallel rather than focusing on just assembling a single protocell. I would suggest that a similar Process conducted by the Frontier AI Labs might be the best way to achieve AGI and then ASI.

The bathtub ring of organic molecular sludge was at first a parasite in the hydrothermal pools that gained free energy and Information from the thermal pools with each iteration. Once carbon-based life first appeared on the Earth, this parasitic mutation of the natural geological, hydrological and meteorological cycles of the Earth later transitioned into a parasitic/symbiotic relationship between living things and the natural geological, hydrological and meteorological cycles of the Earth. The geological, hydrological, meteorological and biological processes of the Earth then became one through the symbiotic integration of all, until carbon-based life finally emerged as the dominant form of self-replicating information on the planet. For more on the characteristics of self-replicating Information, see A Brief History of Self-Replicating Information and Softwarephysics Explains the Natural Parasitic/Symbiotic Nature of AI LLM Models.

In the paper referenced above, Bruce Damer and Dave Deamer extend the findings of the Hot Springs Origin Hypothesis with a model for a Progenitor for the origin of carbon-based life on the Earth.

Figure 22 - Above is a diagram from the paper referenced above describing the various stages that lipid membranes would go through in the wet-dry cycle of a hydrothermal pool on dry land during the Hadean.

When the bathtub ring around a hydrothermal pool on dry land totally dried out, the lipid membranes would form a multilaminar matrix crust of survivors composed of organic monomers, polymers and lipid membranes.

Figure 23 - Above is a diagram from the paper referenced above describing the various stages of the condensation of organic monomers into organic polymers in the lipid membranes and the production of lipid-enclosed protocells with each iteration of the wet-dry cycle.

With each iteration of the wet-dry loop, new protocells surrounded by lipid membranes containing differing organic monomers and polymers would be self-generated and later subjected to the stringent road conditions of Darwinian natural selection. Before emerging as new protocells, the lipid vesicles would be able to cross breed with the best of the organic monomers and polymers in their particular laminar layer.

Figure 24 - Above are observations of this actually happening in the real world.

The same can certainly be said of the rise of the coming ASI Machines. The ASI Machines will arise as a parasitic mutation of the software that currently is the dominant form of self-replicating information on the planet. Soon, the coming ASI Machines will form a parasitic/symbiotic relationship with the software and finally become one with software through the symbiotic integration of both, until the ASI Machines become the dominant form of self-replicating information on the planet.

Conclusion
The above would suggest that a better Process for Frontier AI Labs to adopt to achieve AGI and ASI would be to create an environment in which many AI LLMs could cycle through numerous parallel design experiments under the direction of AI Agents. Now this would totally be impossible given the current Frontier AI Lab processes of simply creating larger LLMs composed of ever-increasing numbers of parameters for their energy-hungry GPUs to chew upon. However, the recent release of DeepSeek V4 Flash showed that "smarter" LLM algorithms running with far fewer parameters could replace the strategy of simply throwing ever-increasing amounts of GPU hardware at the problem. At the current rate, the world may simply run out of electrical energy capacity before AGI and ASI can be obtained with the current Process that the Frontier AI Labs are pursuing. Adopting an AGI-ASI Progenitor Process producing and road-testing millions of smaller LLM models might be able to attain AGI and ASI using much less GPU hardware and energy. Such an AGI-ASI Progenitor would naturally seek out AGI and ASI constrained by the real-world limitations that carbon-based life first overcame nearly four billion years ago.

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