For Robust and Innovative Evolution of DNA: Hierarchical Architecture like OS-and-Apps
I understand that the genes of living organisms evolve by changes in their DNA sequences due to mating and mutations, passing through the gate of natural selection.
Despite these random changes in their blueprints, I’ve always been intrigued by the high probability that they can continue their basic life-sustaining activities.
From the perspective of computer systems, before the possibility of a new function emerging, the chance that a program continues to operate its complex functions nearly the same as the original system despite random changes is astronomically low.
Despite life and computer systems being thought of as even more intricate and delicate, why can such stable random modifications occur? In pondering this, I came across a hypothesis. Parts essential to life are made less susceptible to changes, while non-essential parts can be modified flexibly. This is similar to the distinction between the OS and application parts of a computer.
In this article, we will explore this hypothesis.
However, as a premise, we will first organize the common properties of life and intelligence. This is because I am interested in the commonalities between life and intelligence, and I want to examine whether this OS and application model can be applied to the knowledge dealt with by intelligence.
Let’s explain step by step.
Common Points Between Life and Intelligence
I am considering the nature of life and intelligence. While there are other aspects, I am focusing on the following commonalities:
a) They are systems that develop over time.
In life, this is the ecosystem; in intelligence, it’s the body of knowledge.
b) The system consists of many units.
In life, these units are individual organisms; in intelligence, they are individual pieces of knowledge.
c) Each unit has a mechanism to clearly separate and distinguish itself from other units.
For living organisms, physically it’s the cell membrane for unicellular beings and skin or shells for multicellular organisms. Systemically, they have immunity. This ensures that they don’t mix with other organisms.
Each piece of knowledge, formally (linguistically), can be a simple word, proper noun, or formula for simpler concepts, and definitions for complex ones. This is similar to the physical boundaries in organisms. Systematically, rationality and sensibility work to prevent the blending of different knowledge concepts, similar to the function of an organism’s immunity.
d) Units behave dynamically.
Organisms obviously behave dynamically. Knowledge emerges and interacts within thought processes.
e) Units have static design information and a medium to hold this information.
For living beings, DNA is the medium that holds design information. For knowledge, language is the medium.
f) Using the design information stored in the medium, units are dynamically generated. These dynamically created units might copy the design information.
From DNA, organisms emerge; knowledge emerges from stored memories.
As a result of the activities of organisms, DNA is replicated. Within thoughts, stored knowledge becomes stronger or might be replicated in others.
g) Design information recorded in the medium is newly produced by errors or synthesis. It is also selectively retained through the elimination in relation to other design information, meaning the design information evolves.
DNA produces new DNA due to replication errors or synthesis and evolves through natural selection.
Knowledge is newly generated through replication errors, synthesis within thoughts, learning, or discoveries. It evolves through factual verification or logical inconsistencies.
Two Dimensions of Time and Space
Based on the commonalities between life and intelligence, I’ll provide a simplified model to further understand their nature.
Here, we’ll consider the two dimensions: time and space.
Time has the usual connotation. However, for simplicity, we’ll consider it as moving in discrete time intervals.
Space is slightly different from our 3D physical space; it’s to identify units.
Imagine a grid paper with squares. Time moves from top to bottom, one square at a time, and each vertical line represents one unit.
Here’s an example from time T1 to T3. It illustrates how a unit with design information “A” multiplies. In this case, “A” produces two copies every time unit and disappears after two time units:
T1: _,_,_,_,_,A,_,_,_,_,_,
T2: _,_,_,A,A,A,A,A,_,_,_,
T3: _,_,A,A,A,_,A,A,A,_,_,In this 2D model, you can see how the design information spreads over time and space.
Model of Evolution
When visualizing the evolution of design information in this 2D plane, one might think of introducing other units like B or C in place of A.
However, the way this is modeled can drastically change our understanding of design information.
In this model, the symbol “A” represents design information. But when you think about it, “A” isn’t that simple. In life, it needs to maintain its identity over time, incorporate energy or resources for growth, and has the ability to replicate itself. It’s a highly advanced and intricate design information.
If there’s a mutation during replication and crucial parts of it change, it’s immediately detrimental. It’s vital for the design information to have mechanisms that prevent core changes during copying. This is different from immunity; in the case of DNA, there are various levels of redundancy and error-correction mechanisms built-in.
The key point is that not all design information is protected from changes in this way.
That’s why it’s inappropriate to say that if “A” mutates, “B” or “C” are produced.
Imagine if “A” mutates, we get A1, A+B, A+C, etc. A1 is a variation of A. A+B and A+C have the same design information as A but with additional design information B or C.
In this scenario, if A+B doesn’t adapt and perishes while A1 and A+C survive through natural selection, next we might see variations like A2, A1+D, or A+C+E as new design information candidates.
In this case, you’ll need to prepare multiple sheets of the two-dimensional graph paper mentioned earlier. By designating them as graph paper for A, graph paper for B, graph paper for C, and so on, you can visualize the spread of design information in terms of individual components across time and space.
Architecture Model of Design Information
When considering the evolution of design information in this manner, we begin to see the architectural model of design information.
Design information is analogous to a program in a computer. And the basic functions of living organisms correspond to the Operating System (OS). If this OS component breaks down, the computer ceases to function. As such, the OS component rarely undergoes changes and is designed to resist easy modifications.
However, if the same rules apply to the entire software, it becomes difficult to innovate by adding new programs and expanding the system. Therefore, separate from the OS, application programs (commonly known as apps) are developed, with mechanisms in place to install them.
This distinction between the OS and applications is the structure upon which the architecture model of today’s general computers is based. This architecture has not been in existence since the dawn of computer history but was adopted through a process of evolution and continues to be employed even today.
Similarly, the DNA, which is the design information for life, has probably introduced an architectural model similar to the OS and applications during its evolutionary process, and this has been maintained.
Hierarchical Architecture
For computers, the distinction isn’t just between the OS and apps. Within the OS, various functions are added over time in line with evolution. Furthermore, to accommodate various devices, drivers tailored for those devices can be added, maintaining the core of the OS while allowing for functional additions and expandability.
On the app side, it’s not just about adding individual apps. Middleware, which can be used commonly across different applications, can also be introduced. Layers can be further added to these components.
Through this hierarchical structure of OS, middleware, and applications, while keeping essential parts stable and resistant to changes, there is room for frequent modifications and innovations where needed.
This hierarchical architecture is adopted by the DNA in living organisms, facilitating a robust and efficient evolution.
The hard-to-change parts, like the OS, can be fortified by redundant storage of the same design information on DNA or by including abundant information for error correction, enhancing robustness. On the other hand, sections that should be subject to frequent changes, like applications, probably require less redundancy and error correction data.
How DNA has been intricately woven to discern between the change-resistant OS part and the frequently changing application part is a question. While precise verification is needed, it might naturally balance out if mutations that fortify random design information protection points occur.
For instance, DNA that doesn’t protect the vital OS part essential for life maintenance would produce many organisms that don’t live long, slowing down evolution. Conversely, between DNA that overly protects even the application part and DNA that doesn’t, the former slows down evolution, getting left behind as it can’t keep up with the environmental changes or the evolution of surrounding species.
As a result, it seems plausible that natural selection can effectively achieve a nearly optimal hierarchical architectural model with strong protection for the OS part, balanced protection for the middleware, and high adaptability for the application part.
Even in computer systems, not all features of the OS or middleware are always used. In one system a particular function might be used, but in another system, it might not be used at all, and many such features exist.
I’ve heard that in DNA, there are many parts that are not used. If it’s the OS or middleware section, even the unused parts might continue to be preserved. Therefore, even if they aren’t used, there’s a high possibility they will remain.
Classification of Organisms as a Common Platform
When you view the DNA of living organisms through this lens of hierarchical architecture, it provides a fascinating perspective.
The application side of the hierarchy will differ among species. On the other hand, for the OS or middleware, they exist as shared design information across multiple species. Especially, many species might have common design information at the core of the OS.
This is similar to computer systems running on the same OS platform. Single-cell organisms and humans might be using the same core OS design information, or different versions of it. And vertebrates might have a common OS platform, with mammals having mammal-specific middleware on top of it.
I am primarily a system engineer, so I’m not very familiar with biological classification. However, viewing biological lineages through computer architecture terms and platform concepts makes things clearer to me.
Design Information in Intelligence
Similarly, in the design information of intelligence, which is knowledge, the same architecture might be applied.
Language grammar structures are based on a fundamental structure, with applied structures built on top of it. Concepts expressed in words also build applied concepts on top of basic ones. For instance, within the concept of “fruit,” there are apples, oranges, and bananas, and within the “apple” concept, categories like red apples and green apples are formed. Also, in fields like mathematics or physics, applied theories are developed based on fundamental theories.
When new facts or perspectives emerge, applied grammar structures, concepts, or theories may frequently be revised. However, it’s rare for the more fundamental grammar structures, concepts, or theories to collapse.
Thus, it’s likely that knowledge, the design information of intelligence, also follows an architecture similar to OS, middleware, and applications.
In Conclusion
In this article, we organized the commonalities between life and intelligence and focused on the concept of design information corresponding to DNA and knowledge. We then proposed representing the process of evolution of design information in a two-dimensional model of time and space.
Based on this, we hypothesized that the design information, DNA, has an architectural model with hierarchies like OS, middleware, and applications in computer systems.
This hypothesis can well explain why organisms born through mating and mutations can conduct basic life activities and why a vast amount of unused design information continues to remain in DNA. Additionally, it’s conceivable that this architecture itself can be realized as a result of random mutations in DNA and natural selection.
We also mentioned that this hierarchical architecture is observed in the knowledge in intelligence. Although we may need to delve deeper into the understanding of knowledge, I believe we have confirmed the utility of the perspective on the commonality between life and intelligence. I anticipate that by analyzing from this viewpoint, we can further deepen our understanding of both life and intelligence.
