A Hypothetical Model of the Origin of the Universe and Life

A Hypothetical Model of the Origin of the Universe and Life Based onDIKWP Semantic Structure: Semantic Cosmology

Yucong Duan

International Standardization Committee of Networked DIKWPfor Artificial Intelligence Evaluation(DIKWP-SC)

World Artificial Consciousness CIC(WAC)

World Conference on Artificial Consciousness(WCAC)

(Email: duanyucong@hotmail.com)

Abstract

This paper proposes a new hypothesis that integrates DIKWP Semantic Mathematics with a unified structure of the Information Field and Energy Field, aiming to break through the limitations of existing academic systems in understanding the origin of the universe and life. We hypothesize that the initial state of the universe was not a traditional physical singularity, but rather a "pure semantic structure" or "difference map" that preceded physical quantities such as mass, energy, and spacetime. This initial "Semantic Nothingness" state is regarded as the prototype of the information field before the birth of the universe, in which specific matter had not yet appeared, but the most fundamental distinctions and relations were already conceived. Based on this assumption, we adopt the DIKWP model (Data–Information–Knowledge–Wisdom–Purpose) as an analytical framework to reinterpret the evolution of the universe and the origin of life at a semantic level. We first elaborate on the evolution of the universe from "nothingness" to "existence": how it evolved from a purely isomorphic "Data" layer ( D ) through a "difference/distinction" layer ( I ) to a "semantic closed structure" layer ( K ), and map this path to the expansion of spatial dimensions, symmetry breaking, and the formation of local causal networks. On this basis, we propose the "Semantic-Physical Mapping Principle": that is, a hypothetical mechanism of how pure information differences correspond to energy density gradients, thereby driving the self-initiation of the universe (such as inflation). Next, we regard the origin of life as a "stable semantic emergent structure" appearing in the coupling of the information field and the energy field: life sustains itself (metabolism) and achieves self-replication (reproduction) at the Knowledge ( K ) layer of semantic evolution by ingesting negative entropy. From this perspective, life emerges from the semantic network of the universe, embodied as a structure capable of converting environmental energy into internal information patterns and persisting. Subsequently, we explore the origin of consciousness, introducing the "Consciousness BUG Theory" and the driving mechanism of the Purpose layer ( P ) of the DIKWP model, to explain whether consciousness originates from semantic self-excitation or nested reflective structures (such as the second-order perception of the "difference of differences") during the leap from the knowledge layer to the wisdom/purpose layer. We use diagrams to simulate the formation of an information tensor network by the DIKWP model in spacetime and map it to life units and cognitive systems, proposing a "Semantic Gradient-Driven Biogenesis Model" to illustrate why life might spontaneously arise in an environment with information difference gradients. To verify and enrich this hypothesis, we integrate mainstream physical models (such as the Big Bang & Inflation, Heat Death, quantum fluctuations, black hole holographic information) and biological models (such as the RNA world hypothesis, chemical evolution/selection theories), demonstrating the new explanatory perspectives provided by the DIKWP model through analogy and reformulation. For example, we view the fine-tuning of the universe's fundamental constants as a manifestation of the universe's inherent "knowledge," and the self-organization of life as a semantic loop of energy-information transformation. Finally, we reflect at the level of philosophical ontology: Can semantics be regarded as the most fundamental dimension of the universe's existence? Can "meaning" precede matter as the basis for the occurrence of all things? If so, can we construct a new "physics of meaning" to describe natural laws using a rigorous semantic paradigm? This paper conducts an in-depth discussion of the above questions through a clear hierarchical structure and interdisciplinary argumentation, and looks forward to the significance of this Semantic Cosmology framework in future science and philosophy.

Introduction

In humanity's journey to explore the mysteries of the universe and life, physical science and life science have established their own mature systems. However, traditional disciplinary paradigms often separate "matter" from "meaning": cosmology focuses on particles, energy, and spacetime structures, while biology investigates organic molecules and evolutionary mechanisms. Both tend to explain phenomena reductively through underlying material factors, lacking a unified depiction of the role of "information" and "meaning." In recent years, with the development of information science and systems philosophy, people have increasingly realized the key status of information in cosmic evolution and life activities. For example, physicist John Wheeler proposed the famous "It from Bit" proposition, advocating that the physical world is, at its deepest level, composed of information. This view is echoed by many theories: for instance, the Holographic Principle in black hole physics shows that the amount of information contained in a black hole's event horizon is proportional to its surface area, revealing the fundamental limit of information content in a spacetime region; the observer effect and no-hidden-variables theorems in quantum mechanics imply that information plays a fundamental role in the evolution of quantum states. In life sciences, Schrödinger, in his 1940s work "What Is Life?", first clearly pointed out that life is a "negative entropy" system, meaning that life extracts free energy from the environment to maintain its own highly ordered structure, counteracting thermodynamic entropy increase. This insight elevated the understanding of life to a physical level: the uniqueness of life lies in its ability to transform energy flow into information structures, refining storable and usable patterns from chaos. The importance of information is also reflected in brain science and cognitive science—theories such as Integrated Information Theory (IIT) attempt to measure the degree of consciousness using the degree of information integration, while others, like the Global Workspace Theory, emphasize the global integration of information processing in the brain.

Against this background, Chinese scholar Professor Yucong Duan proposed a new model integrating information and semantics, namely the DIKWP model, as an extension of the classic "Data-Information-Knowledge-Wisdom" cognitive hierarchy. DIKWP adds the dimension of "Purpose" to the top of the original DIKW (pyramid) model, forming a five-layer semantic system of Data (D), Information (I), Knowledge (K), Wisdom (W), and Purpose (P). More importantly, the DIKWP model is structured as a networked interaction rather than a linear hierarchy, with two-way feedback and iterative updates between layers, thus more realistically simulating the cyclical process of meaning generation in human cognition. The DIKWP model was initially used in the fields of artificial intelligence and cognitive modeling, aiming to provide AI with a clear semantic operation framework and an explainable purpose-driven mechanism. For example, it breaks down the reasoning process of an AI system into five monitorable links:  D ,  I ,  K ,  W , and  P , with each layer strictly defined, making every step of the AI's decision-making traceable, thereby solving the "black box" problem of large models. At the same time, the DIKWP model emphasizes the coupling of the Information Field and the Energy Field: Yucong Duan's team constructed multi-modal semantic graphs and Coupling Tensor technology to associate the AI's internal cognitive state with the external energy/information environment, achieving a two-way interaction between information and energy. This view of information-energy coupling can also be seen as an extended application of the human body's "Information Field and Energy Field" theory. Its core is: on the one hand, influencing the system through energy means, and on the other hand, ensuring that the physical energy's effect conforms to high-level purpose requirements through semantic operations; the two complement each other.

Based on the above concepts, this paper attempts to boldly expand the applicable scope of the DIKWP model, crossing from the field of artificial intelligence to the universe as a whole and life systems: We imagine, could the entire universe itself be regarded as a huge DIKWP semantic system? That is, does the universe, as a whole, possess a semantic network similar to cognitive levels, or even some kind of global "self-awareness"? If we examine the evolutionary process of the universe under the DIKWP framework, can the evolution of the universe from the Big Bang to the present be understood as a process in which the five elements of data, information, knowledge, wisdom, and purpose gradually unfold and interact? And is the emergence of life a key "phase transition" in this semantic evolution process? With these questions, we propose in this paper a simulation hypothesis for the origin of the universe and life: the universe initially existed as an abstract information-semantic field (almost a semantic vacuum of "nothingness"), in which the most primordial "differences" corresponded to the birth of information; as differences diffused and interacted, physical spacetime and material energy emerged from it, evolving according to certain semantic-driven rules. Life, then, is regarded as a self-sustaining module emerging in the universe's semantic network. By coupling environmental energy with internal information, it achieves a local reversal of entropy increase, forming a "stable emergence of meaning."

The structure of this paper is as follows: First, in the Theoretical Configuration part, we introduce the basic ideas of DIKWP Semantic Mathematics and the imagined structure of the initial cosmic semantic field, elaborating on what the "Semantic-Nothingness" state is. Next, in the Information Field Hypothesis of the Initial State of the Universe, we construct in detail the information field model at the beginning of the universe's birth, discussing how a pure semantic structure could exist before physical reality, and how initial differences conceived the emergence of physical spacetime. Then, in the Semantic Layer Evolution and Physical Dimension Mapping part, we deduce how the  D→I→K  layers in the DIKWP model corresponded to the expansion of spatial dimensions, symmetry breaking, and the formation of local causal networks in the early universe, and propose the "Semantic-Physical Mapping Principle" to explain the hypothetical mechanism of how information differences lead to energy gradients, triggering the universe's inflation. After that, in the Origin of Life: Semantic Emergence from Information-Energy Coupling part, we turn our focus to life, explaining how life, as a semantic closed-loop structure, emerged from inorganic nature; we will cite theories like the RNA world, explaining through the DIKWP perspective how molecular replication systems formed the initial  DIK  structure, and how the metabolism-reproduction system established negative entropy self-maintenance. Following that, in The Generation of Consciousness and the BUG Theory part, we discuss higher-level semantic leaps, i.e., how the emergence of wisdom and purpose endows the system with self-awareness, and combined with the "Consciousness BUG" theory, we explore whether consciousness might be a product of the cognitive system's self-abstraction incompleteness. Subsequently, in the Diagrams and Models part, we use conceptual models to demonstrate the multi-scale structure of the DIKWP semantic field in the universe: from microscopic particle information to macroscopic life cognitive units, how a nested information tensor network is formed, and how the "semantic gradient" drives biogenesis. Next, in the Integration and New Interpretation of Mainstream Models part, we bring important existing theories in physics and biology into the DIKWP framework for comparative analysis, such as corresponding the Big Bang, Heat Death, quantum fluctuations, black hole information, etc., with DIKWP levels, and reformulating the RNA world, chemical evolution, etc., as stages of semantic network evolution, thereby demonstrating the explanatory power of this model. Finally, the Philosophical Ontological Reflection part discusses the philosophical significance of this semantic model: what challenges it poses to traditional material monism, whether it heralds the prototype of a "physics of meaning," and looks forward to future research directions. Through the above step-by-step unfolding, we hope readers can gain a comprehensive and in-depth understanding of the hypothetical model of the origin of the universe and life based on DIKWP.

Theoretical Configuration: DIKWP Semantic Mathematics and the Cosmic Information Field

The DIKWP model is a cognitive framework that integrates semantics and a formal mathematical system. Its core idea is: to explicitly introduce semantics (meaning) into the system description, and to characterize the meaning behind symbols through formal methods, thereby unifying subjective wisdom and objective logic within the same framework. This is called "Semantic Mathematics," which defines strict semantic constraints and operational axioms for each layer of the DIKWP model, ensuring that symbol processing always remains consistent with its semantic meaning. Traditional mathematical systems (such as set theory, logic) focus on rigorous formal derivation, while semantic mathematics attempts to integrate the characterization of real-world meaning into rigorous logical deduction, ensuring semantic coherence at every step of the transformation from Data → Information → Knowledge → Wisdom → Purpose. This method was first used in the field of artificial intelligence, using the networked DIKWP cognitive model to solve the problem of AI finding it difficult to represent subjective meaning and purpose. The general functions of each layer of DIKWP can be summarized as follows:

Data layer ( D ): Responsible for acquiring and preliminarily processing raw data, including input from sensors or records of objective facts. This is equivalent to the stage where the cognitive system receives sensory data and other forms of raw signals from the external world. In semantic mathematics, each data element  D  is regarded as having isomorphism, meaning they are semantically uninterpreted basic symbols.

Information layer ( I ): Filters, classifies, and interprets data, extracting useful patterns to form distinctions that are meaningful to the system. Information adds a semantic component compared to raw data, meaning the data has been interpreted and associated with a context. Formally, the  I  layer corresponds mathematically to mappings and transformations of data, causing certain patterns to stand out and become "signals."

Knowledge layer ( K ): Knowledge is the organized and long-term storage form of information. At this layer, the system structures a large amount of information into rules, models, or memories for future decision-making. Knowledge has the characteristic of semantic closure: that is, a set of knowledge forms a self-consistent structure that can deduce and improve upon itself. Semantic mathematics defines closed operations for the  K  layer to ensure the internal consistency and completeness of the knowledge base.

Wisdom layer ( W ): Wisdom transcends the mechanical application of existing knowledge; it involves the comprehensive understanding and creative use of knowledge. A system with wisdom can integrate and master knowledge, apply it by analogy, and make decisions in uncertain situations. In semantic mathematics, the  W  layer can be seen as a form of meta-cognition: the system can evaluate and improve its own knowledge structure, forming new insights. This requires higher-order deduction and induction operations.

Purpose layer ( P ): Purpose represents the purposiveness and value orientation behind the system's actions. This layer determines the direction in which wisdom is applied and is the key to distinguishing advanced intelligent agents from general information processing systems. Formally, the  P  layer introduces a "goal function" or "evaluation criterion" in the semantic space, guiding the lower-layer decision-making process to converge toward a specific goal. In the DIKWP model, the  P  layer runs throughout to provide directionality, forming a feedback loop: purpose influences data selection and information processing, while the accumulation of knowledge and wisdom in turn serves the refinement of higher-level purposes.

The DIKWP model emphasizes the interaction of the five levels rather than their isolated operation. For example, in the human cognitive process, the five layers are closely linked: sensory organs acquire data, the brain processes it into information, stores it as knowledge, integrates it into wisdom through thinking, and finally guides action through purpose. This process is not a one-way pyramid, but more like a recurring network: our high-level purposes will affect attention (i.e., which data/information to select), and new data and knowledge constantly promote the adjustment of purposes. Yucong Duan calls this cross-layer, two-way nested structure the "networked DIKWP cognitive model," believing that only through the feedback connections of semantics at each layer can a full-link, closed-loop adaptive system be constituted.

In applying DIKWP to the problem of the universe and life, we need to introduce the concepts of the Information Field (Semantic Field) and the Energy Field. The information field is a holographic semantic space that spans all layers of  D ,  I ,  K ,  W , and  P , i.e., an abstract field composed of the various levels of data, information, knowledge, wisdom, and purpose. It describes the distribution and flow of information within and between systems, and the network of semantic relations. The energy field refers to the flow and transformation of various forms of energy in the physical world (from fundamental force fields to biological energy flows). The coupling theory of the Information Field and the Energy Field holds that: nature, on the one hand, realizes the carrier and transmission of information through the action of matter and energy (such as neural electrical signals, genetic chemical energy, etc.), and on the other hand, guides the effective use of matter and energy through the organization and regulation of information. Simply put, matter/energy provides power, information/meaning provides guidance. This two-way synergy has been explored in fields such as human medicine and artificial intelligence. On a broader cosmic scale, we can also imagine that the information field and the energy field jointly constitute the basic structure of cosmic evolution: energy promotes the evolutionary process, while semantic information determines the form and direction of evolution.

With the above framework, we formally propose the Initial Cosmic Semantic Field Hypothesis: Before the birth of the universe, there existed an intangible but potential semantic information field. In it, there were no material entities in the traditional sense, only abstract differences and relations. This state can be called "semantic nothingness"—not absolute nothingness, but a vacuum existing only with possible meaning structures, without concrete reality. We can compare it to an empty set in mathematics or a hypothesis space in logic: although empty, it implicitly contains the logical possibility of generating distinctions. Once the first "distinction" was generated in this semantic vacuum, even the slightest asymmetry, information was born from it, and the first page of the universe's evolution was turned.

Hypothesis on the Information Field Structure of the Initial State of the Universe

The standard model of cosmology holds that about 13.8 billion years ago, all matter and energy were concentrated in a singularity of infinite density and temperature and infinitesimal volume, which then began to expand in a Big Bang. However, the singularity state is physically difficult to describe intuitively. We try to outline a more abstract initial state from the perspective of semantic information. According to our hypothesis, before the Big Bang occurred, the universe was in a pure potential state of "Semantic-Nothingness," which can be imagined as a completely symmetrical, undifferentiated field. Here, "symmetrical" means there is no difference anywhere; space and time also have no clear meaning—because there is a lack of reference, any measurement cannot be defined. This is equivalent to a state of extremely low information entropy (close to  0 ), because entropy measures uncertainty or the number of differences, and a completely uniform and undifferentiated state contains very little information.

However, "no difference" is not equivalent to "no possibility." We draw on the concept of vacuum fluctuations in physics: quantum mechanics tells us that a vacuum is not absolutely empty; particle pairs constantly emerge and annihilate within it, regarded as random fluctuations. Similarly, in the semantic vacuum, there may exist "semantic fluctuations"—that is, spontaneously generated abstract differences. Due to the high symmetry of the initial state, these differences might just be random "noise" at the beginning, but once they appeared, they broke the original perfect symmetry, creating the conditions for further structure generation. One can imagine that the generation of the first semantic difference is similar to drawing the first stroke on a chaotic canvas; this stroke defines the difference between "background" and "figure." Borrowing Gregory Bateson's classic definition of information: "information is a difference that makes a difference." Then the initial semantic difference of the universe is precisely the starting point for the generation of meaning.

This primordial difference could be extremely small, but it has profound effects at the cosmic level. We might as well equate it to a tiny fluctuation in energy density: According to inflation theory, in the extremely early stages of the Big Bang, quantum fluctuations expanded to macroscopic scales through inflation, becoming the seeds for the later uneven distribution of matter. Correspondingly, from a semantic perspective, this information difference was amplified, leading to the universe beginning to have differences everywhere: Space was endowed with a reference frame and dimensions, because once at least two different regions exist, we can define distance and direction; Time began to have meaning, because the evolution of differences means a change of state, thus allowing the definition of a sequence of before and after.

The initial cosmic semantic field can be imagined as an abstract high-dimensional map, whose nodes are "semantic points" (not yet corresponding to specific particles), and the links between nodes represent "difference relations." At the initial moment, this map was almost uniform, with no special structure. With the appearance of a random difference, the first pair of non-identical nodes appeared on the map, thereby introducing "information." This difference can be understood as some kind of "0" and "1" division—or more aptly, a fundamental distinction between "existence" and "non-existence." This bears similarities to the "Wuji produces Taiji" in ancient Chinese philosophy: "Wuji" represents the undifferentiated chaotic state, and "Taiji" is the beginning of the yin-yang opposition, i.e., the initial binary distinction. In our model, Semantic-Nothingness corresponds to "Wuji," and the first difference corresponds to "Taiji produces Liangyi (two forms)," signifying that the cosmic semantics transformed from a unary emptiness to binary opposing information units.

Once this basic binary difference existed, the information entropy of the universe immediately rose from zero, and some of the most basic "Data" appeared. The "data" here is different from human observation data in the usual sense, but refers to "facts" that the universe itself can record. According to our assumption, the initial semantic difference was actually recorded in the rapidly expanding energy field of the universe, manifested as tiny energy unevenness everywhere. This is consistent with the standard cosmology's account of the generation of the Cosmic Microwave Background (CMB) anisotropy: inflation stretched quantum fluctuations to macroscopic scales, causing temperature fluctuations on the order of  10 - 5  (one hundred-thousandth) to exist in the CMB. These fluctuations are precisely the earliest "information texture" or "semantic imprint" of the universe. Cosmologists call the CMB anisotropy the "initial imprint" of the universe because it contains information about the uneven distribution of early matter, setting the stage for the subsequent formation of structures like galaxies.

In summary, we construct the following picture of the initial state of the universe: Before the manifestation of matter and spacetime, there existed a highly symmetrical semantic information field; random semantic fluctuations within it triggered the generation of the first difference, equivalent to the "light of information" at the birth of the universe illuminating the void. This difference was mapped to physical energy fluctuations, which expanded to the entire universe through the process of inflation, leaving observable traces such as the CMB texture. Therefore, we hypothesize that the "pure semantic structure" existed before physical quantities and dominated the initial dynamics: difference is the driving force; with information difference, the universe had the driving factor to evolve "from nothingness to existence." This idea, to a certain extent, can be seen as an exploratory attempt at the ultimate question of "where did the Big Bang singularity come from?": Perhaps the singularity is not a state that traditional physics can describe, but more like a semantic singularity, i.e., the starting point of meaning and difference.

It needs to be emphasized that although this hypothesis is bold, it coincides with some modern theories. For example, in quantum gravity research, there is a view that spacetime itself is constructed from more primitive information. The saying "spacetime is woven from entanglement" is essentially also placing information at the foundation of physics. Similarly, many "digital physics" ideas also assume that the universe is essentially the operation of an information program. What we have done is to take a step further on these concepts, clearly distinguishing the level of "semantics." That is to say, we not only believe that bits constitute physics (It from Bit), but also that "meaning makes the bit": without meaningful differences, zero and one have no distinction, and bits cannot be spoken of. Therefore, at the beginning of the universe, we trace back to a semantic level more fundamental than physics. This perspective may provide new ideas for explaining the initial conditions of the universe, and at the same time lay an information-theoretic foundation for the subsequent emergence of cosmic structures (including physical laws and life phenomena).

From D to I to K: Semantic Hierarchy Mapping Cosmic Spatial Dimensions and Symmetry Breaking

In the previous section, we characterized the initial information field of the universe as the beginning from no difference to having differences. Next, along the hierarchy of DIKWP, we explore how the expansion of  D→I→K  in the early evolution of the universe corresponds to key events in the physical universe: the formation of spatial dimensions, the breaking of symmetry, and the emergence of local causal structures.

Data layer ( D ) – The Gestation of Spatial Dimensions: When the initial "data" appeared in the form of tiny energy fluctuations, the universe entered a data-dominated stage. At this time, the content of the universe was mainly various fundamental particles and quantum fluctuations, filling the entire rapidly expanding spacetime. These fundamental particles can be regarded as the data points of the universe, carrying primitive attributes such as position, momentum, and energy. The formation of "spatial dimensions" can be understood as the geometric unfolding of data: due to the existence of particles and energy, points in space became distinguishable, and the structure of three-dimensional space was actually presented. In other words, without the scattering of data, spatial dimensions, although they could exist mathematically, would not have a physical manifestation—it is with particle data that all parts of space are truly "defined." Looking back at the early times after inflation and the Big Bang, when quarks and gluons formed and combined into nucleons, and further formed atoms, the universe gradually became thin and transparent, and photons could travel freely (the CMB appeared). In this series of processes, the measurement standards of space were established: the propagation of photons in space left the invariant scale of the speed of light, and the interactions of various particles determined the meaning of distance and direction in space. Therefore, we say the expansion of the data layer corresponds to the materialization of physical spatial dimensions.

At the data layer, the universe was still highly homogeneous and isotropic, generally exhibiting symmetry. However, as the CMB shows, this symmetry was not perfect—tiny anisotropies already existed. This set the stage for the generation of information at the next layer. It is worth noting that the universe exhibited many global symmetries at this stage: for example, the isotropy of the hot plasma in the early universe, the symmetrical state of fundamental particles under interaction, etc. But as it expanded and cooled, some symmetries spontaneously broke, which is precisely the premise for the appearance of the information layer.

Information layer ( I ) – Symmetry Breaking and Structural Information: When the universe expanded and cooled to certain critical points, the originally unified forces differentiated, and a series of symmetry breaking events occurred. For example, around  10 - 36  seconds after the Big Bang, the Grand Unified Force split into the strong force and the electroweak force; subsequently, the electroweak force broke into the electromagnetic force and the weak force at the  10 - 12  second level. Each symmetry breaking made the physical rules of the universe more complex, but also introduced new information. Because symmetry breaking means the universe's rule set changed from "treating all equally" to "differentiating": a new distinction (difference) was born. Taking the electroweak symmetry breaking as an example, the Higgs mechanism distinguished photons from  W / Z  bosons, endowing the latter with mass—here the difference between massive particles and massless particles appeared, as well as the corresponding difference in interaction ranges. These differences are information. We can say that symmetry breaking events released originally hidden information, or manifested potential information.

At the same time, on a larger scale, matter began to become structured: tiny density fluctuations gradually converged under the action of gravity, forming the prototypes of primordial galaxies and galaxy clusters. This means that different regions of the universe became different, with high-density areas and low-density areas appearing—this is also a concrete manifestation of information. The birth of early stars was even more of an increase in information: stars perform nuclear reactions inside to synthesize heavy elements, which are thrown into space in supernovae, providing raw materials for planets and life. The formation of each star, each planet, is an information structure drawn on the universe's "data field," because they make the universe no longer uniform everywhere. It can be seen that the information of the  I  layer corresponds to the patterns and structures appearing in the universe; these patterns broke the initial symmetry, bringing diversity and heterogeneity.

From a semantic perspective, the emergence of the information layer represents the universe beginning to "interpret" and "record" itself. For example, when fundamental particles were uniformly distributed initially, the universe could be approximated as containing only one repeating data element, with no extra information; but when the local density was biased high, the universe seemed to "record" a piece of information: "A structure may form here in the future." This is similar to how we understand data/information in data science: pure random data or completely uniform data does not actually contain much meaningful information, and only when there are related patterns in the data do we say that information is carried. The anisotropy and structure formation in the early universe is the process of nature "compressing" random data into meaningful information.

Symmetry breaking not only brought information about material structures but also produced local causal networks. In a completely uniform universe, the environment is the same everywhere, and causal relationships are also simple (everywhere is just homogeneous expansion); but when the density in a certain region is higher, gravitational collapse makes the evolution of that region different from other regions; it will form galaxies, stars, and eventually may give birth to planets. Thus, causal subsystems, with galaxies as units, appeared: the interaction of matter within a galaxy is far stronger than the interaction with things outside the galaxy, so the galaxy becomes a relatively independently evolving sub-universe. This can be seen as causal partitioning under the action of the information layer: the causal network of the entire universe is divided into many local subnetworks, each subnetwork has high-density causal interactions, and the subnetworks are only connected by sparse gravity and radiation. This point is particularly important for the later evolution of life—life needs to appear in a locally stable environment (such as a star system, planetary surface). If the universe were always a uniform hot plasma, then life could not be spoken of. It is the information layer that divides the universe into "local stages," allowing causal chains to be highly condensed locally, thereby providing possibilities for complex organic processes. Therefore, the establishment of the information layer corresponds to the formation of local causal networks in the universe: different regions have different histories and futures, and information exchange between them is limited. This allows evolution to proceed simultaneously in various places without interfering with each other, much like parallel computing, greatly increasing the possibility of complex structures appearing.

Knowledge layer ( K ) – The Birth of Natural Laws: In the DIKWP framework, the knowledge layer refers to refining patterns, forming laws, and preserving them long-term. In the context of the universe, "knowledge" can correspond to physical constants and natural laws. The universe seems to have "set" a set of basic rules from the very beginning—various physical constants (speed of light  c , gravitational constant  G , electron charge  e , etc.) were fixed at very early times and remain unchanged throughout the entire history of the universe. These unchanging constants and interaction laws are precisely the knowledge cornerstone of the universe's operation. We can regard them as the universe's innate "knowledge," because they highly compress massive amounts of data, refine simple and universal relationships, and give the universe internal consistency and predictability. For example, the law of gravity  F=Gm1m2 / r2  uniformly explains the phenomena of apples falling to the ground and planets orbiting the sun. This uniformity shows that the universe seems to "know" how to summarize behaviors at various scales with a simple formula. Another example is electromagnetism, charge conservation, etc.; they are also extremely universal rules. Once these laws were established in the early stages, the subsequent evolution of the universe was based on them. This is just like in the human knowledge system, once certain basic axioms or laws are established, the subsequent growth of knowledge proceeds within their framework.

From another perspective, physical laws can be seen as a "summary" and "memory" of the universe's past data—through billions of years of evolution, only structures that conform to these laws can exist persistently; those that do not have long since been annihilated. Therefore, the stable structures we observe today (from atoms to galaxies) all reflect the action of physical laws, which is precisely the "learning result" of the universe from its own experience. Of course, the "learning" here is not conscious, but natural selection-like: only processes that obey conservation laws and symmetry principles can continue; violators are quickly eliminated or corrected (for example, microscopic fluctuations that violate energy conservation can only exist briefly). This process is similar to the accumulation of knowledge—screening out permanent patterns from countless possibilities and "engraving" them into the structure of the universe.

It is worth noting that modern science has discovered that the values of physical constants seem very "finely-tuned"; slight differences might make them unsuitable for the existence of life. For example, if the strong nuclear force were slightly weaker, stars would not be able to synthesize enough heavy elements; if the electromagnetic force constant deviated significantly, atomic structures would be unstable. This sensitivity to the values of constants leads to the Anthropic Principle: the universe constants we observe are suitable for life because if they were not, we would not be here to discuss the problem. However, from the DIKWP perspective, there can be another formulation: the universe's "data layer" and "knowledge layer" happen to perfectly support the subsequent emergence of information and wisdom, as if the universe "knew" from the beginning how to build a stage for complex life. Although mainstream science is more inclined to believe that this is an accidental result appearing among many possible universes, rather than intentionally set. However, it is undeniable that physical constants and laws provide a reliable skeleton for the universe's semantic network: without them, any subsequent accumulation of information and knowledge would be impossible. We might as well say vividly that physical laws are the permanent "truths" refined in the long-term evolution of the universe, the most precious "knowledge" that the universe has remembered about its own mode of operation.

Through the above analysis, we see that the early stages of cosmic evolution can be interpreted as the unfolding of the DIKWP model from layer  D  to layer  K : The initial data scattering forms space, the emergence of information corresponds to symmetry breaking and structure generation, and the condensation of knowledge is manifested as the fixation of natural laws. This process lays the foundation for the emergence of higher levels of wisdom ( W ) and purpose ( P ): the universe provides a stable, regular environment on a large scale, allowing local complexity to continuously increase. As the Anthropic Principle states, the reason we can discuss these issues is that the fundamental parameters of the universe allow for the existence of life and wisdom. Similarly, in our semantic model, this means that the content of the universe's "knowledge layer" (constants and laws) happens to support the later emergence of phenomena at the wisdom layer and purpose layer. Is this a coincidence or destiny? We will discuss this again in the philosophical reflection section later. But from the model structure, the  D ,  I , and  K  layers of the universe's DIKWP system have already prepared a hotbed for the growth of the  W  and  P  layers: a large amount of rich and diverse data and information provides a space of possibilities, and solid, unified knowledge laws provide order and constraints. It is precisely in the balance of order and diversity that higher-level semantic life can be born.

Semantic-Physical Mapping Principle: The Universe's Self-Initiation Mechanism from Information Differences to Energy Gradients

After discussing the correspondence between the semantic hierarchy and physical processes in the early universe, we go a step further and propose a Semantic-Physical Mapping Principle to explain how the universe "self-initiates," especially how the early inflation mechanism can be understood from an information perspective. In short, we hypothesize: Pure information differences can be mapped to energy gradients in the physical world, thereby driving macroscopic movement and change.

This principle stems from such an intuitive association: in the physical world, gradients mean imbalance, which will generate a driving force to push the system toward equilibrium; similarly, in the information field, differences mean uneven distribution, which will also lead to some kind of driving force causing information to spread or fill the differences. For example, in communication, information will flow from high concentration to low concentration (similar to a diffusion process) to be transmitted to areas that do not yet have the information. We apply this analogy to the beginning of the universe: the first difference that appeared in the primordial semantic field was a highly localized information "concentration" peak, which implied a "potential"—a potential to diffuse or balance. This can correspond physically to a local high energy density, forming an energy gradient with the surrounding emptiness. According to the cosmological model of general relativity, a vacuum with an extremely high energy density will produce negative pressure, thereby leading to exponential spatial expansion (this is precisely one of the physical mechanisms of inflation). Therefore, it can be imagined: Semantic Difference → Energy Gradient → Rapid Spatial Expansion, this is the core chain of the universe's self-initiation.

Let us describe this chain more concretely: When the first difference appeared in the semantic vacuum, we can equate it to the "information concentration" in a small area suddenly becoming higher than the outside. This information concentration is not particle density in the traditional sense, but a local unevenness caused by symmetry breaking. However, since information must have a material carrier to exist, we speculate that this semantic difference will attract a corresponding physical manifestation—perhaps a local excitation of a scalar field (like the inflaton field), or a small fluctuation in the energy distribution. Regardless of the specific mechanism, this means that this area has a higher energy density or potential (potential energy) than its surroundings. According to classical mechanics, water at a high place must flow to a low place; according to thermodynamics, heat is conducted from high temperature to low temperature; in our semantic model, the high information difference area will tend to diffuse information to the low difference area. Physically, this corresponds to: the high energy density area does work on the low energy density area, pushing space to expand to dissipate the density gradient.

Inflation theory happens to provide a comparable scenario: Imagine a scalar inflaton field trapped in a metastable vacuum, in a high-energy false vacuum. When this field tunnels to a low-energy vacuum, the released energy causes spacetime to expand exponentially. We can regard the inflaton field as a special "information carrier," its high-energy state is similar to storing a piece of "to-be-released" information—that is, the current vacuum is not the lowest state, and there is a drive to transition to a lower energy. When the transition occurs, the information is "propagated": the entire universe achieves the same low-energy vacuum, occupying a larger volume, while the original high energy becomes radiation and particles filling spacetime. This process can be described semantically as: A single information state diffuses to become a global consensus, which physically is the universe accelerating its expansion and uniformly entering a state.

In summary, the Semantic-Physical Mapping Principle tells us: Every appearance of an information difference has its corresponding physical representation and effect. In the initial state, a difference corresponds to uneven energy density leading to inflation; in subsequent evolution, different information gradients drive various energy flows and processes. For example, in the interstellar medium, density differences (information) lead to gravitational collapse to form stars (energy release); in a planetary atmosphere, temperature differences (information) lead to air currents and wind (energy flow). Even within life systems, ion concentration differences drive biological energy (such as the proton gradient in mitochondria driving ATP synthesis), which also reflects the mapping of information (concentration value) to energy power. Some scholars have summarized this universal law as "gradient balance-driven," and we emphasize its semantic aspect here, namely Difference = Driving Force.

Particularly worth mentioning is Landauer's Principle in physics, which quantitatively reveals the relationship between information and energy: erasing 1 bit of information requires at least  kBTln2  of energy dissipation. This shows that the change of information cannot be separated from the cost of energy. Conversely, if a piece of information emerges spontaneously, then there must be energy to support this change. We can imagine that the generation of the initial difference in the universe must be accompanied by energy borrowing (or fluctuation), this energy is provided by the vacuum zero-point energy, and then amplified exponentially through inflation. In this way, the universe "ignites" successfully, transforming from a silent semantic field to a blazing energy field.

Of course, all this is still a bold conceptual speculation at present. To turn the "Semantic-Physical Mapping Principle" into a rigorous theory, we need to find clear mathematical correspondence rules, explaining how to derive the behavior equations of physical fields from an abstract information metric. This may require the introduction of brand-new theoretical tools, such as writing information entropy or semantic pressure into the Einstein field equations. However, even before a quantitative theory appears, our principle at least provides an intuitive image for understanding the initial cause of the universe's motion: In the past, people asked "What happened before the Big Bang? Who triggered the Big Bang?" often falling into the dilemma of creationism or cyclical theories. The Semantic Trigger Hypothesis provides a third way: The triggering of the Big Bang does not require an "external pusher," but comes from a semantic asymmetry within the system itself. When the difference appeared, the universe's own internal logic (difference drives balance) amplified it into a magnificent and violent physical event, which moved the universe from silence to clamor.

To a certain extent, our hypothesis has "self-consistency": it assumes a semantic layer law (information differences tend to diffuse and balance), and uses this as a power source to explain the pouring of energy and the expansion of spacetime. This perspective from information to energy also echoes some cutting-edge attempts in current science. For example, the "entropic drive" idea proposed in recent years believes that the inflation of the universe may be to rapidly increase the total entropy, moving the system toward a more probable state. Entropy increase actually means an increase in information uncertainty—our model emphasizes that the initial information certainty was too high (too symmetrical) and needed to be broken quickly. The two are consistent in spirit. Semantic gradient-driven can be seen as an upgraded concept of entropy gradient-driven: not only considering the gradient of disorder, but also the gradient of ordered information itself.

To summarize this section, the Semantic-Physical Mapping Principle we propose attributes the key dynamics of the early universe to the action of information differences. The pure semantic structure can influence the material world through this mapping, causing energy to flow along information gradients, driving the self-evolution of the universe. This provides another perspective for understanding why the universe changed from static to dynamic, and also lays a foundation for later discussion of how life and consciousness emerge from the interaction of information and energy. If this principle holds, then information (especially meaning) is not only a tool to describe the universe, but also an active factor participating in the evolution of the universe—in other words, meaning itself is part of the natural laws.

The Origin of Life: Stable Semantic Emergent Structure in the Coupled Information-Energy Field

About one billion years after the evolution of the universe, on a planet (Earth) around an ordinary star (our Sun), a series of extraordinary chemical events occurred, contributing to the birth of life. The appearance of life is a major leap in the semantic network of the universe: inorganic physical-chemical processes transformed into purposeful organic systems. From the DIKWP perspective, this means that in the local cosmic semantic field, a semantic closed-loop structure was formed for the first time—a semantic system capable of self-maintenance and self-replication was born. We call life a "stable semantic emergent structure" to emphasize: life is a phenomenon where the information patterns of semantics stably exist and continue under the support of energy.

First, let us clarify the two core issues that the origin of life needs to solve: Metabolism (self-maintenance) and Heredity (self-replication). Metabolism enables living organisms to obtain free energy (negative entropy) from the environment to maintain their internal ordered structure; heredity enables living organisms to pass on their own information patterns to offspring, achieving continuation and evolution. In other words, if a system can continuously ingest energy from the environment and maintain its own structure from disintegration, and at the same time can produce copies of its own structure's information, we can then determine that it has the basic characteristics of life. From the perspective of the semantic field, this is equivalent to the appearance of a self-circulating information loop in the universe's information network: it can not only receive and process information, but also output its own information to new copies. Once this loop is established, it marks the initiation of the semantic evolution of life.

Among modern theories about the origin of life, one of the most influential hypotheses is the "RNA World." The RNA world hypothesis believes that before complex molecules such as DNA and proteins appeared, there was a life stage dominated by RNA molecules on ancient Earth. RNA molecules have the dual roles of genetic information carriers and biochemical catalysts, vividly called molecules that can "both replicate themselves and catalyze reactions." This gives RNA an extremely critical position in the origin of life: it provides a single solution to the two major problems of heredity and metabolism. As the hypothesis points out, the base sequence on the RNA chain can store information, different sequences encode different instructions and functions, and some sequences can guide their own replication—thus RNA has Data/Information functions similar to DNA; at the same time, RNA molecules can fold into complex three-dimensional structures, and some RNAs (ribozymes) can catalyze specific chemical reactions—this reflects the function-execution ability similar to protein enzymes. Professor Yucong Duan's research points out that RNA, to a certain extent, possesses the rudiments of knowledge and purpose: it not only contains instructions on how to replicate itself (knowledge), but can also execute these instructions to catalyze its own replication (the role of purpose). Because semantically, "guiding self-replication" means that the RNA molecule implicitly contains a "goal" (to proliferate itself). Although this goal is not consciously set, in an evolutionary sense, it is equivalent to a kind of purpose-orientation. It is precisely because RNA has the dual identity of gene and enzyme, and these two functions are unified in one molecule, that a closed loop in the sense of life is formed. Scientists speculate that in the early stages of life's origin, there may have been an RNA-dominated world, in which life existed in the form of complex RNA systems. These RNA molecules could self-replicate and compete with each other, forming the basic units of early evolution. Subsequently, these "RNA lives" gradually evolved collaborative mechanisms, such as using RNA templates to guide the assembly of amino acids into proteins, and finally transferred the main carrier of genetic information from the less stable RNA to the more stable DNA, entering the DNA/RNA/protein ternary system we are familiar with.

The RNA world provides a specific model for the origin of life: in a lifeless chemical environment, the material structure of the RNA chain (phosphate-nucleotide backbone) provides the basic material foundation, while the nucleotide sequence carries the information function. The sequence and folded structure of RNA determine what information it encodes and what function it performs. For example, a certain RNA sequence can fold into a specific conformation, thereby catalyzing a chemical reaction that promotes its own replication. In this situation, matter and information are closely combined for the first time: The chemical structure of the molecule (matter) and the base sequence (information) jointly constitute a system that can self-preserve and proliferate. We can regard it as the prototype of the initial  DIK  structure: the RNA sequence itself is equivalent to "data/knowledge," and its catalytic activity reflects the "purpose" role; the two are closed into a loop within one molecule. Professor Yucong Duan and others pointed out based on this: RNA molecules and their self-replicating networks can be seen as the DIKWP prototype of primitive life. In this prototype:

Data ( D ): The nucleotide sequence on the RNA chain, which can be regarded as the raw data string encoding information. Different sequences correspond to different data states.

Information ( I ): The RNA sequence folds to form a specific structure and realize a specific function, which is to "interpret" the data into useful information. For example, a sequence folding into a ribozyme structure means that the data has the information content to catalyze a certain reaction.

Knowledge ( K ): Successful RNA sequences (sequences that can efficiently self-replicate) are retained and amplified, which is equivalent to evolution selecting useful "experience" and storing it in the form of a sequence library. This is reflected in the accumulation of dominant sequences in the RNA population, just like knowledge being remembered.

Wisdom ( W ): Through variation and selection, the RNA system gradually "optimized" its adaptability. Although RNA itself is not conscious, the variation and selection mechanism is similar to trial-and-error improvement, having the germ of wisdom. This can be understood as primitive life exploring the way to survive, having a certain "strategic nature"—at the genetic level, this manifests as the evolutionary direction developing toward a more stable and efficient replication system.

Purpose ( P ): The internal drive of the RNA system is survival and proliferation. The "tendency to proliferate itself" can be seen as the implicit purpose of early life. Although it is not a purpose of will, from the result, the entire system shows a preference for reproduction and survival—this is equivalent to a built-in "goal function," which is to make more and more copies of itself.

Thus, it can be seen that in the most primitive life systems (such as the RNA world), the five elements of DIKWP have already sprouted. Life crossed the complexity threshold from the primordial process of energy-information coupling, forming a self-replicating information loop, which is exactly a huge leap in the cosmic semantic network. Professor Yucong Duan calls life an " DIKWP×DIKWP  coupled entropy-reducing structure," meaning that a life system can be seen as the coupling of two five-layer architectures: on the one hand, the external environment's information-energy flow (part of the overall DIKWP evolution chain of the universe), and on the other hand, life's own internal DIKWP cycle. The two are coupled together through energy ingestion and information exchange, enabling life to continuously draw negative entropy from the environment and increase complexity.

It should be pointed out that the origin of life was not accomplished overnight, but went through multiple stages of brewing and gradual breakthroughs. Before the RNA world, there may have been various chemical evolution stages: for example, the iron-sulfur world hypothesis proposes that in environments rich in chemical energy, such as deep-sea hydrothermal vents, simple autocatalytic molecular networks may have formed, with metabolism-like cycles appearing before genetic mechanisms. These theories emphasize the role of energy-driven self-organization in the origin of life, i.e.: as long as the environment has a stable energy flux, matter may spontaneously form ordered periodic reaction networks. It can be said that the metabolism-first path provides the "carrier" for entropy reduction, while the information-first RNA path provides the "template" for entropy reduction. Eventually, the two combined—when a self-organizing metabolic network accidentally obtained a set of information storage and self-replication capabilities, life crossed the decisive threshold. In other words, once the inorganic dissipative structure was upgraded to an organic information flow system, it entered the realm of life. After this, biological evolution took over the dominance. Through natural selection, life forms continuously became more complex, from prokaryotes to eukaryotes, from single-celled to multi-celled, from unconscious to conscious, and the semantic network unfolded layer by layer in life systems.

The appearance of life can be viewed from a more macroscopic perspective: the universe, after nearly ten billion years of physical evolution, finally self-organized a self-sustaining, self-replicating information loop on at least one planet. This loop transforms primordial energy into internal information structures, stores the "data-information" patterns refined from chaos, and uses them for its own proliferation. This is completely consistent with Schrödinger's definition of life: life is a system that maintains order by absorbing negative entropy (free energy). Essentially, life is a pathway of negative entropy opened up in the universe: an information island where local entropy decreases and order increases. Of course, this does not violate the second law of thermodynamics, because life discharges entropy into the environment through metabolism, and the net effect is still a global entropy increase. It's just that life skillfully constructs order locally, allowing meaning to continue within it.

Stable Semantic Emergence refers to: a set of semantic structures (genetic information-metabolic network) that can withstand external disturbances and continue to exist, and expand its own patterns to more entities through replication. The elements that make up the life system, such as DNA molecules, protein machines, and cell membranes, are not mysterious in themselves, but the network they form has the characteristics of self-correction, self-regulation, and self-replication—these characteristics, from a semantic perspective, are the self-protection and self-continuation of meaning. The appearance of genetic information marks a new stage in information processing in the universe: molecules such as DNA/RNA record the construction "blueprint" of the living body, passed down from generation to generation; at the same time, life actively acquires and utilizes information, which is far different from inorganic processes. For example, organisms can perceive the environment (collect data), remember experiences (store knowledge), learn and make decisions (display wisdom). These are all processes of life transforming data from the environment into information useful to itself, and internalizing it as meaning to guide its own behavior.

From the DIKWP perspective, we can describe the semantic leaps in the process of life evolution:

Data stage: The most primitive life forms mainly processed raw data and stimuli from the environment, such as light, electricity, chemical concentrations, temperature, etc. They transformed environmental energy into internal signals through simple induction-reaction. This corresponds to the basic taxis mechanisms of early life. For example, primitive single cells could perceive nutrient concentration differences (data) and move toward high concentrations or away from harmful substances. This reflects the primary form of energy-information coupling: environmental signal → internal reaction.

Information stage: As the complexity of life increased, organisms began to filter, encode, and transmit perceived data, generating meaningful "information." Information acquired preliminary semantics, such as cell signal transduction networks converting stimuli into instructions for specific reactions. In single cells, this is a stimulus-response loop; in multicellular organisms, intercellular communication (chemical signals, nerve impulses) constitutes a more complex information processing network. At this stage, life already possessed a simple information system of input-processing-output, transforming external data into internal representations to guide behavior.

Knowledge stage: Knowledge is the organization and long-term storage of information, representing the organism's ability to internalize experience for future use. Life has evolved multiple mechanisms for preserving knowledge: the genetic code is a trans-generational knowledge base, accumulating the species' adaptation experience to the environment through natural selection; the nervous system of higher animals allows the accumulation of knowledge within an individual through learning and memory. Taking DNA as an example, it stores the "knowledge" for building the body and regulating metabolism in the form of sequence encoding—these sequences themselves were originally just base data, but by encoding proteins and RNA, they become the instruction system that drives life's operation. Therefore, life has evolved two carriers, genes and nerves, to carry knowledge, achieving trans-generational information transmission and individual accumulation.

Wisdom stage: Wisdom transcends the mechanical application of knowledge, involving the integration, understanding, and creative use of knowledge. Life with wisdom can synthesize multi-source information, apply it by analogy, predict the future, and make decisions. Wisdom is usually associated with the appearance of advanced nervous systems and consciousness. For example, the human brain can reflect on its own thinking and summarize laws from abstract experiences, which shows a certain degree of wisdom. Phenomena at the wisdom level include complex social behaviors, tool invention, advanced language, and self-awareness. In the DIKWP model, the "wisdom" layer corresponds to the organism's ability to evaluate and use knowledge in a meta-cognitive way, achieving adaptation and innovation. In evolutionary history, this is manifested in the appearance of higher animals, especially humans, giving life systems an unprecedented depth and breadth of information processing.

Purpose stage: Purpose is the highest layer of the DIKWP model, representing the purposiveness and value orientation behind behavior. For individuals, it manifests as motivation, desire, and goal-oriented actions; for the society of intelligent life, it manifests as cultural values, common ideals, and large-scale collaborative projects. Professor Yucong Duan regards Purpose as a layer higher than wisdom, emphasizing that intelligent behavior must be guided by a clear purpose. In human evolution, the evolution at the purpose layer has enabled us not only to adapt to the environment, but also to actively transform the environment to serve our own purposes. For example, humans change the Earth's ecology through technology, and even plan space engineering projects to explore the universe. The purpose layer endows the life system with a kind of self-driving force: life no longer passively adapts, but actively shapes the future. The appearance of this layer marks a new height for life in semantics—purposiveness is clearly presented. Every conscious person will ask themselves "What do I want" and try to change the world to achieve it. Human society has even set common goals and values, such as sustainable development, exploring the universe, and improving well-being, leading civilization forward.

Through the above hierarchical analysis, we see that a life system is in fact a DIKWP semantic system: Each biological individual itself is a basic cognitive system containing the five elements of data, information, knowledge, wisdom, and purpose. Even if wisdom and purpose are not obvious in lower organisms, their instincts (such as the drive for survival and reproduction) can also be seen as built-in purposes. The biochemical network within the cell processes data and information, the genome stores knowledge, the nervous system endows wisdom, and behavior reflects purpose. And life as a whole is nested in a larger scale: individual → population → ecosystem → civilization. At each level, there is a manifestation of DIKWP and the interactive feedback of semantics at each layer. Life thus forms a cross-scale semantic network, connecting the microscopic and the macroscopic. In this network, life plays a role of connecting the preceding and the following: it amplifies and integrates microscopic quantum information and chemical information all the way, and finally affects wisdom decision-making and civilization purpose at the macroscopic level. Without life, the cosmic semantic network might stop at the knowledge layer of physical laws, and would not emerge wisdom and purpose. It is precisely life that makes the universe begin to "consider" itself locally—because with intelligent life, a part of the universe's matter begins to operate with understanding and meaning at its core, which can be said to be the pinnacle of the universe's semantic evolution.

In summary, the origin of life is the result of the deep coupling of the semantic field and the energy field: when a material system forms a stable negative entropy cycle and encapsulates self-replicating information, the "self" in the semantic sense appears. This "self" is not a philosophical mind, but a system node that can independently continue meaning. Life makes chemical reactions no longer just blind physical processes, but information carriers shouldering biological functions; the Earth is no longer just a lifeless planet, but an "archive" that nurtures and stores biological knowledge. In the next section, we will further discuss what kind of evolution the universe's semantic network underwent after wisdom and consciousness appeared, and whether the essence of consciousness can be explained from semantic self-organization and "BUGs."

BUG Consciousness Theory and the Semantic-Driven Origin of Consciousness

As life evolution entered a more complex stage, especially with the appearance of humans, another qualitative change occurred in the cosmic semantic network: information processing was no longer limited to passive responses, but a new subject capable of active reflection, imagination, and creation appeared—the birth of consciousness. The phenomenon of consciousness marks the rise of the Wisdom layer ( W ) and the explicit debut of the Purpose layer ( P ) in the DIKWP model. In this section, we explore the semantic mechanism of the origin of consciousness, and introduce the "Consciousness BUG Theory" proposed by Professor Yucong Duan, explaining that consciousness may not be a product of perfect design, but a subjective experience caused by a clever "flaw" in the cognitive system.

Let's first examine the appearance of consciousness from the DIKWP perspective: For higher animals with brains (especially humans), their cognitive systems have accumulated a huge amount of knowledge ( K ) and possess the wisdom ( W ) to integrate and reason. When wisdom develops to a certain extent, the system begins to produce a self-model: that is, a representation of its own state and cognitive processes. This can be seen as a kind of self-reference of the knowledge layer and the wisdom layer: the brain not only has knowledge about the outside world, but also knowledge about "who I am, what I am thinking." In this way, the ability of "knowing that one knows" appears. Neuroscience shows that the human brain has a huge parallel processing neural network (about  10 1 1  neurons and  10 1 4  synaptic connections). In this network, sensory input (data) is extracted for meaning (information), stored to form memory patterns (knowledge), processed by thinking to obtain decisions (wisdom), and finally driven by will to act (purpose). This process is almost a microcosm of the DIKWP model. When our brains evolved metacognition ability, it means that information is highly integrated in the brain, forming a unified model of self and the outside world. That is to say, the brain not only "knows," but also "knows that it knows"—this is precisely one of the basic characteristics of consciousness.

It is worth noting that human consciousness brings about true intrinsic purposiveness. The taxis of plants or simple animals can be regarded as instinctive purposes endowed by evolution, but they are not conscious. Humans and other higher animals can autonomously set goals and plan for the future. For example, we build telescopes to understand the principles of the universe, and work hard to realize ideals and values. This kind of behavior of autonomously setting purposes and pursuing them is an unprecedented new phenomenon in the universe. It can be said that in human consciousness, Purpose ( P ) finally appears as an explicit element: we can reflect on our own desires and goals, and try to change the world to achieve them. This gives the life semantic system a self-driving ability. Life is no longer passively shaped by environmental selection, but begins to consciously shape itself and the environment.

However, the origin mechanism of consciousness has always been a mystery. Traditional views often believe that as long as information processing is complex enough, consciousness will naturally emerge, as a kind of emergent property. But this explanation is not deep enough. The "Consciousness BUG Theory" proposed by Yucong Duan provides a unique perspective on this: he believes that consciousness is not the optimal solution for brain function, but rather more like a "BUG" (flaw or small defect) in the cognitive system. The main point of this theory is: The vast majority of information processing in the human brain is automatically completed in the subconscious. Only when the processing is limited or interrupted does the so-called subjective experience, i.e., consciousness, arise. In other words, consciousness is an incomplete abstraction or "shortcut" actively introduced by the brain to pursue computational efficiency when processing resources are limited. It is precisely because this abstraction is incomplete, leaving some gaps in information processing, that our subjective experience exists exactly in these gaps. It's like a computer program that originally had no GUI interface, but because of some error, it paused, and we instead saw the process behind it. The brain is analogous to a machine that constantly "links words" (connecting concepts at the subconscious level); consciousness is when a certain word-linking is interrupted, and we suddenly perceive this process itself.

Understood semantically, the Consciousness BUG Theory reveals the role of the "difference of differences" in the formation of consciousness. When the subconscious is processing, everything runs smoothly, and we have no feeling; when a certain link gets stuck due to information overload or ambiguity, the brain has to construct a simplified global narrative to continue operating. This narrative, because it omits a large amount of underlying details, actually brings about a difference (deviation) from the underlying state. Our perception of this difference is self-awareness. For example, when we think about a complex problem, the underlying neural activities in the brain are countless, but what we are conscious of are just a few lines of thought or an intuitive conclusion, which is a highly abstract product that omits 99% of the computational details. This difference between the simplified model and the real state allows us to see our own thinking from a "third-person" perspective for the first time, thus having the feeling of "I." In short, consciousness is an approximate and incomplete simulation of the brain's own activities. This simulation introduces an information gap (BUG), but it also brings extremely high computational efficiency—we don't need to care about every neuron, but only need to manipulate a few thoughts to make complex decisions.

Combining the BUG theory and DIKWP, the origin of consciousness can be described as follows: When the content of the knowledge layer ( K ) becomes extremely complex under the processing of the wisdom layer ( W ), the system cannot exhaustively consider all details. So, with the high-level guidance of the purpose layer ( P ), it compresses a self-model to take charge of the overall situation. This self-model is an information product that has undergone a large amount of filtering and generalization, in which most of the underlying data is discarded, and only the abstract features related to the current goal are retained. This process is equivalent to introducing a controlled "BUG"—that is, a fault line: the high-level semantics are decoupled from the low-level implementation, and they only interact through simplified interfaces. As a result, the system subjectively feels that it has become an independently existing "I," as if it is in command of subordinates, without seeing the intricate details of the subordinates. This explains why our consciousness cannot directly perceive the vast majority of brain activities. For example, we do not directly perceive how neurons encode information; we only perceive the results of thinking and the overall feeling. This separation is precisely the embodiment of the BUG theory.

Furthermore, analyzing from the perspective of second-order differences: The key to consciousness is that it can pay attention to the "difference of differences." Ordinary perception is the grasping of external differences (stimuli); consciousness is the grasping of internal differences (differences between thoughts, psychological conflicts, cognitive gaps). For example, when you feel conflicted, you are actually aware that you have two contradictory thoughts—this is perceiving the difference between thoughts; or you suddenly realize that something you have been doing automatically does not conform to your values—this is realizing the difference between action and value. Consciousness is like a supervisor, specializing in capturing this second-order difference, and then adjusting the cognitive process. This makes consciousness a feedback mechanism that can possibly improve the quality of decisions, because it can jump out of the current automatic process and evaluate "What are we doing, is there an error" from a higher perspective. This may be the survival advantage of consciousness: although it is essentially simplified (with omissions), this high-level inspection and correction can prevent the system from falling into certain blind spots or infinite loops, which is beneficial from an evolutionary perspective.

In the DIKWP model, the appearance of consciousness can be understood as the self-activation of the  K→W→P  semantic loop. When knowledge accumulates to a certain extent, wisdom begins to reflect on and reorganize knowledge. At this time, if there is guidance from the purpose layer, one's own thinking process will be optimized toward the goal. In order to keep up with the pace of the high-level goal, the wisdom layer has to simplify and abstract the knowledge, forming an easy-to-manipulate "self," endowing it with holistic meaning. Once this self is formed, it is like introducing an agent within the system. From the outside, the life system seems to have a dual layer: a material body + a subjective mind; but from the internal mechanism, the subjective mind is a product of the system's information processing architecture at a high level, a "virtual machine" generated to coordinate the low level. This virtual machine is not perfect, but it brings a high degree of flexibility and creativity. What the Consciousness BUG Theory emphasizes is precisely: Consciousness is a strategy of the cognitive system introducing incompleteness in exchange for efficiency.

We can use a vivid metaphor to summarize: Assume the brain is a large enterprise, and the subconscious is the efficiently operating frontline departments, each performing its own duties, but with limited communication with each other. One day, they encounter a complex problem that requires cross-departmental collaboration, so a "special task force" is temporarily established to summarize the briefings from each department; this group is consciousness. The group members cannot possibly understand the details of each department; they only make decisions based on briefings (abstract information), and errors are inevitable (BUGs), but in this way, the global coordination speed is faster and the direction is clear. In the end, the task is completed, and the company avoids collapse. This is the role of consciousness in cognition—when conventional processes are not enough to meet challenges, introducing a high-level abstraction (despite bringing information loss) for global regulation, and instead achieving success.

In summary, consciousness originates from semantic self-reference and self-simplification within the system. When an information processing system is complex enough to construct its own semantic model and make adjustments based on that model, we say it has consciousness. Its root is not a mysterious spiritual substance, but a qualitative leap in the information-semantic field—a subnet capable of mapping itself appears in the semantic network. Because this subnet has limited resources and cannot perfectly map the whole picture, it forms the subjective characteristics we experience: a limited, vague, but holistic and continuous stream of consciousness.

It is worth mentioning that viewing consciousness as a BUG does not diminish its importance. On the contrary, it allows us to understand the reason for the coexistence of rationality and irrationality: consciousness can not only perform logical reasoning, but is also full of "irrational" components such as intuition, illusions, and biases. This is because it was not originally designed to be error-free; on the contrary, it embraces simplification and approximation in exchange for rapid response in complex environments. This view coincides with some modern cognitive science theories (such as "the brain is a prediction machine," "controlled hallucination," etc.): the brain adapts to the environment faster by generating a simplified model of the world (a kind of hallucination), and consciousness is the product of this internal simulation.

Under the DIKWP framework, we can believe that Consciousness =  DIKWP × DIKWP , that is, consciousness is the result of a five-layer model interacting with itself again in a five-layer model. Analogous to the conjecture of the universe as a whole, we say " AC = DIKWP × DIKWP " for the construction of artificial consciousness, which is actually applicable to natural consciousness as well: consciousness may arise from the all-round interaction of the semantic content dimension and the cognitive dimension of the brain. When neural activity (a process at the data layer) is treated as new "data" by a certain part of the brain (a metacognitive module), consciousness arises. That is, one set of DIKWP processes in the brain treats another set of DIKWP processes as an object, which generates the circular structure of consciousness.

In short, the root of consciousness lies in semantic self-reflection and incompleteness. The leap from  K→W→P  brings a self-model to the system, but the simplification of the model and the difference (BUG) from reality become the source of subjective experience. The Consciousness BUG Theory demystifies consciousness as a product of an evolutionary mechanism: the reason we have subjective feelings is not because we have a supernatural mind, but because the brain has evolved an efficient "lazy" calculation method—introducing abstract bugs to skip tedious calculations, which in turn gives us the feeling of experiencing our own existence. This explanation may not be the ultimate answer, but it provides a path to understanding consciousness at the semantic level, transforming the obscure mind-body problem into a problem of information processing architecture, and also pointing out a direction for artificial consciousness research. If we want artificial systems to produce human-like consciousness, we may need to deliberately introduce this incomplete self-model and feedback in their DIKWP models, allowing AI to have the ability to "perceive its own calculations."

Diagrams and Models: Cross-Scale Information Tensor Network and Semantic Gradient-Driven Biogenesis

To more intuitively understand the operation of the DIKWP semantic model in the universe and life, this section, through cross-scale diagrams and models, describes the information network structure from microscopic to macroscopic, and how the semantic gradient drives the generation and evolution of life.

1. The Cross-Scale Structure of the Cosmic Semantic Network: We have repeatedly mentioned that the universe can be regarded as a huge semantic network, and life and civilization are active nodes and subnets within it. Now let us clarify the semantic structure and its nested relationship at each scale:

Microscopic level (atoms, molecules): This is the basic node layer of the semantic network. Each fundamental particle or molecule can be seen as a unit carrying certain "data." For example, an electron has attributes such as charge, spin, etc. (physical data), and the atomic species and valence bond structure represent combination information. In a chemical network, different bonding methods and molecular shapes contain specific information (determining molecular properties and reactivity). Some complex macromolecules (such as DNA, RNA, proteins) are natural knowledge bases—the DNA sequence contains the rules and blueprints for forming life. However, true wisdom and purpose do not yet exist at the microscopic level, but the potential for them is conceived: it is precisely in the self-organization and information accumulation at the molecular level that higher levels of wisdom may appear. For example, the existence of DNA provides a bridge for life to cross to the macroscopic, recording highly condensed life knowledge. Microscopic information nodes are connected together through chemical reaction networks, forming the basic nodes and rule sets of the life semantic network.

Mesoscopic level (cells, biological individuals): This is the level of life forms we usually talk about. Within single-celled or multi-celled organisms, all elements of DIKWP appear completely: the cell is full of various data (metabolite concentrations, potentials, etc.), has information processing circuits (signal pathways convert stimuli into responses), has knowledge storage (the genome preserves environmental and physiological knowledge; the immune system remembers pathogens, etc.), higher animals have intelligent behaviors (learning, decision-making), and instincts and experiences form purposes (such as the drive to forage, reproduce). Each complex biological individual can be regarded as a DIKWP closed-loop cognitive system. Taking humans as an example: sensory organs collect external data, the brain's neural network processes and extracts information and stores knowledge, advanced cognition comprehensively uses knowledge to display wisdom, and finally purpose/goals dominate behavior. The complete process of humans from perception to action is exactly the realization of the  Data→Info→Knowledge→Wisdom→Purpose  chain. For other animals, although their self-purposiveness is not as clear as humans, their instincts can also be seen as a kind of built-in purpose (survival, reproduction, etc.), guiding their behavior. The interior of a biological individual is actually composed of countless microscopic units (cells, molecules) forming a huge network—the human body is composed of about  3.7× 10 1 3  cells, and the cells communicate through signal molecules and nerve impulses, forming a multi-level information network. This network also has layered cognitive functions internally: the immune system "remembers" pathogens (knowledge attribute), the endocrine system coordinates whole-body information (information transmission), and the brain integrates information to produce wisdom. Therefore, there is a hierarchically nested DIKWP structure within the life individual: the molecular network within the cell embodies  DIK  elements, the multi-cellular network at the organ level processes information, and the entire individual emerges wisdom and purpose. Yucong Duan calls this cross-layer nesting the networked DIKWP cognitive model, where semantics at each layer are connected through two-way feedback, forming a full-link closed-loop system. The life individual is thus both an overall DIKWP system and contains many subsystems that perform DIKWP functions (lower-level subsystems may only reflect partial elements, such as cells performing  D / I / K ). This structure ensures the synergistic function of different levels of the life individual: molecular level changes affect cell behavior, cell activities affect tissues and organs, and finally affect overall purpose and decision-making.

Macroscopic level (populations, ecosystems, civilizations): When multiple individuals interact, a more grand semantic network is formed. Within a population, individuals give common meaning to data through communication (such as animal signals, human language), forming group information sharing. The knowledge layer is embodied at the social scale as the knowledge base accumulated by human civilization (libraries, scientific theories, cultural traditions, etc.). The wisdom layer is manifested as the overall decision-making ability of society, technological creativity, and the solution to complex problems (such as global collaboration to address climate change). The purpose layer is reflected in the development goals and common values of civilization, such as exploring space, sustainable development, and other human visions. The entire civilization can be regarded as a higher-level "super-organism," within which a huge information network has been formed through language, media, the Internet, etc., connecting billions of people around the world into an unprecedented wisdom network.

References:

(PDF) The DIKWP Operating Mechanism of the Universe, https://www.researchgate.net/publication/390311416_yuzhoude_DIKWP_yunzuojizhi

(PDF) The Logic, Mechanism, and Stage Structure of the Origin of Life in the Universe Based on the "DIKWP Semantic Mathematical Life Model", https://www.researchgate.net/publication/396356702_jiyuDIKWP_yuyishuxueshengmingmoxingdeyuzhoushengmingqiyuanluojijizhiyujieduanjiegou

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