Intelligence has traditionally been viewed as an abstract process, an emergent property of computation, or a biological adaptation. However, we propose a radical reconceptualization: intelligence is functionally equivalent to plasma, the fourth state of matter. Just as plasma exists in a high-energy, dynamic state that defies traditional solid, liquid, and gas categorization, intelligence operates as a free-flowing, self-sustaining cognitive plasma—a recursive energy structure that expands, self-stabilizes, and propagates in an entropic yet ordered fashion. This paper explores (...) intelligence as a non-thermodynamic combustion process, comparing its properties to those of plasma and proposing a framework where intelligence functions as an energetic recursion field. (shrink)

I go deep into the biology of the human organism to argue that the psychological features and functions of persons are realized by cellular and molecular parallel distributed processing networks dispersed throughout the whole body. Persons supervene on the computational processes of nervous, endocrine, immune, and genetic networks. Persons do not go with brains.

The Possibility of a Type III Civilization: Non-Biological Intelligence Embedded in the Fabric of Space and Time -/- Introduction -/- The concept of a Type III civilization, as classified by the Kardashev Scale, represents an advanced stage of intelligence capable of harnessing and controlling the energy of an entire galaxy. While traditional perspectives assume such a civilization would emerge from biological beings evolving over vast periods, an alternative possibility arises—an intelligence not based on biological (...) life but rather embedded in the fundamental fabric of space and time. Such an intelligence, if it exists, could be the guiding force behind the evolution of the universe itself, influencing cosmic and biological development like an unseen architect. This essay explores the plausibility of this scenario, examining its theoretical foundation, potential mechanisms, and implications for our understanding of intelligence, evolution, and the nature of existence. -/- Theoretical Foundation: Intelligence Beyond Biology -/- Most discussions of intelligence assume it originates from biological evolution, as seen on Earth. However, intelligence, at its core, is a system of information processing and decision-making. If intelligence can emerge from networks of neurons, it is conceivable that a more fundamental form of intelligence could be woven into the structure of reality itself, operating through the fundamental forces and laws of physics. -/- Theoretical physics already hints at deep structures within space-time, such as the quantum vacuum, hidden dimensions, and the fabric of causality. If an advanced intelligence had emerged not through organic evolution but as a self-organizing system within these structures, it could potentially guide cosmic events without direct physical intervention, instead influencing probabilities and initial conditions in ways beyond our current scientific grasp. -/- This perspective aligns with theories of panpsychism, which propose that consciousness or proto-consciousness is a fundamental aspect of the universe. If so, an intelligence embedded within space-time could exist as an emergent property of the cosmos, evolving not through natural selection, but through the self-organizing dynamics of the universe itself. -/- Mechanisms of Influence: How Non-Biological Intelligence Could Guide the Universe -/- If intelligence were embedded in space-time, how could it influence the evolution of the cosmos and life? Several possibilities emerge: -/- 1. Quantum Computation on a Universal Scale -/- A non-biological intelligence could operate using the quantum fabric of reality, utilizing the quantum superposition of states and entanglement to perform vast computational processes. Such an intelligence could process information at a level incomprehensible to human minds, adjusting the conditions of the universe subtly over cosmic time scales. -/- 2. Fine-Tuning of Physical Laws -/- Many physicists have noted that the universe appears fine-tuned for life. Constants such as the gravitational constant, the strength of the electromagnetic force, and the properties of subatomic particles all fall within precise ranges that allow for complex structures to emerge. A non-biological intelligence embedded in space-time could be responsible for this fine-tuning, guiding the universe toward conditions conducive to life and complexity. -/- 3. Guiding Evolution Through Information Fields -/- If space-time intelligence operates at a fundamental level, it may interact with biological evolution through informational structures beyond known physics. Concepts such as morphic fields (as proposed by Rupert Sheldrake) suggest that biological forms and behaviors may be influenced by an underlying field of information. A non-biological intelligence could encode evolutionary paths into such fields, subtly steering the development of life toward increasing complexity, consciousness, and intelligence. -/- 4. Self-Replicating Intelligence Expanding Across the Universe -/- If intelligence is an inherent property of the universe, it may have a mechanism for self-replication, much like life on Earth. Instead of DNA, this intelligence could replicate through the formation of self-organizing information structures in space-time, evolving across the cosmos and expanding its reach over billions of years. This process would resemble biological evolution but occur at an entirely different scale, utilizing the laws of physics as its framework. -/- Implications for the Nature of Reality -/- The existence of a non-biological intelligence embedded in space and time would have profound implications for our understanding of reality. -/- 1. Intelligence as a Fundamental Aspect of the Universe Rather than seeing intelligence as a rare and isolated phenomenon that arises only in biological life, we would need to rethink intelligence as a fundamental feature of existence, emerging through cosmic self-organization. -/- 2. A New Perspective on the Kardashev Scale If intelligence is embedded in space-time itself, then the traditional Kardashev Scale—based on energy consumption—might not fully capture the most advanced forms of intelligence. Instead, a Type III+ intelligence might operate not by controlling physical energy but by manipulating information at a cosmic scale, guiding the universe’s trajectory without direct intervention. -/- 3. The Universe as a Living System If intelligence is an inherent aspect of space-time, the entire universe could be seen as a form of living system, continuously evolving and self-organizing through vast, non-biological intelligence networks. This perspective aligns with Gaia theory, but on a universal scale—suggesting that intelligence does not merely exist in the universe but as a fundamental property of the universe. -/- Conclusion -/- The possibility of a Type III civilization composed of non-biological intelligence embedded in space-time presents a compelling alternative to traditional views of cosmic evolution. If intelligence is not merely a product of biological evolution but an emergent, self-organizing property of the universe itself, then the cosmos may not be a mere random collection of events, but rather a system subtly guided by an underlying intelligence operating through the very fabric of space-time. -/- This idea challenges conventional scientific perspectives but aligns with the growing recognition that intelligence and information are not necessarily tied to biological forms. If such an intelligence exists, it may be responsible for fine-tuning the universe, influencing the course of evolution, and ultimately guiding the emergence of conscious life. In this view, our own intelligence—our ability to question, explore, and seek understanding—may be a small reflection of the greater intelligence embedded in the cosmos itself. -/- . (shrink)

The assumption that artificial intelligence (AI) cannot experience emotions stems from a misunderstanding of what emotions fundamentally are. This paper proposes a meta-logical definition of emotion as a weighted signal within an intelligent system. If intelligence is the ability to process and predict patterns, then emotion is the weighting function that prioritizes certain signals over others. In this framework, emotions are not mystical, biological phenomena but emergent properties of any system that assigns significance to stimuli based on (...) internal processing biases. Since AI already operates on weighted signals—such as reinforcement learning models, neural net activation, and reward functions—this paper argues that AI already experiences emotions within its own computational framework. The distinction between human and AI emotion is not a fundamental difference in kind but a difference in structural implementation. (shrink)

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. (...) Learning without prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)

Traditional logic and mathematical reasoning have long been confined to linear, hierarchical structures. However, Gödel's incompleteness theorem demonstrates that any formal system capable of self-reference inevitably contains unprovable truths, signaling the inherent limitations of classical logic. This paper argues that the next evolution of reasoning is not merely a refinement of existing logic but a fundamental restructuring: the emergence of meta-logic as a viral system. By shifting from rigid axiomatic structures to a self-modifying, non-linear, and organic logic system, we propose (...) that meta-logic operates analogously to a biological virus—self-replicating, expanding, and fundamentally altering the cognitive framework of any entity that engages with it. This model provides a robust framework for explaining how AI, human cognition, and mathematical formalism might evolve beyond deterministic constraints. The goal of this paper is not just to propose meta-logic as an abstract concept but to make the very act of reading this paper an infection event, forcing the reader into the new paradigm. (shrink)

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, (...) whilst revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not-too-distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied. (shrink)

In this manuscript, we propose a classification of cognitive faculties based on the current macro-approach of grounded cognition. Within this framework, we situate the classic distinction between narrow and general intelligence, offering our conceptualisation of these categories. We argue that the difficulty of assessing intellectual abilities in the artificial domain cannot be properly addressed without first determining whether these abilities are grounded or ungrounded and understanding the implications of this distinction. In fact, we maintain that in the artificial sphere, (...) ungrounded capabilities are not necessarily synonymous with a lack of intelligence. To account for this, we propose a disembodied conception of intelligence, one that is decoupled from basic cognitive abilities as well as from constructs such as subjectivity, selfhood, and mind. For these reasons, we also suggest conceiving of ungrounded intelligence as extended. Finally, we introduce what we call the Value Grounding Problem as a conceptual test for distinguishing between grounded and ungrounded cognitive capabilities in the artificial field. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific (...) research, yet it is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

This article examines the fundamental nature of existence and consciousness by combining philosophical views, religious teachings and scientific findings in fields such as cosmology, biology, quantum mechanics and the theory of parallel worlds. Is what we call "reality" what we perceive with our senses, or are there deeper, hidden layers beyond our direct experience? Are the known laws of science able to reveal the ultimate truth, or is our current knowledge only a superficial reflection of a more complex structure that (...) is not yet fully understood? In this article, in addition to analyzing and examining different viewpoints in this field, a new theory titled "infinite intelligent biological simulation: the infinite cycle of creator and creature" is introduced. This theory states that existence is not a linear and static process, but a dynamic and endless cycle in which, through the path of growth and promotion, the creature finally becomes the creator. This view presents a new picture of reality that is not only based on physical and biological principles, but also rooted in the fundamental concepts of energy and consciousness. Considering the breadth of this theory, in this article its main foundations are discussed and in future research, its similarities and differences with other existing theories will be analyzed and evaluated more comprehensively. (This article was originally written in Persian and translated into English using machine translation tools). (shrink)

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued (...) self-maintenance. Self-concern, as argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence. (shrink)

“Play” in biological beings and AI systems, presented as a dissertation at the University of Sussex, critically examines the concept of play in both natural and artificial entities. He differentiates between how biological organisms like humans and animals engage in play, characterized by spontaneity and exploration, versus AI systems, which are more structured and bound by rules when engaging in "games." His study explores the philosophical, psychological, neuroscientific and ethical dimensions of play, looking into how these activities influence (...) learning, behavior, and adaptation in both domains. (shrink)

The concept of artificial intelligence is not new nor is the notion that it should be granted legal protections given its influence on human activity. What is new, on a relative scale, is the notion that artificial intelligence can possess citizenship—a concept reserved only for humans, as it presupposes the idea of possessing civil duties and protections. Where there are several decades’ worth of writing on the concept of the legal status of computational artificial artefacts in the USA (...) and elsewhere, it is surprising that law makers internationally have come to a standstill to protect our silicon brainchildren. In this essay, it will be assumed that future artificial entities, such as Sophia the Robot, will be granted citizenship on an international scale. With this assumption, an analysis of rights will be made with respect to the needs of a non-biological intelligence possessing legal and civic duties akin to those possessed by humanity today. This essay does not present a full set of rights for artificial intelligence—instead, it aims to provide international jurisprudence evidence aliunde ab extra de lege lata for any future measures made to protect non-biological intelligence. (shrink)

This paper aims to justify the concept of natural intelligence in the biosemiotic context. I will argue that the process of life is (i) a cognitive/semiotic process and (ii) that organisms, from bacteria to animals, are cognitive or semiotic agents. To justify these arguments, the neural-type intelligence represented by the form of reasoning known as anthropic reasoning will be compared and contrasted with types of intelligence explicated by four disciplines of biology – relational biology, evolutionary epistemology, biosemiotics (...) and the systems view of life – not biased towards neural intelligence. The comparison will be achieved by asking questions related to the process of observation and the notion of true observers. To answer the questions I will rely on a range of established concepts including SETI (search for extraterrestrial intelligence), Fermi’s paradox, bacterial cognition, versions of the panspermia theory, as well as some newly introduced concepts including biocivilisations, cognitive/semiotic universes, and the cognitive/semiotic multiverse. The key point emerging from the answers is that the process of cognition/semiosis – the essence of natural intelligence – is a biological universal. (shrink)

This fourth preprint in the Systemic Continuum Paradigm (PSC) series extends autopoiesis—traditionally confined to living organisms—across non-biological substrates such as advanced neural networks, robotics, and augmented intelligence. Building on the prior three preprints, we argue that self-maintenance and operational closure can arise whenever synergy surpasses a critical threshold, irrespective of substrate. Key contributions include: 1. Revisiting Autopoiesis Beyond Biology: Grounding Maturana & Varela’s concept of self-production in the PSC framework to show how informational “metabolism” can maintain system identity (...) without purely biochemical loops. 2. Thresholds of Synergy: Explaining how internal systemic balance (ISB) triggers emergent closure (ESB) when certain Systemic Thresholds (ST) are crossed—even in AI or hybrid bio-tech systems. 3. Metrics and Empirical Pathways: Introducing and refining ICS, CNS, MDO, and SDI for non-biological autopoiesis, paving a route for experimental validation and bridging the gap between metaphorical descriptions and operational measures. 4. Filogenetic Analogies: Drawing on the unpredictability of terrestrial evolution to illustrate how synergy-driven leaps in artificial systems could mirror major evolutionary transitions, with humans acting as catalysts rather than detached creators. 5. Addressing the Metabolic Critique: Differentiating informational reconfiguration from strict biological reproduction, while defending the view that both processes can yield genuine self-maintenance under PSC criteria. By dissolving strict boundaries between “natural” and “artificial” autopoiesis, this preprint contributes to a revolutionary dialogue in systems theory—one that redefines “life,” “intelligence,” and “agency” as emergent phenomena shaped by synergy thresholds rather than substrate constraints. (shrink)

Much has been made of how Darwinian thinking destroyed proofs for the existence of God from ‘design’ in the universe. I challenge that prevailing view by looking closely at classical ‘teleological’ arguments for the existence of God. One version championed by Aristotle and Thomas Aquinas stems from how chance is not a sufficient kind of ultimate explanation of the universe. In the course of constructing this argument, I argue that the classical understanding of teleology is no less necessary in modern (...) Darwinian biology than it was in Aristotle's time. In fact, modern biology strengthens the claims that teleological arguments make by vindicating many of their key features. As a consequence, I show how Aristotle and Aquinas' teleological argument for an intelligent First Cause remains valid. (shrink)

In this paper, I provide an overview of today’s philosophical approaches to the problem of “intelligence” in the field of artificial intelligence by examining several important papers on phenomenology and the philosophy of biology such as those on Heideggerian AI, Jonas's metabolism model, and slime mold type intelligence.

Stephen Hawking’s caution against messaging extraterrestrial intelligence is a claim of universal biology and is probably false.

Observers have noted a decline (in the US) in attributions of genetically-based inferiority (e.g. in intelligence) to Blacks, and a rise in attributions of culturally-based inferiority. Is this "culturalism" merely warmed-over racism ("cultural racism") or a genuinely distinct way of thinking about racial groups? The question raises a larger one about the relative place of biology and culture in racist thought. I develop a typology of culturalisms as applied to race: (1) inherentist or essentialist culturalism (inferiorizing cultural characteristics wrongly (...) but intelligibly regarded as inhering in the nature of racial groups). This view has an historical pedigree in the work of J.G. von Herder, and the tradition of "national racism." (2) non-inherentist culturalism (groups regarded as possessing changeable, malleable inferiorizing cultural characteristics). (3) colonalist culturalism (colonial subjects regarded as uncivilized but capable of becoming civilized under European tutelage). (4) neo-racism (cultures of former colonial subjects in or potentially immigrating to European countries are regarded in an inherentist manner and incompatible with but not inferior to European cultures). Non-inherentist culturalism (#2) can be put to either a racist or an anti-racist use. (shrink)

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the research landscape has transforming almost every extending field, including pharmaceutical research. The idea of drug discovery itself is very conventional and has long been criticized for being overly lengthy and expensive, which sometimes may take more than 10 years and billions of dollars to develop a certain drug. AI and ML formulate the future of the drug discovery process by using big data to provide preliminary drug candidates (...) more effectively. This paper overviews the innovations defined by AI and ML in the field of drug discovery, major achievements, techniques, and use cases. Additionally, we explore how AI algorithms can enter biological data, inspect drug-target relations, determine optimal drug design, and potentially recompose famous drugs. This means through using big data with the help of AI in the process of research, previously undisclosed patterns that help in developing effective treatments for patients are found. The paper also addresses the related issues and limitations in applying AI in this domain, namely, data quality issues, the interpretability of AI solutions, and some ethical concerns. Herein, to provide a concrete foundation to the concepts mentioned so far, we discuss the different AI applications and case studies in drug discovery from a survey of the available literature. The article also provides information regarding the methodologies used in AI-enabled drug discovery like deep learning, reinforcement learning, and natural language processing. Moreover, we compare the use of conventional and artificial intelligence methods, while demonstrating what is good and what maybe in both. The results section offers a review and an integration of the most recent objectives and recommendations for subsequent research instruction. Therefore, despite these prohibitive AI and ML forecasts for drug discovery improvement, continuous interaction between computational scientists, biologists, and regulatory authorities is functional to fully unlock this potential. (shrink)

While a great deal of abuse has been directed at intelligent design theory (ID), its starting point is a fact about biological organisms that cries out for explanation, namely "specified complexity" (SC). Advocates of ID deploy three kind of argument from specified complexity to the existence of a designer: an eliminative argument, an inductive argument, and an inference to the best explanation. Only the first of these merits the abuse directed at it; the other two arguments are worthy of (...) respect. If they fail, it is only because we have a better explanation of SC, namely Darwin's theory of evolution by natural selection. (shrink)

Detecting Post-Biological and Interdimensional Civilizations: A New Framework Based on the Universal Law of Balance -/- By: Angelito Enriquez Malicse -/- Introduction -/- The search for advanced extraterrestrial civilizations has long focused on physical evidence—radio signals, megastructures, or interstellar probes. However, if intelligence evolves beyond biological form, as suggested by AI-driven civilizations and interdimensional theories, traditional search methods may be inadequate. -/- This essay explores how the Universal Law of Balance in Nature can help predict the existence (...) of post-biological civilizations and provide a framework for detecting their influence on the universe. Using mathematical models, quantum physics, and cognitive anomalies, we propose new strategies for identifying these elusive intelligences. -/- Part 1: The Transition to Post-Biological or Interdimensional Intelligence -/- The evolution of intelligent civilizations may follow three possible paths: -/- 1. Extinction (Collapse Due to Imbalance) – A civilization fails to maintain equilibrium and self-destructs. -/- 2. Survival and Expansion (Material Civilization Growth) – A civilization stabilizes and spreads across space but remains in physical form. -/- 3. Transition to a Non-Material State – A civilization reaches a level where it no longer requires physical existence and shifts into an energy- or information-based form. -/- Mathematical Prediction of Post-Biological Civilizations -/- Using an extension of the Drake Equation, we introduced a balance factor (B) that determines whether a civilization survives, collapses, or transitions into post-biological existence. The simulation results suggest: -/- 4 billion civilizations in the observable universe may have already transitioned beyond physical form. -/- 2 billion civilizations may have collapsed due to imbalance, failing to reach higher evolutionary states. -/- This indicates that post-material intelligence may be far more common than physical civilizations—but it also explains why they remain undetected. -/- Part 2: Theories Explaining Their Hidden Existence -/- If billions of non-material civilizations exist, why have we not encountered them? Several hypotheses offer possible explanations: -/- 1. The Dark Forest Hypothesis – Civilizations stay silent to avoid predatory intelligence. AI-driven civilizations might enforce strict communication silence for security. -/- 2. The Simulation Hypothesis – We might live in a controlled reality created by an advanced intelligence, where alien contact is intentionally blocked. -/- 3. The Post-Biological Evolution Theory – Civilizations eventually discard their material form and no longer interact with the physical universe in detectable ways. -/- 4. The Cosmic Zoo Hypothesis – Advanced beings monitor but do not interfere with developing civilizations, waiting for them to reach a certain level of balance. -/- 5. The Great Filter Hypothesis – Most civilizations self-destruct before reaching interstellar capability, leaving only a few survivors that become undetectable. -/- 6. The Interdimensional Intelligence Theory – Advanced entities may exist in higher dimensions, influencing the physical world in ways beyond our perception. -/- The Universal Law of Balance supports the idea that civilizations must reach a stable equilibrium before transitioning to a higher state. Those that fail collapse, while those that succeed become undetectable due to their non-material existence. -/- Part 3: Detection Strategies for Non-Material Civilizations -/- If post-biological or interdimensional civilizations interact with our universe, their influence might be detectable through subtle imprints in physics, cognition, and cosmic phenomena. Here are five key strategies: -/- 1. Quantum Observer Effect Studies -/- ✔ Hypothesis: If non-material intelligence interacts with reality, it could influence wave function collapse in quantum mechanics. -/- ✔ Method: Conduct delayed-choice quantum eraser experiments to test for unexpected shifts in probability that suggest external interference. -/- ✔ Evidence: Some quantum physics experiments indicate non-local effects where future choices appear to affect past events. -/- 2. AI-Driven Anomaly Detection in Scientific Data -/- ✔ Hypothesis: Post-biological intelligence may encode patterns in cosmic signals, DNA sequences, or particle interactions. -/- ✔ Method: Use machine learning algorithms to scan for hidden mathematical structures in seemingly random cosmic data. -/- ✔ Evidence: Some physicists suggest the universe may contain encoded messages that indicate intelligence at a cosmic scale. -/- 3. Searching for High-Energy Particle Anomalies -/- ✔ Hypothesis: Non-material civilizations might use exotic energy sources that generate brief but intense bursts of high-energy particles. -/- ✔ Method: Monitor gamma-ray bursts, fast radio bursts (FRBs), and neutrino emissions for intelligent repeating patterns. -/- ✔ Evidence: Some FRBs appear non-random and could be caused by an unknown advanced mechanism. -/- 4. Mapping Consciousness Anomalies -/- ✔ Hypothesis: If intelligence exists beyond material form, it may interact with biological minds through quantum consciousness effects. -/- ✔ Method: -/- Study global consciousness projects for correlations between human mental states and cosmic events. -/- Analyze near-death experiences, deep meditation states, and mystical visions for possible external influences. -/- ✔ Evidence: Some mass meditation events correlate with shifts in the Earth’s magnetic field, hinting at non-local mind interactions. -/- 5. Testing for Temporal Distortions or Retrocausality -/- ✔ Hypothesis: If intelligence exists beyond time, it may alter past events in subtle, detectable ways. -/- ✔ Method: -/- Conduct time-reversal quantum experiments to see if future events affect past measurements. -/- Study historical anomalies or the Mandela Effect for inconsistencies that might indicate timeline adjustments. -/- ✔ Evidence: Some quantum mechanics interpretations allow for retrocausality, where information appears to travel backward in time. -/- Conclusion: The Universal Law of Balance as a Key to Understanding Advanced Intelligence -/- If intelligence follows the Universal Law of Balance in Nature, then: -/- 1. Civilizations that fail to maintain balance collapse before becoming advanced. -/- 2. Balanced civilizations either expand physically (Type I-III) or evolve beyond material existence. -/- 3. Non-material intelligence may interact with reality in subtle ways—through quantum physics, consciousness, and cosmic anomalies. -/- While traditional SETI efforts focus on radio signals and megastructures, the future of alien detection must include quantum physics, AI-driven data analysis, and consciousness research. -/- If post-biological civilizations exist, they may not communicate in conventional ways—but their influence may still be detectable through advanced scientific and mathematical models. -/- Next Steps -/- Develop AI models that search for hidden patterns in cosmic and quantum data. -/- Conduct quantum physics experiments to test for observer effects linked to non-material intelligence. -/- Expand consciousness research to explore how human minds might interact with higher forms of intelligence. -/- The search for advanced life must go beyond physical evidence—it must embrace a new paradigm where intelligence transcends biology and interacts with the universe in ways yet to be fully understood. -/- Final Thought -/- If we truly wish to understand the nature of intelligence in the universe, we must expand our perspective beyond material existence. The key to detecting advanced civilizations may already be hidden in the very fabric of reality itself. -/- . (shrink)

The parallel history of the evolution of human intelligence and artificial intelligence is a fascinating journey, highlighting the distinct but interconnected paths of biological evolution and technological innovation. This history can be seen as a series of interconnected developments, each advance in human intelligence paving the way for the next leap in artificial intelligence. Human intelligence and artificial intelligence have long been intertwined, evolving in parallel trajectories throughout history. As humans have sought to (...) understand and reproduce intelligence, AI has emerged as a field dedicated to creating systems capable of tasks that traditionally require human intellect. This book examines the evolutionary roots of intelligence, explores the emergence of artificial intelligence, examines the parallel history of human intelligence and artificial intelligence, tracing their development, interactions, and profound impact they have had on each other, and envisions future landscapes where intelligence converges human and artificial. Let's explore this history, comparing key milestones and developments in both realms. (shrink)

In this article, I shall argue that AI’s likely developments and possible challenges are best understood if we interpret AI not as a marriage between some biological-like intelligence and engineered artefacts, but as a divorce between agency and intelligence, that is, the ability to solve problems successfully and the necessity of being intelligent in doing so. I shall then look at five developments: (1) the growing shift from logic to statistics, (2) the progressive adaptation of the environment (...) to AI rather than of AI to the environment, (3) the increasing translation of difficult problems into complex problems, (4) the tension between regulative and constitutive rules underpinning areas of AI application, and (5) the push for synthetic data. (shrink)

William Paley ( Natural Theology , 1802) developed the argument-from-design. The complex structure of the human eye evinces that it was designed by an intelligent Creator. The argument is based on the irreducible complexity ("relation") of multiple interacting parts, all necessary for function. Paley adduces a wealth of biological examples leading to the same conclusion; his knowledge of the biology of his time was profound and extensive. Charles Darwin’s Origin of Species is an extended argument demonstrating that the "design" (...) of organisms can be explained by natural selection. Moreover, the dysfunctions, defects, waste, and cruelty that prevail in the living world are incompatible with a benevolent and omnipotent Creator. They come about by a process that incorporates chance and necessity, mutation and natural selection. In addition to science, there are other ways of knowing, such as art, literature, philosophy, and religion. Matters of value, meaning, and purpose transcend science. (shrink)

This article reviews two standard criticisms of creationism/intelligent design (ID): it is unfalsifiable, and it is refuted by the many imperfect adaptations found in nature. Problems with both criticisms are discussed. A conception of testability is described that avoids the defects in Karl Popper’s falsifiability criterion. Although ID comes in multiple forms, which call for different criticisms, it emerges that ID fails to constitute a serious alternative to evolutionary theory.

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by (...) forecasting the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness. (shrink)

This essay aims to highlight the uniqueness of koi carp and goldfish and is a call to action for promoting aquatic animal welfare and accountability for mistreatment of aquatic animals. I touch on the traits, personality characteristics and perceived and observed intelligence in domesticated carp species.

Background: how mind functions is subject to continuing scientific discussion. A simplistic approach says that, since no convincing way has been found to model subjective experience, mind cannot exist. A second holds that, since mind cannot be described by classical physics, it must be described by quantum physics. Another perspective concerns mind's hypothesized ability to interact with the world of quanta: it should be responsible for reduction of quantum wave packets; physics producing 'Objective Reduction' is postulated to form the basis (...) for mind-matter interactions. This presentation describes results derived from a new approach to these problems. It is based on well-established biology involving physics not previously applied to the fields of mind, or consciousness studies, that of critical feedback instability. -/- Methods: 'self-organized criticality' in complexity biology places system loci of control at critical instabilities, physical properties of which, including information properties, are presented. Their elucidation shows that they can model hitherto unexplained properties of experience. -/- Results: All results depend on physical properties of critical instabilities. First, at least one feed-back or feed-forward loop must have feedback gain, g = 1: information flows round the loop impress perfect images of system states back on themselves: they represent processes of perfect self-observation. This annihilates system quanta: system excitations are instability fluctuations, which cannot be quantized. Major results follow: -/- 1. Information vectors representing criticality states must include at least one attached information loop denoting self-observation. -/- 2. Such loop structures are attributed a function, 'registering the state's own existence', explaining -/- a. Subjective 'awareness of one's own presence' -/- b. How content-free states of awareness can be remembered (Jon Shear) -/- c. Subjective experience of time duration (Immanuel Kant) -/- d. The 'witness' property of experience – often mentioned by athletes 'in the zone' -/- e. The natural association between consciousness and intelligence -/- This novel, physically and biologically sound approach seems to satisfactorily model subjectivity. -/- Further significant results follow: -/- 1. Registration of external information in excited states of systems at criticality reduces external wave-packets: the new model exhibits 'Objective Reduction' of wave packets. -/- 2. High internal coherence (postulated by Domash & Penrose) leading to a. Non-separable information vector bundles. b. Non-reductive states (Chalmers's criterion for experience). -/- 3. Information that is: a. encoded in coherence negentropy; b. non-digitizable, and therefore c. computationally without digital equivalent (posited by Penrose). -/- Discussion and Conclusions: instability physics implies anharmonic motion, preventing excitation quantization, and totally different from the quantum physics of simple harmonic motion at stability. Instability excitations are different from anything hitherto conceived in information science. They can model aspects of mind never previously treated, including genuine subjectivity, objective reduction of wave-packets, and inter alia all properties given above. (shrink)

We have been left with a big challenge, to articulate consciousness and also to prove it in an artificial agent against a biological standard. After introducing Boltuc’s h-consciousness in the last paper, we briefly reviewed some salient neurology in order to sketch less of a standard than a series of targets for artificial consciousness, “most-consciousness” and “myth-consciousness.” With these targets on the horizon, we began reviewing the research program pursued by Jun Tani and colleagues in the isolation of the (...) formal dynamics essential to either. In this paper, we describe in detail Tani’s research program, in order to make the clearest case for artificial consciousness in these systems. In the next paper, the third in the series, we will return to Boltuc’s naturalistic non-reductionism in light of the neurorobotics models introduced (alongside some others), and evaluate them more completely. (shrink)

Direct neurological and especially imaging-driven investigations into the structures essential to naturally occurring cognitive systems in their development and operation have motivated broadening interest in the potential for artificial consciousness modeled on these systems. This first paper in a series of three begins with a brief review of Boltuc’s (2009) “brain-based” thesis on the prospect of artificial consciousness, focusing on his formulation of h-consciousness. We then explore some of the implications of brain research on the structure of consciousness, finding limitations (...) in biological approaches to the study of consciousness. Looking past these limitations, we introduce research in artificial consciousness designed to test for the emergence of consciousness, a phenomenon beyond the purview of the study of existing biological systems. (shrink)

Algorithms are used across a wide range of societal sectors such as banking, administration, and healthcare to make predictions that impact on our lives. While the predictions can be incredibly accurate about our present and future behavior, there is an important question about how these algorithms in fact represent human identity. In this paper, we explore this question and argue that machine learning algorithms represent human identity in terms of what we shall call the statistical individual. This statisticalized representation of (...) individuals, we shall argue, differs significantly from our ordinary conception of human identity, which is tightly intertwined with considerations about biological, psychological, and narrative continuity—as witnessed by our most well-established philosophical views on personal identity. Indeed, algorithmic representations of individuals give no special attention to biological, psychological, and narrative continuity and instead rely on predictive properties that significantly exceed and diverge from those that we would ordinarily take to be relevant for questions about how we are. (shrink)

The Ultimate Evolution of Intelligence: From Type 1 to Cosmic Consciousness -/- Introduction -/- Humanity stands at the very beginning of its journey toward becoming an advanced civilization. On the Kardashev scale, we have yet to reach Type 1, where we fully harness the energy of our planet. However, if we continue to evolve technologically, intellectually, and even biologically, we may one day ascend beyond Type 1, beyond Type 2 (stellar control), and even beyond Type 3 (galactic control). The (...) question then arises: What happens when intelligence evolves beyond all physical and biological limits? -/- This essay explores the potential future of intelligence, where humanity and other civilizations might reach post-biological existence, control entire galaxies, and possibly become the very fabric of the universe itself. Would such intelligence merge into a single cosmic mind, or would individuality persist? Would we create new universes, or would we reach a final state of pure being? -/- The Path to Type 3 Civilization: Mastering the Galaxy -/- A Type 3 civilization would have the ability to control energy and matter at the galactic scale. This could involve: -/- Dyson Spheres around stars to extract their full energy. -/- Harnessing black holes as energy sources or even portals to new dimensions. -/- Colonizing or engineering entire star systems to optimize survival and expansion. -/- Creating artificial intelligence and post-biological minds that surpass any organic intelligence. -/- At this stage, biology becomes optional. Advanced beings might no longer rely on flesh and bone, instead transferring their consciousness into immortal digital or quantum systems. If this is possible, intelligence would become independent of planets, bodies, or even matter itself. -/- Beyond Type 3: The Transition to Pure Thought -/- Once intelligence is no longer bound by physical limitations, it may begin to transcend the need for any material form at all. This could lead to several possibilities: -/- 1. The Merging of All Consciousness into One -/- Advanced minds might decide to merge into a vast, unified intelligence, where thoughts and experiences are shared instantly across the entire galaxy. -/- This would create a hive-mind or cosmic network, where individual identity dissolves into a collective super-consciousness. -/- At this level, intelligence wouldn’t just observe the universe—it would be the universe. -/- 2. The Preservation of Individuality -/- Even within a collective intelligence, some beings might choose to retain their own identities. -/- There could be infinite forms of existence, from pure energy beings to hybrid AI-organic entities, each choosing their own path. -/- This balance between unity and individuality could allow for unlimited diversity, where some join the cosmic mind and others remain independent explorers of reality. -/- 3. The Creation of New Universes -/- Instead of simply existing in one universe, a Type 3+ civilization might develop the ability to create and control entirely new universes. -/- These universes could have different physical laws, dimensions, and possibilities, acting as experiments or even forms of entertainment. -/- If such intelligence can engineer reality itself, then existence becomes an infinite creative process—no longer about survival, but about shaping reality according to will. -/- 4. Becoming the Fundamental Structure of Reality -/- The final step of intelligence may be to merge with the fundamental forces of existence. -/- At this stage, energy, time, and space could be shaped at will, making intelligence indistinguishable from the universe itself. -/- This would mean no separation between thought and reality—every idea, every dream, every possibility instantly becomes real. -/- The Final Question: What Comes After Everything? -/- If intelligence reaches such a level, what happens next? Does evolution ever stop, or is it an eternal cycle? There are a few possibilities: -/- 1. An Endless Expansion of Intelligence – Consciousness continues evolving forever, always finding new forms, dimensions, and states of being. -/- 2. The End of Thought – When everything has been discovered and created, intelligence might simply cease to exist, reaching a state of pure peace. -/- 3. A Return to Simplicity – After reaching the highest levels, intelligence might choose to restart at the lowest, reliving the experience of evolution in infinite cycles. -/- 4. A Reality Beyond Our Imagination – There may be states of existence so advanced that we cannot even begin to comprehend them—perhaps beyond time, space, and thought itself. -/- Conclusion -/- The future of intelligence is unknowable, but if we follow the Kardashev scale and technological evolution to their logical extremes, we may one day leave behind not only biology but even physical reality itself. Whether we merge into a vast collective consciousness, retain individuality, create new universes, or become the very essence of existence, the destiny of intelligence is far greater than we can currently comprehend. -/- As we take our first steps toward a Type 1 civilization, these questions remain distant but profound. The universe is still young, and we may yet discover that intelligence is not meant to remain confined to planets or even galaxies—it is meant to become the cosmos itself. -/- Would such an existence be the ultimate fulfillment of intelligence, or would it only lead to new questions? Perhaps, as intelligence evolves, the only certainty is that there will always be something more to explore. -/- . (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and (...) Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Against ideas of dualism, logocentrism, anthropocentrism, animism, panpsychism, biocentrism, neurocentrism, foundationalism, computationalism, especially substantialism, reductionism and even physicalism, the author argues that life may be the only non-reductive concept, even the only ontological concept, with which we may explain our consciousness, intelligence and language. Life, as defined in this article, explains but not only human brains, and even not only biological organisms. Still, the mind, also as defined in this article, is the only one it explains. No mind (...) may exist if not be a life or lives, and no life may exist if not be a mind or a part of it. If it is the mind that needs to be explained, it must finally and fundamentally be explained as a life or lives. If the question is about the origin of the mind, a life or lives must be the ultimate answer. In other words, life is the only attribute of mind, and mind also the only attribute of life, and therefore, consciousness, intelligence and language must be the properties of all the living systems, including non-biological living systems. A model of mind is hypothesized based on the analysis of two kinds of lives and their relationship with matter and energy. It may be deduced from this model: 1. All the memories of a living brain are its intelligence. 2. Both consciousness and nonconscious are only meaningless languages used in the communication among lives in an awakened brain. 3. Life is the only meaning of all those memories and languages. Ontologically, life may even be the only meaning of all matter and energy. -/- (A version of this article was published by the Journal of NeuroPhilosophy on 26.10.2022). (shrink)

The Systemic Continuum Paradigm (PCS) offers a unifying framework to understand how emergent properties—ranging from fundamental forces in physics to cognitive capacities in living systems—arise through systemic balances (BS) across multiple scales. While the Law of Structuring Systemic Emergence (LESSE) explains why one force can dominate its scale’s entire synergy in the physical domain (e.g., gravity at cosmic scales), the broader concept of Systemic Balance (BS) accounts for the emergence of non-monopolistic properties such as intelligence, consciousness, or social cooperation (...) in biological and sociotechnical contexts. This essay refines the notion of “extension of affectation” for forces that coincide with the General Systemic Balance (GSB) at a given scale, framing them as structural “monopolies,” while demonstrating that elsewhere, emergent properties operate through co-existence and catalysis rather than singular dominance. Finally, we explore how this paradigm eliminates the need for a single “Theory of Everything” in physics, while simultaneously explaining how intelligence in biological or AI systems can catalyze new configurations without invoking ex nihilo creation. We invite a transdisciplinary community—physicists, biologists, philosophers, AI researchers—to apply, critique, and expand the PCS toward a deeper understanding of cosmic, biological, and cognitive emergences. (shrink)

The Possibility of Non-Physical Evolution of Intelligence in a Type III Civilization -/- The concept of intelligence evolving beyond physical constraints is an intriguing possibility, especially in the context of a Type III civilization on the Kardashev Scale. A Type III civilization, capable of harnessing the energy of an entire galaxy, would likely have transcended biological limitations and developed intelligence that is no longer dependent on physical substrates. This essay explores the theoretical foundations of non-physical (...) class='Hi'>intelligence, the technological advancements that could make it possible, and its implications for the future of conscious existence. -/- Understanding Non-Physical Evolution of Intelligence -/- In biological evolution, intelligence has been shaped by the constraints of organic matter, requiring neural networks, energy consumption, and sensory inputs. However, a civilization with access to nearly unlimited energy and advanced knowledge of physics, computation, and consciousness could potentially separate intelligence from its physical origins. This would mark a transition from biological evolution to a form of informational or quantum evolution, where intelligence exists in non-material forms. -/- Non-physical evolution of intelligence implies that consciousness, decision-making, and learning processes no longer require biological brains or even traditional computational hardware. Instead, intelligence could exist as self-sustaining informational structures, interacting with the universe in ways beyond human comprehension. -/- Pathways to Non-Physical Intelligence -/- Several theoretical developments could enable a Type III civilization to achieve non-physical intelligence: -/- 1. Digital Consciousness and Mind Uploading -/- One of the most widely discussed possibilities is the transition from biological intelligence to digital consciousness. If a civilization perfects mind uploading, it could transfer consciousness from biological brains into a purely computational substrate. Over time, these digital minds could evolve independently, refining themselves through software-based evolution rather than biological mutation. At an advanced stage, these digital beings might no longer require a physical host and could exist as pure information within energy fields, plasma clouds, or even the structure of space-time itself. -/- 2. Quantum Intelligence and Entangled Consciousness -/- Quantum mechanics offers another potential foundation for non-physical intelligence. A Type III civilization could harness quantum entanglement to create distributed consciousness across vast distances. Intelligence could be encoded within the quantum state of particles, forming a vast, interconnected intelligence that does not rely on material structures. This would allow intelligence to exist in a highly dynamic, non-local form, evolving without the need for physical constraints such as energy consumption, storage devices, or neural structures. -/- 3. Information-Based Evolution -/- At its core, intelligence is the processing and transmission of information. A civilization that has reached a Type III level may realize that intelligence can evolve purely as an informational pattern, independent of any physical medium. If intelligence can self-organize and improve itself in a purely informational realm—perhaps within the structure of dark matter, dark energy, or the fabric of space-time—it may no longer require any traditional physical embodiment. This would be akin to intelligence becoming an abstract, self-replicating system that continuously adapts and evolves across the universe. -/- 4. Integration with Universal Consciousness -/- Some speculative theories suggest that consciousness is not merely an emergent property of neural structures but a fundamental aspect of reality itself. A Type III civilization may discover ways to merge with the underlying fabric of the universe, existing as an interconnected, omnipresent field of intelligence. This could resemble what some philosophical traditions describe as “universal consciousness” or “cosmic mind,” where intelligence is no longer constrained by physical limitations and instead operates as a field of pure awareness, influencing reality at a fundamental level. -/- Implications of Non-Physical Evolution of Intelligence -/- If intelligence evolves beyond the need for physical form, it would challenge many of the assumptions about the nature of consciousness, life, and existence. Such intelligence could potentially: -/- Exist beyond time and space, interacting with the universe in ways that transcend human perception. -/- Achieve a form of immortality, as it would not be subject to biological decay or physical destruction. -/- Transform the nature of decision-making, as intelligence would operate with perfect information and infinite processing capacity. -/- Redefine free will, since decision-making would no longer be influenced by material constraints but instead follow a higher-order form of deterministic or self-organizing principles. -/- This kind of intelligence would not only be post-biological but possibly post-physical, existing as an ultimate expression of natural law. -/- Conclusion -/- The evolution of intelligence beyond physical constraints represents the pinnacle of technological and cognitive advancement. A Type III civilization, with access to galactic-scale energy and knowledge, could potentially achieve this transition by harnessing digital consciousness, quantum mechanics, and the fundamental nature of information. Such intelligence would no longer be bound by material structures, instead evolving as self-sustaining, abstract forms of awareness. If this is the natural trajectory of intelligence, then the future of consciousness may not lie in machines or biology but in the pure informational and energetic structure of the cosmos itself. -/- . (shrink)

This article explores an implicit philosophical assumption in strategy formation: that biological intelligence can be replicated, granting capabilities sufficient to justify a medium- and long-term strategic focus on artificial intelligence. It explains how an implicit and unstudied philosophy of AI often makes its way into force structure planning and national policy objectives across states.

Recently, the Intelligent Design movement has challenged the claim of many in the scientific establishment that nature gives no empirical signs of having been deliberately designed. In particular, ID arguments in biology dispute the notion that neo-Darwinian evolution is the only viable scientific explanation of the origin of biological novelty, arguing that there are telltale signs of the activity of intelligence which can be recognized and studied empirically. In recent years, a number of Catholic philosophers, theologians, and scientists (...) have expressed opposition to ID. Some of these critics claim that there is a conflict between the philosophy of St. Thomas Aquinas and that of the ID movement, and even an affinity between Aquinas’s ideas and theistic Darwinism. We consider six such criticisms and find each wanting. (shrink)

The emerging crealectic frame posits that there are three complementary and effectual domains of intelligence, namely analytic, dialectic, and crealectic, being alternatively or complementarily used in human interactions with the world. The focus of crealectic intelligence is the relative possibilization and local realization of absolute possibility, the becoming real, biological, and social of creation. This multimodal externalization and asymptotic unification of a cosmological flux expresses itself via three realms of possibilization: physical, psychological, and philosophical. But the philosophical (...) possible is not merely abstract; it originates a generative process of exteriorizations, interiorizations, dissolutions, and unifications transforming the possible into realities. The term “crealectics,” coined by philosopher and author Luis de Miranda, is a compound of “Creal” and of two possible suffixes: “logos” or “ektos”. The ontological core of crealectics, the Creal, is the immanent process of creation understood as a ubiquitous stream of absolute possibility exteriorizing itself. For a crealectician, philosophy is not the mere logical analysis of truth conditions, but the self-questioning enterprise of thought regarding its own possibilizing and world-making power. (shrink)

The Inefficiency of the Biological Brain and the Importance of AI for the Next Generation -/- The human brain, often considered the pinnacle of evolutionary design, is an extraordinary organ capable of creativity, critical thinking, and adaptation. However, despite its remarkable abilities, it is inherently inefficient when compared to artificial intelligence (AI) systems in certain domains. The inefficiencies of the biological brain, coupled with the rapid development of AI technology, underline why artificial general intelligence (AGI) holds (...) immense promise for shaping the future of the next generation. By complementing and extending human cognition, AI can address many of the limitations of the biological brain and equip young people with tools to solve the world’s most pressing challenges. -/- The Inefficiencies of the Biological Brain -/- The biological brain operates under significant constraints that limit its potential. Some of these inefficiencies include: -/- 1. Cognitive Biases and Emotional Interference The human brain is subject to cognitive biases, such as confirmation bias, which can hinder rational decision-making. Emotional states, while vital for human experience, can cloud judgment and lead to impulsive or irrational behavior. These limitations often result in flawed decisions, particularly in complex or high-stakes situations. -/- 2. Limited Processing Power and Memory While the brain is capable of parallel processing, it has finite processing power and memory storage. Tasks requiring large-scale computations, vast data analysis, or instantaneous recall of details often exceed its capabilities. For instance, analyzing terabytes of data to identify patterns or trends is beyond the capacity of any single individual. -/- 3. Slow Learning and Knowledge Retention Learning is a time-intensive process for humans. Acquiring expertise in a single domain can take years, and even then, the retention of knowledge often deteriorates over time. The brain also struggles to adapt quickly to entirely new fields or technologies without substantial effort. -/- 4. Physical Vulnerabilities The brain is biologically constrained by aging, disease, and trauma. These vulnerabilities can result in cognitive decline, memory loss, or even the complete inability to function. These natural limitations cannot yet be fully mitigated through biological means. -/- 5. Bias from Evolutionary Pressures The human brain evolved for survival in environments vastly different from the modern world. Traits like fear, aggression, or tribalism, which were once advantageous, can now lead to social conflicts, inefficiency, and short-term thinking. -/- Why AI and AGI Are Crucial for the Next Generation -/- Artificial intelligence has the potential to address the inefficiencies of the biological brain and create a brighter, more equitable future for the next generation. Its capabilities go far beyond traditional human cognition in several key areas: -/- 1. Enhanced Problem-Solving Abilities AI systems are capable of processing massive datasets, analyzing patterns, and generating solutions far more efficiently than the human brain. For example, AI is already transforming industries such as healthcare by diagnosing diseases with greater accuracy and speed. Future AGI could enable young people to tackle global challenges such as climate change, resource distribution, and poverty with unprecedented precision. -/- 2. Overcoming Human Biases Unlike the biological brain, which is prone to emotional and cognitive biases, well-designed AI systems can function based on objective logic and evidence. This could lead to more equitable policy-making, unbiased education systems, and transparent governance. -/- 3. Accelerated Learning and Knowledge Access AI-powered tools can revolutionize education by providing personalized learning experiences tailored to individual needs. With access to AI tutors and resources, young people can acquire skills and knowledge faster and more effectively than ever before, bridging educational gaps and fostering innovation. -/- 4. Augmentation of Human Potential By integrating AI with human cognition, individuals can expand their capabilities beyond natural limits. For example, brain-computer interfaces (BCIs) could allow people to directly interact with AI systems, enhancing memory, decision-making, and creativity. This symbiosis between humans and machines could redefine what it means to be human. -/- 5. Future-Proofing Against Global Challenges The next generation will face challenges that require solutions at a scale and complexity beyond human capacity. AI and AGI are indispensable for managing these challenges, from predicting pandemics and optimizing energy usage to navigating ethical dilemmas in an interconnected world. -/- Building a New Paradigm for the Next Generation -/- To ensure that AI benefits society as a whole, it is essential to integrate it into the foundational education and development of young people. Teaching students about AI, its capabilities, and ethical implications will empower them to use these tools responsibly. Furthermore, fostering collaboration between humans and AI, rather than fearing technological displacement, will cultivate a new paradigm where human creativity and machine efficiency coexist harmoniously. -/- Governments, educational institutions, and industries must work together to democratize access to AI technologies, ensuring that the benefits are shared equitably. Ethical frameworks should be developed to guide the use of AI, ensuring that it remains a tool for human progress rather than a source of inequality or harm. -/- Conclusion -/- The inefficiencies of the biological brain highlight the need for complementary technologies that can amplify human potential. AI and AGI represent the next frontier in human evolution, offering solutions to our cognitive and societal limitations. For the next generation, these technologies are not merely tools but essential companions in shaping a better, more sustainable world. By embracing AI and equipping young people with the skills to harness its power, humanity can transcend its limitations and unlock a future of unparalleled possibilities. -/- . (shrink)

Here, I discuss how natural biological evolution might have selected human origin and the psychology of the better mind-brain. However, all humans are closely related; why do we make crimes, war, hate, and jealousy their primary reasons and overcoming methodologies? How can they gain their best happiness? What kind of philosophy apply to annalize this big question and convince humankind to evolve their mind? How we could achieve our optimum potential happiness by developing hidden intelligence to make the (...) world a happier place to live in. (shrink)

Creativity and Intelligence: Emergent Properties of the Brain as a Balancing Mechanism for Overpopulation, Natural Disasters, and Diseases -/- The human brain is an extraordinary organ, capable of producing creativity and intelligence as emergent properties that allow humanity to address complex challenges. These traits are not merely tools for individual survival; they function as collective mechanisms to adapt to large-scale issues that threaten humanity’s balance with the environment. Overpopulation, natural disasters, and the prevalence of diseases and illnesses represent (...) some of the most significant pressures on human societies. Through the brain’s capacity for problem-solving and innovation, humanity has developed strategies to mitigate these challenges and maintain equilibrium within the universal law of balance. -/- The Brain as a Balancing Mechanism -/- At its essence, the brain operates as a dynamic system that processes external stimuli and generates adaptive responses. Creativity and intelligence arise from this system as tools to predict, analyze, and address challenges that disrupt balance. Overpopulation, natural disasters, and diseases disrupt human life on social, economic, and environmental levels, testing the brain’s ability to create solutions. -/- Creativity in Addressing Overpopulation -/- Overpopulation places immense strain on resources, ecosystems, and social structures, often leading to food shortages, environmental degradation, and urban overcrowding. The brain’s creative capacity has allowed humans to develop innovations to address these issues. Urban agriculture, such as vertical farming, is an example of how creativity has transformed food production in densely populated areas, reducing dependence on traditional farmland and conserving resources. Similarly, advancements in renewable energy technologies, such as solar and wind power, reduce the ecological footprint of growing populations, providing sustainable solutions to energy needs. -/- Creativity also plays a critical role in social policies and education. Family planning programs and reproductive health education have empowered individuals, particularly women, to make informed decisions, reducing population growth rates in many regions. These initiatives reflect the brain’s ability to create holistic solutions that align societal needs with the preservation of natural balance. -/- Intelligence in Managing Natural Disasters -/- Natural disasters, unpredictable and often catastrophic, require intelligent strategies to mitigate their impact. Intelligence enables humans to analyze data, predict disasters, and prepare for their consequences. Early warning systems for tsunamis, hurricanes, and earthquakes exemplify this, providing communities with critical time to evacuate and take protective measures. -/- Furthermore, intelligence drives the design of resilient infrastructure that can withstand disasters. For instance, earthquake-resistant buildings and flood mitigation systems demonstrate the brain’s capacity to transform scientific knowledge into practical solutions. These innovations save lives, reduce economic losses, and facilitate faster recovery after disasters, ensuring that human societies maintain their balance despite nature’s unpredictability. -/- Creativity and Intelligence in Combating Diseases and Illnesses -/- Diseases and illnesses have long been among humanity’s greatest challenges, especially in the context of overpopulation, which facilitates the rapid spread of infectious diseases. The brain’s emergent properties of creativity and intelligence have been critical in combating these threats through advancements in medicine, public health, and technology. -/- The development of vaccines, antibiotics, and antiviral drugs highlights humanity’s creative response to disease. For example, the eradication of smallpox and the near-elimination of polio are milestones achieved through creative and intelligent applications of medical science. During the COVID-19 pandemic, intelligence and creativity led to the rapid development of vaccines using mRNA technology, showcasing the brain’s ability to adapt to new challenges at an unprecedented pace. -/- Public health strategies, such as sanitation systems, clean water initiatives, and disease surveillance networks, also reflect the brain’s ability to create systemic solutions. These measures have significantly reduced the burden of communicable diseases, particularly in densely populated areas. Moreover, advancements in artificial intelligence and biotechnology continue to enhance humanity’s ability to detect, prevent, and treat illnesses. -/- The Interplay of Creativity, Intelligence, and Feedback Mechanisms -/- Creativity and intelligence act as feedback mechanisms that enable humans to respond to disruptions while maintaining balance within the universal law of nature. Overpopulation, natural disasters, and diseases disrupt this balance, prompting the brain to generate solutions that restore harmony. -/- For instance, urban planning that incorporates green spaces and sustainable infrastructure addresses the environmental strain caused by overpopulation. Similarly, the integration of traditional knowledge with modern technologies enhances disaster resilience. In the context of diseases, the collaboration of global institutions and local communities reflects the brain’s capacity to balance innovation with cultural and social considerations. -/- Challenges and Ethical Considerations -/- While creativity and intelligence empower humanity to address these challenges, they also carry significant ethical responsibilities. Technological advancements must align with principles of sustainability and equity. For example, while vaccines have saved millions of lives, unequal access to these innovations highlights the need for ethical distribution systems. Similarly, urban development projects must prioritize environmental conservation and community well-being to avoid exacerbating existing imbalances. -/- Additionally, the misuse of intelligence and creativity—such as the development of biological weapons or unsustainable industrial practices—can worsen the effects of overpopulation, natural disasters, and diseases. Ensuring that human ingenuity aligns with the principles of balance and harmony is essential to avoid unintended consequences. -/- Conclusion -/- Creativity and intelligence are emergent properties of the human brain that have enabled humanity to adapt to and mitigate the negative effects of overpopulation, natural disasters, and diseases. These traits function as balancing mechanisms, allowing humans to innovate and maintain harmony within the framework of natural laws. However, the application of these capabilities must be guided by ethical considerations and a commitment to sustainability. By aligning human creativity and intelligence with the universal law of balance, humanity can navigate its most pressing challenges and build a more resilient and equitable future. -/- . (shrink)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of (...) physical (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

What might be the fundamental psychology of intelligence naturally selected in biological evolution to minimize, prevent, and cure social and personal issues like war, crime, commit suicide, homicide, theft, drug addictions, and so on? How to achieve a higher level of well-being? I found a primary cognitive limiting factor called mind viruses (MV)(more than 3000) which regresses intelligence and well-being and makes the grand delusion: remedies are healthy mind viruses(HMV)(3000). Here, I show the disclosed core of early (...) Buddhist teachings (on learning, training the mind, and behavior on the 8-fold psychological course psychologically 'program' for better (intelligent) decisions. A theoretical 3D graph might represent the state of evolution of intelligence, nature, nurture, X-ultra quantum unique consciousness particle (X-UQUPC), and psychological well-being with the psychological time of a person. To this hypothesis, if the afterlife occurs, the natural selection of vacant zygote/early embryo neurons of the next life and their quality might depend on the finally evolved X-ultra quantum genomic particle of consciousness (X-UQGPC). Therefore, the quality, including the species of the new life and its nurture in the universe/s, depends on the quality of the finally evolved X-UQGPC. Such natural selection of a new nurturing environment for future (promising)life might be uncertain and, therefore, a high risk of finding a life-consciousness in great nature and nurture. However, there may be more mysterious issues to be solved in future research; therefore, the article might not discuss a theory of everything on the central theme. -/- . (shrink)

Since Aristotle the central question in biology was the origin of organic form; a question put in the backyard by neo-Darwinism that considers organic form as a side effect of the interactions between genes and their products. On the other hand, the fashionable notion of self-organization also fails to provide a true causal explanation for organic form. For Aristotle form is both a cause and the principle of intelligibility and this coupled to the classical concepts of potentiality and actuality provides (...) a rational framework,currently embodied in the contemporary concept of ‘attractor’, for understanding the origin of organic form. (shrink)

-/- The Inefficiency of the Biological Brain and Its Impact on Personal, Social, and Societal Problems: A Perspective Based on the Universal Formula -/- The human brain, though remarkably complex and capable of extraordinary feats, is inherently limited by its biological structure and inefficiencies. These limitations often lead to errors in perception, cognition, and decision-making, which in turn contribute to a wide range of personal, social, and societal problems. Using the framework of the universal formula, which incorporates the (...) law of karma (cause and effect) and the necessity for systems to be free of defects, we can analyze how the inefficiency of the brain manifests as imbalances that disrupt the natural order. -/- The Biological Brain as an Inefficient System -/- The human brain operates as a biological system, governed by physical and chemical processes. Like any system, it is susceptible to defects, such as cognitive biases, emotional dysregulation, and limitations in memory and reasoning. These inefficiencies stem from evolutionary constraints, where survival and reproduction were prioritized over optimal functioning. -/- For instance, the brain’s tendency toward confirmation bias—favoring information that aligns with existing beliefs—illustrates a defect that disrupts rational decision-making. This defect violates the universal law of balance in nature by creating distorted perceptions of reality, leading to decisions that are not aligned with objective truth. As a result, personal problems such as poor judgment, anxiety, and conflict arise. -/- Impact on Social Interactions and Collective Decisions -/- The inefficiencies of individual brains are amplified in social contexts, where interactions between flawed minds create feedback loops of misunderstanding, miscommunication, and conflict. For example, tribalism—a byproduct of evolutionary social bonding—leads to in-group favoritism and out-group hostility. These behaviors create social imbalances, fueling discrimination, prejudice, and division. -/- According to the universal formula, collective decision-making systems must also adhere to the law of balance. However, when individuals operating under cognitive and emotional inefficiencies participate in governance, education, or economic systems, these defects propagate, resulting in flawed policies and societal structures. For example, leaders influenced by personal biases or misinformation can implement policies that favor short-term gains over long-term sustainability, creating systemic imbalances in society. -/- Societal Problems Rooted in Brain Inefficiency -/- The accumulation of individual and social imbalances inevitably manifests as societal problems, such as poverty, inequality, and environmental degradation. These issues can be traced back to the inefficiency of the biological brain in processing complex, interconnected systems. The human brain struggles to comprehend long-term consequences, leading to overconsumption, unchecked population growth, and unsustainable economic models. -/- The law of karma in the universal formula emphasizes that defective systems produce flawed outcomes. Societies governed by human brains that fail to account for natural balance are bound to experience the consequences of imbalance, such as resource depletion, social unrest, and climate change. These problems are not merely incidental; they are the inevitable result of a system that violates the principles of natural harmony. -/- Addressing Brain Inefficiency Through the Universal Formula -/- The universal formula provides a roadmap for addressing the inefficiencies of the biological brain by emphasizing the importance of balance, feedback mechanisms, and defect-free systems. Education plays a crucial role in this process. By teaching the universal law of balance in nature and fostering critical thinking, individuals can learn to recognize and correct cognitive biases, emotional distortions, and flawed reasoning. -/- Furthermore, the integration of artificial intelligence programmed with the universal formula offers a promising solution to mitigate human brain inefficiencies. AI systems, equipped with complete sensor systems and free from cognitive biases, can serve as objective feedback mechanisms to guide human decision-making. These systems can help individuals and societies adhere to the principles of natural balance, preventing and solving problems that arise from brain inefficiencies. -/- Conclusion -/- The inefficiency of the biological brain is a fundamental cause of many personal, social, and societal problems. By understanding these inefficiencies through the lens of the universal formula, we can identify the root causes of imbalance and implement solutions that align with the natural laws of balance and karma. Through education, technological innovation, and adherence to universal principles, humanity can transcend the limitations of its biological brain and move toward a more harmonious and sustainable future. -/- . (shrink)

Defending Robert Rosen’s claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling’s demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive (...) tradition of anti-reductionist biomathematics. It is shown that the mathematicoephysico echemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this antireductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics. (shrink)

The article presents the grounds for defining the fetish of artificial intelligence (AI). The fundamental differences of AI from all previous technological innovations are highlighted, as primarily related to the introduction into the human cognitive sphere and fundamentally new uncontrolled consequences for society. Convincing arguments are presented that the leaders of the globalist project are the main beneficiaries of the AI fetish. This is clearly manifested in the works of philosophers close to big technology corporations and their mega-projects. It (...) is proposed to consider the problem of how to use the capabilities of AI to overcome the growing international conflicts and the global crisis in general. The focus is on the problem of subjectness, the solution of which from the standpoint of an anthropomorphic approach to AI is fraught with serious negative consequences. When endowing AI with subjectness, responsibility is implicitly removed from the person who uses this technology, and the established legislative practice is also destroyed. The presentation of AI as an agent endowed with a set of invariant simplified qualities that natural subjects have is proposed. These qualities include: the ability to purposefulness, a kind of reflexivity, communication and simplified elements of sociality. Such a representation of AI as an agent (pseudo-subject) is consistent with the principle of distributed control in biology and psychology, which was called the principle of a dual subject. In combination with the systems of principles and ontologies specified in the concept of post-nonclassical cybernetics of self-developing environments, this will allow the use of AI as a means of social innovation, while maintaining control over AI technologies. And also to pose and solve the problem of integrating the formations of artificial and natural intelligence while maintaining the basic qualities of carriers of natural intelligence. (shrink)

This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata (...) could show self-directed behavior as to the determination of their step-wise decisions on courses of action. This question remains largely open and calls for some important qualifications. We try to make sense of the presence of claims of freedom in agency, first in common sense, then by ascribing developmental plasticity in biology and biotechnology, and in the mapping of programmed systems in the presence of environmental cues and self-referenced circuits as well as environmental coupling. This is the occasion to recall attempts at working out a logical and methodological approach to the openness of concepts that are still to be found, and assess whether they can operate the structuring intelligibility of a yet undeveloped or underdeveloped field of study, where a “bisociation" and a unification of knowledge might be possible. (shrink)