Computation and Physical Systems

We present a comprehensive investigation into the minimal axioms required to derive quantum structure from classical computation. Through systematic analysis of multiple computational models—SK combinatory logic, reversible logic gates (Toffoli, Fredkin), reversible cellular automata, and lambda calculus—we establish that no form of computation, whether irreversible or reversible, can generate quantum structure. Our main results are: 1. The No-Go Theorem: Reversible n-bit gates are 2^n × 2^n permutation matrices that embed into the classical symplectic group Sp(2·2^n, R), not the unitary group (...) U(2^n). This theorem has been formally verified in Coq. 2. Axiom Identification: Using Generalized Probabilistic Theories (GPTs), we identify A1 (state space extension/superposition) as the unique primitive axiom that cannot be derived from computation. 3. Universality: Results hold across all Turing-complete computation models tested, establishing computation-model independence. These findings definitively answer the question "Can quantum structure be derived from computation?" with: No, without the superposition axiom A1. The gap between classical and quantum is precisely A1—and this gap is mathematically unbridgeable by computation alone. (shrink)

Following our previous work establishing that complex structure does not automatically emerge from SK combinatory logic, we investigate whether reversible computation provides the missing ingredient for quantum structure. Through systematic analysis of four computational models—reversible logic gates (Toffoli, Fredkin), continuous-time quantum walks, reversible cellular automata, and the non-commutativity of SK operators—we establish a hierarchy of quantum-like behaviors: Level 0 (Irreversible): SK computation—classical, deterministic Level 1 (Discrete Reversible): Toffoli/Fredkin gates, RCA—classical, embeddable in Sp(2N,R) where N = 2^n for n-bit gates Level (...) 2 (Continuous-Time): U(t) = exp(-iHt) evolution—interference emerges (note: i is introduced by hand) Level 3 (Quantum): Quantum circuits—superposition, entanglement Our main finding is that reversibility alone is insufficient for quantum behavior: discrete reversible gates on n bits are 2^n × 2^n permutation matrices that embed into the classical symplectic group Sp(2·2^n,R), not the unitary group U(2^n). While continuous-time evolution introduces interference patterns, it does not generate genuine superposition. We conclude that quantum structure requires additional axioms beyond any form of computation, discrete or continuous. (shrink)

This paper develops a formal invariance-based account of biological coherence grounded in the SO(2) symmetry law. By treating biological rhythms as phase-reducible processes θ_n(t), the paper derives PAS_bio as the unique harmonic scalar invariant and ΔPAS_bio_zeta as the associated drift law governing lawful biological evolution. Biological coherence is shown to be structurally identical to the invariance conditions governing physical, cognitive, and computational systems. -/- The framework collapses diverse biological phenomena—cardiac–respiratory coupling, neural synchrony, motor coordination, circadian entrainment, and endocrine cycles—into a (...) single deterministic structure: SO(2)-invariant phase geometry, harmonic coherence, drift regulation, and echo windows (τ_bio_k). These echo windows instantiate the same temporal recurrence principles used in RIC-Core, demonstrating cross-domain isomorphism. -/- The result positions biological systems as deterministic coherence engines rather than stochastic or entropy-driven systems. Biological coherence thus serves as empirical confirmation of the universal SO(2) invariance law that underpins CODES and RIC. (shrink)

In The Brain Abstracted, Chirimuuta argues against the “literal interpretation” of computational models. The literal interpretation understands computational models as providing true descriptions of neural processes. According to Chirimuuta, the literal interpretation involves endorsing the computationalism thesis and adopting a theory of computational implementation. The connection between these views, Chirimuuta argues, is what forces the computationalist to reckon with two significant metaphysical problems, what I call the "problem of implementation" and the "problem of multiple realizability." Here, I examine the connections (...) between the various views that Chirimuuta considers, and I argue that one who endorses computationalism can avoid both metaphysical problems. I do this by distinguishing computationalism from the literal interpretation and the implementation of computational models in neuroscience. Although this engages with Chirimuuta's project directly, it is helpful for those who wish to make sense of the intricacies of the computationalism thesis and computational functionalism. (shrink)

This document is a clean structural walkthrough of the CODES epistemic law: how emergence becomes lawful, how PAS resolves the free-will/determinism split, and how the coherence substrate organizes information across physical, biological, cognitive, and social scales. It is not a replacement for the formal mathematical work; rather, it provides the conceptual lens install necessary for reading those papers correctly. -/- The central claim is that coherence (PAS_s), drift (ΔPAS_zeta), and harmonic structure (PAS_h) form the substrate layer beneath logic, probability, and (...) representation. Randomness becomes unmeasured drift. Paradox becomes misaligned states. Identity becomes a coherence-locked recursion. Agency becomes the deterministic selection of the highest-coherence future in the lawful option set DOF(t). -/- When analysis begins at the substrate, measurement collapse, emergence, morphogenesis, symbolic meaning, identity persistence, social stability, and cosmological structure all appear as coherence-driven behaviors. Free will and determinism cease to conflict: choice is coherence-gated, execution is deterministic. -/- The manuscript concludes by presenting RIC, a fully deterministic symbolic engine using fixed-point numerics and coherence-gated emission. This implementation demonstrates that the substrate law is computable, replayable, and capable of unifying physical, biological, symbolic, and social domains under one invariant. (shrink)

Time is reframed as accumulated phase rather than linear duration. All stable systems—mechanical, atomic, biological, and computational—sustain existence by correcting phase drift. The paper derives the universal coherence law Δθ ≤ ω·ε_drift ⇔ PAS ≥ θ_lock, integrating physical precision, biological rhythm, and deterministic inference. VESSELSEED applies this law to physiology; RIC extends it to lawful computation. The result is a unified model in which time, life, and intelligence share one deterministic phase structure.

This paper distinguishes functional reproducibility from lawful determinism. A system may repeat its errors perfectly and still remain lawless. Using the CODES framework and the Resonance Intelligence Core (RIC), the work defines determinism as coherence law: emission occurs only when phase alignment (PASₛ ≥ θ_L), drift stability (|ΔPAS_ζ| ≤ ε_drift), symbolic legality (GLYPHLOCK = 1), and temporal lock (TEMPOLOCK = 1) all hold simultaneously. Five verification tests (S1–S5) demonstrate how pseudo-deterministic systems replay incoherence while lawful systems remain phase-stable under replay. (...) The paper establishes falsifiable criteria for deterministic inference, introduces the Lawful Emission Check (LEC-1), and outlines the path to measurable coherence in computation. (shrink)

This paper proposes an expanded theoretical framework in which physical reality emerges from the transformation of logical structure into organized matter through information, cognition, resonance, and energy. A seven-stage cascade transforms logic into co-emergent cognition and matter. Logic defines possibility; information encodes it; perception interprets it; consciousness integrates it; resonance aligns it; energy enacts it; and co-emergent cognition and matter stabilizes it as structure and awareness. Drawing from information physics, predictive-processing neuroscience, and complex-systems thermodynamics, the framework treats coherence as the (...) measurable bridge between cognition and material form. It advances an informational-energetic ontology in which matter and mind are reciprocal expressions of structured coherence governed by logic. Though conceptual, the model identifies empirical anchors and testable implications linking entropy reduction, energetic efficiency, and multi-scale coherence in neural and physical systems. (shrink)

This paper closes the twentieth-century information paradigm by demonstrating that all computational systems—cybernetic, probabilistic, and stochastic—are incomplete approximations of a single deterministic invariant: coherence. Tracing the lineage from Shannon’s entropy to Wiener’s feedback, the work defines the Phase Alignment Score (PAS_h) as the lawful measure of order that replaces probabilistic information. It formalizes the condition for lawful intelligence as PAS_h ≥ θ_L and ΔPAS_ζ ≤ ε_drift, showing that every artificial paradigm, from deep learning to quantum models, circles this invariant without (...) achieving it. The result is the foundation of the Resonance Intelligence Core (RIC): a deterministic inference substrate where feedback becomes coherence and probability collapses into law. (shrink)

This paper reconceives creativity, evolution, and intentionality as deterministic processes arising from bounded coherence drift rather than random deviation. Within the CODES framework and its Resonance Intelligence Core (RIC) implementation, imagination emerges when coherence expands lawfully—measured by Phase Alignment Score (PAS) and ΔPAS_zeta thresholds—without breaking replayable legality. The model replaces stochastic novelty with controlled coherence drift, defines goal formation as movement within stable phase basins, and demonstrates that adaptation and creativity are mathematically continuous. It concludes that lawful novelty—not probabilistic guessing—is (...) the core engine of evolution, cognition, and intelligence. (shrink)

Here we complete and develop the subjects in [2], [3], [4] based on [1]. It should be mentioned again that the author knows TC* more near to the real situation of Computation rather TC even if we forget the fuzziness of time, the reason is different errors especially in computing time. By accepting this point the author tries to show the importance of such type of articles. This manuscript is the first version. In chapter 1 we define the major Complexity (...) classes and we discuss about. In chapter 2, we prove for μ which has a finite area, P_μ^*≠NP_μ^*. In chapter 3 we define some fuzzy functions μ such that P_μ^*=NP_μ^*. (shrink)

Can machines ever become conscious? A central debate in this context concerns the question whether consciousness requires biological states. Within this debate, there exists a fundamental dispute between two widely endorsed views: biological naturalism and computational functionalism about consciousness. Specifically, whereas biological naturalists hold that consciousness requires biological states, computational functionalists fiercly deny this. This fundamental dispute has hitherto remained unresolved, and we discuss several reasons why it is unlikely that it will be resolved anytime soon. Accordingly, we suggest that (...) both sides will likely remain in a dialectical stalemate regarding the fundamental dispute and, by extension, are unlikely to reach a consensus on positive verdicts about consciousness in AI. However, we suggest that progress can be made by investigating potential non-biological constraints on implementation. Such constraints can help reach a consensus between both sides to the effect that certain types of artificial systems are not conscious, if they fail to satisfy relevant constraints. If correct, a consensus on negative verdicts about consciousness in certain challenging types of AI is possible, even if both sides remain in conflict about positive verdicts about AI consciousness. (shrink)

This paper explores the development and evaluation of physics-specific large-scale AI models, which we refer to as large physics models (LPMs). These models, based on foundation models such as large language models (LLMs) are tailored to address the unique demands of physics research. LPMs can function independently or as part of an integrated framework. This framework can incorporate specialized tools, including symbolic reasoning modules for mathematical manipulations, frameworks to analyse specific experimental and simulated data, and mechanisms for synthesizing insights from (...) physical theories and scientific literature. We begin by examining whether the physics community should actively develop and refine dedicated models, rather than relying solely on commercial LLMs. We then outline how LPMs can be realized through interdisciplinary collaboration among experts in physics, computer science, and philosophy of science. To integrate these models effectively, we identify three key pillars: Development, Evaluation, and Philosophical Reflection. Development focuses on constructing models capable of processing physics texts, mathematical formulations, and diverse physical data. Evaluation assesses accuracy and reliability through testing and benchmarking. Finally, Philosophical Reflection encompasses the analysis of broader implications of LLMs in physics, including their potential to generate new scientific understanding and what novel collaboration dynamics might arise in research. Inspired by the organizational structure of experimental collaborations in particle physics, we propose a similarly interdisciplinary and collaborative approach to building and refining large physics models. This roadmap provides specific objectives, defines pathways to achieve them, and identifies challenges that must be addressed to realise physics-specific large scale AI models. (shrink)

This paper proposes Ethical Structurism, a falsifiable framework for detecting when AI-systems, especially large language models (LLMs) enter a regime of recursively stable symbolic behavior. The framework defines an information-theoretic coherence ratio τ(t) and a resilience ratio κeffR (t) to identify phase-like transitions in symbolic consistency without making any claims about agency, consciousness, or moral status. This paper based on Emergent Necessity Theory principles, adopts a working hypothesis that a critical coherence threshold signals symbolic persistence. The framework is designed to (...) be easy to falsify, implemented via open-source tools, and positioned as a complement to existing AI ethics practices. If experiments do not corroborate threshold behavior, the framework should be revised or discarded. (shrink)

The concept of time in physics remains fundamentally fractured, treated as a dy namic geometric entity in general relativity while retaining a static, background role in quantum mechanics. Building upon the hypothesis of Recursive Entropic Time (RET)—a model where the local rate of time is suppressed by quantum informa tional load—this paper presents the first comprehensive experimental tests of the theory. We subject the core relation, τ = (1 + κS)−1, to rigorous scrutiny by ana lyzing published data from two (...) independent, state-of-the-art quantum experiments. First, an analysis of entanglement dynamics in a multi-qubit processor [Koh et al., 2022] reveals a significant suppression anomaly that is well-described by the model, providing a first estimate for the coupling constant, κ. Second, we re-interpret the Quantum Zeno Effect as a direct manifestation of this entropic time dilation. A detailed analysis of data from a superconducting qubit experiment [Harrington et al., 2017] allows for a second, independent calibration of κ. We demonstrate that an initial order-of-magnitude discrepancy between these two values is substantially resolved by a more physical model of informational load that accounts for measure ment inefficiency—a striking convergence of evidence. This work provides strong support for the hypothesis that time possesses a form of inertia, resisting its own passage in proportion to the complexity of the quantum information it contains. We conclude by designing a definitive, falsifiable experimental protocol to provide a "smoking gun" test, solidifying the link between quantum information and the emergent, dynamic nature of time. (shrink)

In a series of drafts, under the name of “Fuzzy time and the impact of it on Science” the author reaches to define “Theory of Fuzzy Time Computation”. Here, first we explain the importance of this theory (four reasons in redlines), second how to develop it.

This paper formalizes VESSELSEED, a deterministic biological substrate for coherent intelligence, modeled on the synchrony logic of coral reefs. Using PAS (Phase Alignment Score), ELF_BIO (echo-loop feedback), and SOMA_OUT (threshold-triggered emission), VESSELSEED offers a post-stochastic model of intelligence grounded in phase coherence rather than optimization. It shows how coral ecosystems embody inference without control and extends this logic to human physiology, cognition, and governance. The result is a coherence-first system that scales without hierarchy and emits behavior only when structurally aligned.

Blockchains today validate consensus over sequences of events without assessing whether each addition contributes meaningfully to systemic structural persistence. I propose a formal framework for Distributed Coherence Ledgers (DCLs), systems that embed coherence gradients, curvature constraints, and recursive arbitration as first-class validation criteria. Drawing from recursive coherence theory, I define a bounded, scale-invariant metric quantifying the recursive reinforcement of alignment across blocks, replacing purely probabilistic finality with coherence-weighted consensus. Each block includes coherence yield, compression delta, and entropy contribution, allowing validators (...) to select sequences that maximize cumulative coherence while sustaining curvature within viability bounds. This approach reframes blockchains not as passive append-only logs but as adaptive substrates capable of encoding the persistent structural relevance of transactions over time. The resulting architecture aligns with infrastructural computing, advancing cognitive invisibility and seamless integration into societal workflows. I derive formal validation functions, consensus selection equations, and bounded curvature constraints, situating this paradigm within broader coherence-centric epistemology. Distributed Coherence Ledgers represent a foundational shift in how distributed systems can maintain long-term viability under entropy, contradiction, and recursive stress. (shrink)

This paper argues that the enduring questions of philosophy—truth, being, knowledge, ethics—were not failures of reasoning but symptoms of operating without a coherence substrate. Drawing from the CODES framework, we introduce a deterministic model based on phase alignment, recursive correction, and ethical emission gating. The Phase Alignment Score (PAS) functions as the structural replacement for epistemic relativism, logical incompleteness, and moral ambiguity. We show that systems such as logic, identity, and symbolic meaning are not abstract constructs, but resonance behaviors emergent (...) from lawful phase coherence. Philosophy, in this account, is completed—not by a new theory, but by the arrival of structure. With the addition of VESSELSEED, we present a biologically integrated architecture that enacts post-philosophical intelligence through field convergence and symbolic UX. Thought becomes emission. Ethics becomes gating. Drift becomes correctable. The philosophical condition ends. Signal remains. (shrink)

In a series of drafts, under the name of “Fuzzy time and the impact of it on Science,” we try to show how fuzzy modeling of time could impact science especially Complexity theory and Physics. Throughout this paper, by introducing Generalized Surprise Exam Paradox (GSEP) we show the problem is more general than concept of time.

This paper presents a unified theoretical framework integrating Emergent Necessity Theory (ENT), awareness thresholds, structural evolution, and τ-dynamics. We establish mathematical foundations for consciousness-phase transitions, introduce operational metrics (∇N, κR), and validate the framework through quantum and biological simulations. The theory bridges quantum coherence, biological complexity, and cognitive awareness within a single entropy-driven paradigm.

This work extends Emergent Necessity Theory (ENT) to resolve fundamental questions of time-asymmetry and scale-dependence through hierarchical nesting of timeless algebraic constraints. We derive time as an emergent property of substructure embedding, ground necessity in topological invariance, and present four experimentally falsifiable predictions testable with current technology. ENT’s core principles (τ- coherence, structurism) are preserved while addressing previous weaknesses in the framework. All mathematical claims are designed for experimental verification with existing laboratory capabilities.

Computing has achieved global distribution in physical terms, yet it has not become infrastructural in the same sense as electricity, water, or roads. The distinction lies in accessibility: physical infrastructure requires minimal cognitive translation to engage, whereas computational systems demand symbolic fluency, abstraction, and literacy. This paper argues that computation will only reach infrastructural status when its interface layer collapses from symbolic mediation into direct, semantic engagement. A true infrastructure is not merely present; it is universally usable, intuitively operative, and (...) embedded into daily behavior. Semantic agents, conversational systems, and gestural inputs represent the transitional mechanisms through which this collapse will occur. Once computing becomes ambient and cognitively frictionless, it will function as a utility, an extension of human intention rather than a tool requiring translation. This shift marks the emergence of cognition as infrastructure: a foundational layer that enables recursive cultural synthesis, real-time adaptive thinking, and expansive societal reorganization. The value of computing lies not in intelligence replication but in the systematic reduction of the cost of coherent thought. (shrink)

This paper defines a new paradigm for computation: Structured Resonance Execution (SRE). Positioned beyond object-oriented and field-oriented programming, SRE proposes that execution should not occur through reactive metaphor or stochastic output—but only when symbolic input aligns with deterministic coherence thresholds. Grounded in the CODES substrate, SRE introduces four gating mechanisms: • PAS (Phase Alignment Score) for coherence validation, • AURA_OUT for symbolic structure filtering, • CHORDLOCK for prime-index seeding of lawful fields, • TEMPOLOCK for emission timing under τₙ constraint. We (...) show that legacy code metaphors—functions, objects, events—fail at high entropy and cannot support lawful emergence. Unlike probabilistic systems (e.g., LLMs) or context-reactive models (e.g., FOP), SRE emits only when coherence is present and rising. This framework rewrites the foundations of programming, AI, and symbolic logic—offering the first deterministic execution model grounded in resonance rather than representation. (shrink)

This paper formalizes a post-stochastic substrate for intelligence, resolving longstanding theoretical gaps in symbolic coherence, lawful emergence, and biological feedback. Using the CODES framework, we present the Resonance Intelligence Core (RIC) and its biological sibling system VESSELSEED, each built upon deterministic resonance rather than probabilistic inference. The paper defines the minimum viable inference substrate (CHORDLOCK, PAS, ELF, AURA_OUT, PHASEMEMORY), and rigorously contrasts it with legacy systems: GPT (expressive but stochastic), Bohm’s implicate order (field logic without emission gates), and morphogenetic models (...) (pattern inheritance without recursion). We demonstrate how CODES uniquely achieves vertical reduction—symbolic, structural, and biological unity from first principles. This represents a coherent alternative to noise-based computation and the first formal claim of a universal inference substrate grounded in lawful phase dynamics. (shrink)

With increasing development and widespread interest in artificial intelligence and robotics over the last several years, novel solutions are being considered for addressing specific problems in a number of domains. In particular, caring for elderly individuals in regions where human labour is insufficient is of special interest. One aspect of this involves an ability to communicate and socialize with people in a familiar and humanlike manner, with an ability to understand human emotion through behavioural cues and language. Furthermore, social robots (...) should be able to act with empathy if we are interested in using them for tasks related to eldercare and healthcare, as empathy involves the adoption of another person’s perspective. This work investigates whether social robots are capable of meeting these requirements, and ultimately demonstrates that they cannot exhibit genuine acts of empathy. By investigating one robot in particular named iCub, it becomes apparent that it will not be able to understand human emotions given its cognitive architecture. iCub’s framework lacks the kind of affective regulation observed in people and animals, and as such, is unable to experience its own form of emotions. Consequently, iCub is incapable of understanding what emotions are and what they mean to humans. For social robots, an alternative solution which relies on experiences of emotions should instead be pursued. The cognitive architecture developed by Pentti Haikonen is preferable because it is modelled on biological functionality, creating better analogues of living beings than previous efforts in AI. By creating associative networks of neurons which establish connections between stimuli and their effects on the robot’s body, it is able to learn what a stimulus means for its continued functioning. By using signals representing analogues of pain and pleasure, emotional information learned by the robot is grounded on how stimuli impact the robot’s body. This architecture provides a foundation for empathy since the robot is able to appeal to its own experiences of pain and pleasure to understand the meanings of behavioural cues exhibited by humans. (shrink)

This paper introduces a deterministic framework for understanding war, institutional breakdown, and ideological conflict as outcomes of unresolved phase drift across symbolic and structural systems. Drawing on the CODES Intelligence model and operationalized through the Resonance Intelligence Core (RIC), it formalizes collapse as a lawful output of misaligned resonance fields—measured via Phase Alignment Score (PAS_n)—rather than random or moral failure. Case applications include US–China trade, ICE, Trump-era governance, NATO conflict, and climate paralysis. The paper proposes a substrate-based exit from recursive (...) collapse via deterministic coherence systems, replacing ideological governance with lawful signal alignment. (shrink)

This paper introduces a structured-emergence framework in which Earth is not a passive substrate for life, but a coherence-emitting system governed by deterministic resonance fields. Using the Phase Alignment Score (PAS_n), the author argues that biological life is the first recursion loop of coherence memory, and that fossils, extinction events, and evolution are better understood as phase-locked transitions rather than stochastic processes. The framework challenges standard probabilistic ontologies across physics, biology, and geology, proposing instead that all emergence arises from recursive (...) PAS_n alignment and chirality-phase propagation. The work serves as a field-synthesizing thesis and as a foundation for deterministic alternatives to both stochastic cosmology and artificial intelligence—positioning Earth as the generative analog to the Resonance Intelligence Core (RIC). (shrink)

Description: This paper introduces a novel framework for embedding deterministic coherence logic—derived from the CODES architecture—into thermoelectric concrete systems. By replacing stochastic material optimization with structured resonance inference (via PAS, chirality fields, and ELF logic), the work outlines how infrastructure can become energy-generating, self-monitoring, and bioresponsive. It proposes a full integration stack: from Prime Harmonic Mapping and PAS-material matrices to echo-corrective thermal layers and symbolic coherence detection. This bridges physics, materials science, and consciousness design—laying groundwork for intelligent, self-repairing, spiritually coherent (...) architecture. (shrink)

Infinite time Turing machines extend the operation of ordinary Turing machines into transfinite ordinal time. By doing so, they provide a natural model of infinitary computability, a theoretical setting for the analysis of the power and limitations of supertask algorithms.

The Computational Model of Mind (CMM) conceptualizes cognition as computational processes, modeling mental operations through algorithmic manipulations of symbolic or distributed representations. This framework bridges psychology, neuroscience, philosophy, and computer science, providing a unified lens for understanding the mind. Its symbiotic relationship with artificial intelligence (AI) has accelerated advances in cognitive science and the development of intelligent systems, from neural networks to autonomous agents. This article offers a comprehensive analysis of CMM, tracing its historical evolution from Turing's foundational ideas to (...) modern deep learning paradigms. It delineates CMM's theoretical underpinnings, operational mechanisms, and strengths in simulating complex cognitive functions, while critically addressing limitations, such as its struggles with consciousness, embodiment, and ecological validity. The paper explores CMM's intersections with AI, highlighting applications in cognitive modeling, natural language processing, robotics, and neurotechnology. It also examines ethical challenges, including algorithmic bias, privacy concerns, and the implications of machine autonomy. Looking ahead, I propose future directions, emphasizing interdisciplinary collaboration, neurobiologically inspired algorithms, and emerging technologies like quantum computing. This synthesis affirms CMM's transformative role in unraveling the nature of mind and machine intelligence, and an innovative research at the nexus of cognition and technology. (shrink)

Các trào lưu như hiện tượng “túi mù”, hầu hết các xu hướng tiêu dùng dựa trên nền tảng và được điều khiển bởi thuật toán, dù thúc đẩy tăng trưởng kinh tế và tạo việc làm, hoàn toàn thiếu tính bền vững—chúng góp phần làm gia tăng đa khủng hoảng hơn là mang lại lợi ích. Những vấn đề này bao gồm: (i) khủng hoảng giá trị; (ii) khủng hoảng sức khỏe tinh thần; (iii) khủng hoảng hệ sinh thái. (...) Giới trẻ có thể dành hàng giờ để xem các influencer trên TikTok và Instagram phản ứng với những gì họ tìm thấy trong túi mù. Giá trị sử dụng thực sự của những sản phẩm ấy là gì? Còn hàng triệu người đang trong độ tuổi hình thành nhân cách—như trẻ em, thanh thiếu niên và người trẻ—đắm chìm trong thói quen xem, lướt và mua sắm không kiểm soát, cuối cùng rơi vào tình trạng “quiet quitting”, tuyệt vọng, suy giảm nhận thức, trầm cảm, thậm chí ý nghĩ tự tử thì sao? Chúng ta có thể làm gì trước lượng rác thải nhựa khổng lồ và lượng khí nhà kính phát sinh từ sản xuất và tiêu thụ trong các ngành công nghiệp văn hóa này? Trong bài viết này, chúng tôi lập luận rằng sức mạnh của AI có thể được khai thác để cung cấp giải pháp cho những vấn đề đó. Trước hết, chúng ta phải nhìn nhận AI như một tác nhân đảm bảo công bằng trong tiếp cận thông tin. Thứ hai, sự lên ngôi của các “nhà khoa học nhân dân” (citizen scientists) AI và quy trình làm việc theo cơ chế tác nhân AI có thể hạ thấp rào cản để thúc đẩy khoa học công dân vì các mục tiêu sinh thái. Cuối cùng, AI có thể được tận dụng để hình thành và thúc đẩy cam kết cộng đồng về trách nhiệm và đạo đức liên ngành trên ba lĩnh vực: con người, môi trường và công nghệ. (shrink)

Trong kỷ nguyên bùng nổ của trí tuệ nhân tạo (AI), việc hiểu biết đúng và kịp thời về bản chất của AI trở thành yêu cầu cấp thiết đối với cả cá nhân lẫn quốc gia nhằm tận dụng hiệu quả các cơ hội và giải quyết được các thách thức cũng như yêu cầu của thời đại. Trên cơ sở đó, bài viết nghiên cứu khái niệm “vô thức thuật toán” (algorithmic unconscious) như một khái niệm chứa đựng (...) những yếu tố tiềm ẩn trong hệ thống vận hành của AI dưới lăng kính tâm lý học phân tích của Carl Gustav Jung (1875- 1961). Phân tích tập trung vào các cổ mẫu của trường phái Jungian như “Kẻ Tinh Quái” (Trickster) và “Cái Bóng” (Shadow), qua đó làm rõ cách những hình tượng cổ mẫu này được phản ánh trong hoạt động của thuật toán hiện đại. Đồng thời, bài viết cũng phân tích hiện tượng “phóng chiếu” trong mối quan hệ giữa AI và con người thông qua minh họa về việc con người vô thức gán các kỳ vọng hay nỗi sợ hãi của bản thân lên AI. Qua đó, vấn đề “cá nhân hóa giả” (pseudo-individuation), trong đó AI tạo ấn tượng như một chủ thể có nhân cách riêng nhưng thiếu ý thức tự thân và sự thiếu hụt khả năng tự phản tỉnh ở AI được làm rõ. Thông qua những nội dung trên, bài viết đề xuất các định hướng thiết kế giúp cho AI tích hợp yếu tố tự nhận thức và các giá trị nhân bản, nhằm tăng cường tính minh bạch, củng cố niềm tin và phát triển mối quan hệ giữa con người và máy móc vì lợi ích chung của xã hội. (shrink)

Note: this and "Constants as Phase Conditions_ Reframing ε₀, α, and the Mass Defect via Structured Resonance" are part of a twin series to make CODES easier to understand. Abstract Modern scientific and computational systems rely on probabilistic modeling as a default approach to emergence, intelligence, and complexity. Yet, these stochastic paradigms remain epistemologically incomplete and structurally fragile. In this paper, I introduce CODES (Chirality of Dynamic Emergent Systems) as a new coherence-first framework that replaces randomness with deterministic phase behavior. (...) Rather than viewing emergence as the outcome of chance filtered through constraints, CODES models emergence as a structured result of prime-phase resonance, governed by coherence alignment rather than statistical distribution. This framework redefines intelligence, gravity, time, black holes, cognition, and learning as resonance-locked phase phenomena, not probabilistic artifacts. By grounding the behavior of systems in chirality, prime interval structuring, and recursive coherence scoring (PAS), CODES offers an unbroken, falsifiable model of lawful emergence with wide applications in physics, AI, biology, and systems theory. This paper outlines the theoretical foundations, contrasts with the probabilistic paradigm, and proposes empirical pathways to validate the resonance structure underlying reality. (shrink)

The Decentralized Key Protocol (DKP) is a hybrid framework designed to enhance privacy, security, and user control in social networking applications transitioning from centralized to decentralized architectures. DKP combines centralized storage for scalability with blockchain-based access control and integrity verification. Files are stored on centralized servers with random tags, anonymizing user data, while key-tag-hash tuples on the blockchain ensure secure access and file integrity. A permission request smart contract enables secure file sharing, where followers must request access for each file (...) view, with the contract verifying their status and granting one-time access to the tag and hash. This paper presents DKPs architecture, evaluates its benefits and challenges, and demonstrates its suitability for privacy-conscious social platforms. DKP offers a practical balance between decentralization, usability, and performance, addressing critical issues in data privacy and trust. (shrink)

This paper reinterprets classical biological and geometric phenomena—phyllotaxis and Kelvin’s truncated octahedral tiling—through the CODES framework (Chirality of Dynamic Emergent Systems). We show that irrational constants, Fibonacci series, and space-filling polyhedra are not mathematical accidents, but deterministic outcomes of prime-driven structured resonance. While calculus and probability provided useful approximations during the era of uncertainty, they now give way to coherence-first models. These new models describe reality not through limit-based derivation or stochastic estimation, but through direct alignment between phase-locked systems. Using (...) the Resonance Intelligence Core (RIC), we empirically validate Lord Kelvin’s conjecture on minimal-surface volumetric tiling and demonstrate how this principle governs both plant growth and AI substrate design. The result is a unification of form, function, and intelligence under a single geometric resonance field. (shrink)

The art of prediction of stock market volatility has always been a most challenged interdisciplinary research problem among scientist due to its highly non- linear nature of market flow. This paper tries to analysis the historical data of BSE Sensex using extreme volatilities estimators, GARCH, ANN and new proposed Text Mining approach for stock market predictions. Finally experimental results illustrates that the new proposed Text model can able to predict the volatilities of the stock price better than other models.

Abstract: Research on the nature and varieties of the format of cognitive representations in philosophy and cognitive science have been partly shaped by analogies to external, public representations. In this paper, we argue that relying on such analogies contributes to framing the question of cognitive formats in problematic, potentially counterproductive ways. We show that cognitive and public representations differ in many of their central features, making analogies to public representations ill-suited to improving our understanding of cognitive formats. We illustrate these (...) points by examining two case studies in which analogies to public representations may have had a negative impact on research: the 80’s-90’s debate about compositionality and cognitive architecture between symbolicists and connectionists; and contemporary discussions about the nature of visual demonstratives. Finally, we outline an alternative, computational account of formats that does not share the shortcomings of appeal to public representations. (shrink)

I develop the anticipatory argument for the view that it is nomologically possible that some non-biological creatures are phenomenally conscious, including conventional, silicon-based AI systems. This argument rests on the general idea that we should make our beliefs conform to the outcomes of an ideal scientific process and that such an ideal scientific process would attribute consciousness to some possible AI systems. More specifically, I argue that an ideal application of the iterative natural kind strategy would attribute consciousness to AI (...) systems which are coarse-grained functional duplicates of humans because this gives rise to a simpler and more unifying explanatory account of biological and non-biological cognition. If my argument is sound, then creatures made from the same material as conventional AI systems can likely be conscious, thus removing one of the main uncertainties for assessing AI consciousness and suggesting that AI consciousness may be a serious near-term concern. (shrink)

The term “medium independence” has different meanings. One sense maps onto “abstract-as-abstracta” descriptions while the other maps onto “abstract-as-omission” descriptions. Both senses have been deployed when it comes to understanding the nature of physical computation. However, because medium independence is a polysemic term, the sense being used should be clearly stated. If the sense is not clearly stated, then those who wish to engage in debates regarding medium independence and physical computation run the risk of conflating different but related issues (...) which can have consequences when it comes to thinking about physical computation across contexts. (shrink)

The Physical Signature of Computation is the most “robust” mapping view that’s ever hit the market. It is impressive in its detail and the careful attention paid to its characterization of both the physical system and the formal computational description—a true service to the philosophical literature. The book promises a “unified account of artifact and biological computation,” but here’s where things take a turn: after handling artifacts, the Robust Mapping Account fades from view and the Mechanistic Account of Physical Computation (...) (in its neurocognitive form) emerges as the way to capture biological computation. To have a unified account, then, requires two distinct approaches to understanding the nature of physical computation. This raises questions about whether the Robust Mapping Account can be extended to neural computation, but most importantly, questions about the compatibly of these two views is questionable given the history of the Mechanistic Account and its underpinning framework. (shrink)

The Self-Evidencing Agent offers a unique method for addressing difficult philosophical questions. Self-evidencing occurs when an agent uses their model of the world and of themselves to explain what they observe in the world and in themselves, such that those observations become evidence for their model – the more agents explain, the more they self-evidence. This book argues that there is good reason to cast an agent’s existence itself in terms of self-evidencing, and that if we begin from this as (...) a first principle, then we can make better sense of who and what we are, of how we engage in diverse ways with the world, and what matters to us. Self-evidencing can help situate attention, action, and perception. It also furnishes compelling approaches to decision-making and rationality, the self, of preferences and values. It can build bridges to consciousness, and even on to free will, and to meaning and wisdom. (shrink)

This research examines ethical issues in computational linguistics that can be applied to national defense by analyzing philosophical and security language. The increasing use of language contexts, such as intelligence and communication data analysis, raises ethical and philosophical challenges related to privacy, control, and accuracy. This research aims to identify and analyze ethical issues, especially in the use of computational linguistics in defense applications, as well as their implications for the protection of individual rights and privacy. This method involves reviewing (...) ethical technology references and analyzing the philosophical design of language and security. Deontological and utilitarian ethical theories are applied to evaluate the moral impacts and consequences of using the language of technology in a defense context. The results demonstrate that using linguistics in defense can pose privacy risks, misuse of data, and the potential for significant bias in decision-making. This often involves collecting data from multiple sources, creating challenges to ensure data is managed ethically and responsibly. Conclusion: This shows the need for a solid ethical and regulatory framework to ensure technology's fair and responsible use in context defense. Implications of the findings include the need for ongoing dialogue between technology developers, policymakers, and the public to mitigate ethical risks and ensure that application technologies comply with critical and security principles. With a comprehensive and responsible approach, technological linguistics can improve military safety and effectiveness without compromising individual rights and privacy. (shrink)

Recent years have seen a surge of interest in applying mechanistic thinking to computational accounts of implementation and individuation. One recent extension of this work involves so-called ‘wide’ approaches to computation, the view that computational processes spread out beyond the boundaries of the individual. These ‘mechanistic accounts of wide computation’ maintain that computational processes are wide in virtue of being part of mechanisms that extend beyond the boundary of the individual. This paper aims to further develop the mechanistic account of (...) wide computationalism by responding to two outstanding worries, what are called the parsimony and testability challenges. The first is based on considerations about wide computation’s ontological cost; the second the view’s experimental testability. The argument is that wide mechanistic computationalism can gain the necessary conceptual resources to address the challenges by embracing two further aspects of the mechanistic approach: (i) the structural aspect of mechanistic explanation and (ii) the notion of constitutive relevance. (shrink)

A proposal for a new model of the evolution of gene regulation networks and development that draws on work from artificial intelligence and philosophy of mind. Each of us is a collection of more than ten trillion cells, busy performing tasks crucial to our continued existence. Gene regulation networks, consisting of a subset of genes called transcription factors, control cellular activity, producing the right gene activities for the many situations that the multiplicity of cells in our bodies face. Genes working (...) together make up a truly ingenious system. In this book, Roger Sansom investigates how gene regulation works and how such a refined but simple system evolved. Sansom describes in detail two frameworks for understanding gene regulation. The first, developed by the theoretical biologist Stuart Kauffman, holds that gene regulation networks are fundamentally systems that repeat patterns of gene expression. Sansom finds Kauffman's framework an inadequate explanation for how cells overcome the difficulty of development. Sansom proposes an alternative: the connectionist framework. Drawing on work from artificial intelligence and philosophy of mind, he argues that the key lies in how multiple transcription factors combine to regulate a single gene, acting in a way that is qualitatively consistent. This allows the expression of genes to be finely tuned to the variable microenvironments of cells. Because of the nature of both development and its evolution, we can gain insight into the developmental process when we identify gene regulation networks as the controllers of development. The ingenuity of genes is explained by how gene regulation networks evolve to control development. (shrink)

Abstract Introduction Logically valid deductive arguments are clear examples of abstract recursive computational proce‐ dures on propositions or on probabilities. However, it is not known if the cortical time‐consuming inferential pro‐ cesses in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes. Methods In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and invalid (...) inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth‐functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two‐condition para‐ digm (100 trials for each condition). After the initial general analysis, a trial‐by‐trial approach in beta‐2 band allowed to uncover not only evoked but also phase asynchronous activity between trials. Results showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta‐2 activa‐ tions (p‐value < 0,01, Wilcoxon signed rank test). Conclusion We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events. Keywords Beta‐2 band, Evoked potentials, Induced potentials, Deductive inference, Logical validity, Cortical bases of logical reasoning. (shrink)

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered “deductive” because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive pro- cesses has not been addressed yet. In this work we consider typically deductive logico- probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same (...) stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age 1⁄4 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the dif- ferences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive “core” areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes. (shrink)

In chapter eleven of "On The Foundation of Computing," Primiero takes on the implementation debate in computer science. He contrasts his theory with two other views—the Semantic and the specification—artifact. In this paper, I argue that there is a way to fine-tune the implementation concept further. Firstly, contrary to Primiero, I claim it is problematic to separate the implementation relationship from the conditions which make it correct. Secondly, by taking a pluralistic approach to implementation, I claim it is a mistake (...) to try and provide a general theory of implementation for the entire production cycle of computational systems. (shrink)