Patrick-Olivier Dieu

This framework presents a rigorous analysis of human cognition, highlighting its intrinsic limitations and the role of information stabilization in understanding and knowledge acquisition. Cognition is constrained by evolutionary and biological factors, and scientific progress is bounded not by reality itself but by the limits of cognitive capacity. Tools and artificial intelligence can amplify cognitive reach but cannot surpass these fundamental constraints. The framework’s robustness stems from its foundational assumptions, which are logically coherent and resistant to internal critique. Attempts to replace or modify these assumptions encounter fundamental obstacles, including the difficulty of defining new foundational principles and maintaining coherence within an alternative framework. This work provides a unified perspective on the boundaries of human cognition, the scope of scientific knowledge, and the structural constraints on theory formation.

This paper clarifies a conceptual framework based on the finitude of cognition and the role of information stabilization in scientific knowledge. Scientific theories do not provide direct access to reality in itself but formalize structures that finite cognitive systems can stabilize and reproduce. Recent discussions in fundamental physics, such as the problem of the origin of fundamental constants (e.g., the fine-structure constant and particle masses), highlight the persistence of explanatory limits. This work argues that even a complete physical theory would not necessarily grant access to the ultimate origin of reality, but only to structures that can be stabilized, reproduced, and formalized. Perfect reproducibility would render the distinction between original and copy indistinguishable, suggesting that what science ultimately stabilizes are reproducible structures rather than metaphysical origins. The framework therefore proposes that the limits of cognition define the horizon of intelligibility in both science and philosophy.

This manifesto presents a framework connecting cognition, science, and reality, emphasizing the role of information stabilization in defining what can be known. Cognition is finite, emergent, and structured; it arises from stabilized physical and cellular networks and is constrained by replication, symbolic organization, and survival-driven architecture. Scientific theories formalize what cognition can stabilize, revealing the structured interface between observer and world rather than reality in itself. Amplification of cognition through technology or abstraction increases formal capacity but also exposes limits, where intelligibility fades. The framework introduces the Titan Lock, a conceptual boundary identifying minimal conditions for meaningful discourse. Reality is understood as a mille-feuille (layered, stratified structure); certain layers remain permanently inaccessible to any cognition. Science is thus not the conquest of reality, but the continuous refinement — and regulation — of the space of the intelligible.

Cognition defines the horizon of all knowledge: what can be known, represented, or formalized depends on the stabilization of information within finite networks. This cartography synthesizes insights from nine previous texts and introduces further clarifications on the biological and structural basis of cognition, including stabilized cellular organization and dynamic, constrained replication. It maps the boundaries of intelligibility, revealing where science, mathematics, and thought themselves meet the limits of human and electronic cognition. By tracing how patterns stabilize, replicate, and adapt, this framework situates understanding as both an achievement of insight and a recognition of cognitive limits.

Mathematics is discovered only in the sense that perception presents patterns to cognition; what we formalize is never reality itself, only the trace our minds can grasp. This paper argues that mathematics is a formal extension of human cognition rather than a mind-independent structure of reality. Mathematical structures emerge from evolved cognitive capacities for abstraction, categorization, recursion, and symbolic manipulation. Their effectiveness in empirical science arises from a selective alignment between these cognitive capacities and the regularities of the world, rather than from a pre-existing mathematical ontology. By addressing classical objections—including Platonism, the “unreasonable effectiveness” of mathematics, indispensability, and results beyond human intuition—this work situates mathematics as a cognitively mediated, indispensable tool for modeling and understanding the empirical world. It emphasizes that all scientific knowledge is produced through the interaction between observer and observed, constrained by the limits of cognition, and that epistemic modesty is essential for interpreting the apparent universality of mathematical structures.

The effectiveness of scientific laws and mathematical models does not reveal a mind-independent reality; it reflects the structured operations of human cognition. Science emerges at the interface between a partially accessible physical world and our cognitive capacities for abstraction, classification, and formal computation. This manifesto advocates a reverse-engineering approach to cognition, analyzing how naming, classifying, and calculating generate the laws and models underlying scientific knowledge. By revealing the cognitive architecture of science, this perspective highlights its inherent constraints, biases, and the potential for alternative modes of understanding. Thought experiments with alternative cognitive frameworks, artificial intelligence, and extreme environments illustrate both the limits and plasticity of human scientific understanding. Science is thus a product of cognition—revealing the structure and possibilities of our minds—rather than a complete mirror of reality.

Scientific laws and mathematical structures are not mere reflections of reality but emerge from the constraints and biases of human cognition. This manifesto explores the limits of cognition as they shape our understanding of fundamental physics, from Planck-scale phenomena to black holes and spacetime symmetries. By reverse-engineering the cognitive processes underlying scientific modeling, we identify how the architecture of our mind guides the formation of laws, selects applicable mathematics, and imposes boundaries on intelligibility. The manifesto proposes thought experiments and alternative cognitive frameworks to probe the frontier where science meets the limits of human conceptualization.

This paper argues that all possible cognition is necessarily biased, not for psychological or contingent reasons, but as a consequence of universal physical constraints. Any cognitive system must be physically realized, finite, and subject to thermodynamic and informational limits. To maintain stable internal states over time, such systems must selectively process information relevant to their own organizational persistence. This necessary selection constitutes a structural form of cognitive bias. Science, understood as a collective and instrumented extension of cognition, inherits these constraints. From this perspective, conceptual difficulties in fundamental physics—such as singularities, uncontrolled infinities, and failures of unification—are interpreted not as empirical shortcomings, but as structural boundaries arising from the viewpoint of finite cognition. The argument does not deny scientific progress, but reframes the limits of fundamental theories as necessary features of physically situated modeling.

This note examines contemporary artificial intelligence systems as a limiting case of finite cognition. Building on a perspective-based framework in which cognition is treated as a physically constrained, scale-dependent phenomenon, it argues that AI performance, coherence, and predictive success do not entail privileged ontological access to reality. Artificial intelligence illustrates how a finite cognitive system can generate stable, operationally valid outputs without explicit ontological grounding. The analysis is epistemological and interpretive, not empirical, and serves as a conceptual corollary to Cognition Across Scales: A Perspective-Based Interpretation of Physical Laws (PhilArchive).

This paper presents a perspective-based analysis of physical laws grounded in the physical constraints of cognition. Cognition is treated as a physically realized, scale-dependent emergent phenomenon, capable of acquiring, stabilizing, and using information. By examining how physical description would differ if cognition were instantiated at atomic, molecular, or subatomic scales, the paper argues that fundamental features of modern physics—quantization, wave–particle duality, measurement collapse, and nonlocal correlations—should be interpreted as scale-relative manifestations of constrained cognition rather than as absolute features of reality. Conceptual difficulties in fundamental physics are reframed as signatures of the physical conditions under which knowledge becomes possible, highlighting that “laws” emerge only from within a finite cognitive perspective.

This paper formalizes a minimal epistemic constraint on scientific knowledge. It does not propose a physical theory, a metaphysical hypothesis, or a philosophical doctrine. Instead, it specifies the minimal conditions under which information becomes intelligible as scientific information. Scientific information is defined as content that enables description, comparison, prediction, or modeling of phenomena within a communicable and reproducible framework. Such information presupposes a cognitive system capable of discriminating, structuring, and interpreting physical interactions. The framework advances three core principles: (1) cognition functions as a boundary condition for scientific information, (2) information emerges from the interaction between phenomena and cognitive systems rather than residing intrinsically in either alone, and (3) variations in cognitive context may produce systematic differences in the resulting information without negating objectivity or scientific validity. This approach introduces no new entities and is compatible with classical physics, quantum mechanics, and information theory. It does not claim that cognition creates reality; it claims that intelligibility is conditioned by cognitive processes. The proposed constraint is confrontable through comparative studies of distinct cognitive systems, controlled variations of observational context, and experiments involving human, non-human, or artificial cognition. The framework aims to clarify the epistemic boundaries of scientific knowledge while preserving its methodological rigor.

This paper presents a minimal epistemic framework arguing that scientific information does not exist independently of a cognitive system, but emerges from the interaction between phenomena and cognition. It does not propose a physical theory, a metaphysical claim, or a relativistic account of knowledge. Instead, it formalizes the minimal conditions under which information becomes intelligible as scientific information. The framework articulates five core principles: (1) scientific information presupposes a system capable of discrimination, structuring, and interpretation; (2) information emerges from the interaction between phenomena and cognitive systems rather than residing intrinsically in either alone; (3) variations in cognitive context may produce systematic differences in information without negating objectivity; (4) there is no scientifically meaningful observation independent of a cognitive framework; and (5) science faces a structural boundary of intelligibility that cannot be eliminated by technical progress. These principles are compatible with existing physical theories, including classical and quantum physics, and do not introduce new entities or modify physical laws. The framework is empirically confrontable through comparative studies of human, non-human, and artificial cognition, as well as through controlled variations of observational context. It aims to clarify the epistemic conditions of scientific practice rather than to redefine the nature of reality itself.

This paper articulates a conceptual framework examining the role of cognition in the formation of scientific information. Operating under a minimal epistemic constraint, it argues that scientific information becomes intelligible only through the interaction between physical phenomena and a cognitive system. The framework does not propose a physical theory, a metaphysical claim, or an observer-dependent ontology. Instead, it treats cognition as a boundary condition shaping what can be known, not what exists. Drawing on insights from physics, cognitive science, and information theory, it emphasizes that observation is an active process and that scientific knowledge reflects structured interactions between observer and observed. The paper explores the implications of this constraint for scientific practice, including the limits of measurement, the interpretation of quantum phenomena, and the comparison between human and artificial cognition. It concludes that understanding the universe requires explicit consideration of the cognitive conditions under which scientific information emerges.