Technology Category
Machine Learning: Information TheoryReasoning under Uncertainty: CausalityKnowledge Representation and Reasoning: Action, Change, and Causality
Where are the bits in atoms? A perspective on the physical origin and evolutionary nature of information
🤖 AI Summary
The ontological foundation of information—particularly its physical origin and dynamical evolution in atomic and other physical systems—remains inadequately grounded in fundamental physics.
Method: We propose an ontological definition: “information is a structural pattern that represents another structural pattern,” and systematically introduce causal set theory into the interdisciplinary domain of information philosophy and physics. Using causal sets to model structural generation processes, we formulate a physically realizable framework for the emergence of information.
Contribution/Results: This framework unifies theoretical physics, computation theory, and evolutionary principles, offering a novel paradigm for interpreting quantum information, investigating the origins of life, and advancing foundational theories of artificial general intelligence. It bridges abstract informational concepts with concrete spacetime microstructure, thereby grounding information in relativistic causality and discrete geometry.
Technology Category
Application Category
📝 Abstract
Information is a structural pattern that represents another structural pattern. This perspective hypothesizes that modelling of structure creation through causal sets can elucidate the natural origin, evolution and ontology of information.
Problem
Research questions and friction points this paper is trying to address.
Information dynamics
Atomic systems
Time evolution
Innovation
Methods, ideas, or system contributions that make the work stand out.
Causal Relationships
Information Transformation
Educational Analogies
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2024-04-05Citations: 0
