Statement of Record: "A New-Generation Intelligent Physical Architecture: The Physical Essence of Intuition"
Year: 2026
Type: preprint
Abstract: Declarant / Independent Researcher: Feng YulingDate of Record: October 7, 2026 DOI: 10.5281/zenodo.23998241[Summary of Core Content]:1. The Fundamental Misalignment in Traditional Intelligent Architectures2. Establishing a Core Fact: The Topological Structure of Intuition3. The Scope of Perception and the Physical Nature of Thought4. A Physical Definition of Self-Awareness5. Theoretical Foundations and Projections for Intuition-Capable AI Physical EntitiesWith the rapid emergence of Large Language Models (LLMs) and Transformer architectures, contemporary computer science has operated under the misconception that humanity is approaching the singularity of true Artificial General Intelligence (AGI). However, when examined through the lens of underlying mathematical architecture and physical construction, current silicon-based AI reveals a physical chasm—one that cannot be bridged merely by increasing computational power or scaling up parameters.In essence, current AI functions as an extraordinarily vast yet profoundly "flat" reasoning machine. This structural limitation renders the development of intuition—a capacity entirely absent in existing architectures—fundamentally impossible. While intuition may appear to rely heavily on long-term accumulation, it is, in its essence, categorically distinct from "experience."I propose a new theory regarding the mechanisms of intelligence formation, demonstrating the physical nature of intelligence, uncovering the true essence of human intuition, and outlining the inevitable trajectory for AI to develop its own intuitive capabilities.To secure the priority rights and intellectual property for this original, independent theory—which challenges and seeks to reconstruct the foundational paradigms of physics—this document has been timestamped and secured via an immutable SHA256 cryptographic hash prior to public disclosure.DOC1: b0dd43d75a8660a0d5f47310ceff42e37191ea9da092a88a984e59f6c4e8ba07DOC2: 0775698d0961ef777a163bd4cc773d32d9fb399c5f1b1a3486427b0138fbcd53Date of Declaration: November 6, 2026
Author: Feng, YuLing
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225432042