First Draft on the xInf Model for Universal Physical Computation and Reverse Engineering of Natural Intelligence
Hongbo Jia

TL;DR
This paper introduces the xInf model, a theoretical framework that unifies physics, computer engineering, and neuroscience to analyze physical computation and consciousness, proposing a universal language and a conjecture about machines passing the Turing Test in physical time.
Contribution
The paper presents the xInf model as a novel universal language for translating between scientific fields and introduces a conjecture on constructing physical machines that can pass the Turing Test.
Findings
xInf model is Turing-complete and adaptable to physical time properties
Provides a unified language for physics, engineering, and neuroscience
Conjectures the existence of a minimal rule set for physical machines to pass the Turing Test
Abstract
Turing Machines are universal computing machines in theory. It has been a long debate whether Turing Machines can simulate the consciousness mind behaviors in the materialistic universe. Three different hypotheses come out of such debate, in short:(A) Can; (B) Cannot; (C) Super-Turing machines can. Because Turing Machines or other kinds of theoretical computing models are abstract objects while behaviors are real observables, this debate involves at least three distinct fields of science and technology: physics, computer engineering, and experimental neuroscience. However, the languages used in these different fields are highly heterogeneous and not easily interpretable for each other, making it very difficult to reach partial agreements regarding this debate, Therefore, the main goal of this manuscript is to establish a proper language that can translate among those different fields.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputability, Logic, AI Algorithms · Quantum Computing Algorithms and Architecture · Photoreceptor and optogenetics research
