Intelligence of Matter: Rise of a New Style of Doing Science and Scientific Thinking?

From Galileo’s conviction that the Universe is written in the language of mathematics to the genomic and computational revolutions of the twentieth century, science has long sought to describe nature through external symbolic systems. However, mounting evidence across biology, physics, and cognitive science suggests that this reduction of semantics to syntax is insufficient. Life cannot be deterministically read only from DNA sequences, cognition cannot be reduced to just rule-based logic, and complex systems exhibit emergent behaviors that transcend symbolic description. We argue that these phenomena point toward an underappreciated principle, “the intelligence of matter”, whereby organized material systems inherently process information, adapt, and remember. Examples span from protein allostery and epigenetic memory to epitranscriptomic regulation, intelligent soft matter, and ecological reservoir computing. In these cases, computation emerges not from imposed codes but from the intrinsic dynamics of matter that is far from equilibrium. Recognizing intelligence as a general property of organized matter may inaugurate a new scientific style: one that deciphers the semantics of nature rather than superimposing ours and thus reshaping the epistemology of modern science.

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Publication Details

Journal
Systems
Published
2025-11-28
DOI
https://doi.org/10.3390/systems13121072
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Intelligence of Matter: Rise of a New Style of Doing Science and Scientific Thinking?

Alessandro Giuliani, Timir Tripathi, Vladimir Nikolaevich Uversky
Systems
Neural Networks and Reservoir Computing
article

Intelligence of Matter: Rise of a New Style of Doing Science and Scientific Thinking?

Alessandro Giuliani, Timir Tripathi, Vladimir Nikolaevich Uversky
article en

Abstract

From Galileo’s conviction that the Universe is written in the language of mathematics to the genomic and computational revolutions of the twentieth century, science has long sought to describe nature through external symbolic systems. However, mounting evidence across biology, physics, and cognitive science suggests that this reduction of semantics to syntax is insufficient. Life cannot be deterministically read only from DNA sequences, cognition cannot be reduced to just rule-based logic, and complex systems exhibit emergent behaviors that transcend symbolic description. We argue that these phenomena point toward an underappreciated principle, “the intelligence of matter”, whereby organized material systems inherently process information, adapt, and remember. Examples span from protein allostery and epigenetic memory to epitranscriptomic regulation, intelligent soft matter, and ecological reservoir computing. In these cases, computation emerges not from imposed codes but from the intrinsic dynamics of matter that is far from equilibrium. Recognizing intelligence as a general property of organized matter may inaugurate a new scientific style: one that deciphers the semantics of nature rather than superimposing ours and thus reshaping the epistemology of modern science.

SystemsVol. 13(12)
North Eastern Hill University (IN), University of South Florida (US), Istituto Superiore di Sanità (IT), USF Health Byrd Alzheimer's Institute (US)
Indian National Science Academy, University of South Florida
Openalex Percentile: Top 80%
Neural Networks and Reservoir Computing
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Intelligence of Matter: Rise of a New Style of Doing Science and Scientific Thinking? — Alessandro Giuliani, Timir Tripathi, et al. · Systems (2025) | TGRS Research Map | TGRS