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.
Tripathi et al. (Fri,) studied this question.