Against Physics-Based AI: A Critical Response from the Possest–PQF Perspective
Year: 2025
Type: article
Abstract: This paper presents a critical response to the resurgence of physics-based artificial intelligence, arguing that such approaches rest on a latent metaphysical substrate: the belief in a stable, modelable world. From the perspective of the Possest–PQF framework, physical laws are not fundamental truths, but local stabilizations within a plenum of intensities. Intelligence, accordingly, is not predictive modeling, but the recursive reorganization of accessibility. We contrast the physics-informed paradigm with a filtrational ontology, developing formal operators of intensional bifurcation. The goal is not to refine representation, but to dissolve the representational regime entirely. Possest–PQF offers not an improvement upon physicalist AI — but a transposition of what counts as intelligence, truth, and system.
Author: Schimmelpfennig, Yochanan
Language: English
Subfield: History and Philosophy of Science
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6949904639
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