In dem Bereich der künstlichen Intelligenz gibt es die sog. "The Platonic Representation Hypothesis“. Diese geht davon aus, dass die neuronale Repräsentanz von bestimmten abstrakten Konzepten immer konstant sei.

Im "Proof of a perfect platonic representation hypothesis“ by Liu Ziyin und Isaac Chuang ist zu lesen: "A recent line of research in AI has uncovered the emergence of universally aligned and structurally similar representations across different models — a phenomenon referred to as the Platonic Representation Hypothesis. This hypothesis states that large models trained on larger and larger datasets will learn representations that are very close (if not identical) to each other, even if these models have different architectures and may even see different (but often related or paired) data.“ 

Und in der Grundlagenarbeit "The Platonic Representation Hypothesis“ (PRH) wird ausgeführt: "Our central hypothesis is that there is indeed an endpoint to this convergence and a principle that drives it: different models are all trying to arrive at a representation of reality, meaning a representation of the joint distribution over events in the world that generate the data we observe.“ Und natürlich wird auch das Höhlengleichnis bemüht: "We call this converged hypothetical representation the “platonic representation” in reference to Plato’s Allegory of the Cave (Plato, c. 375 BC), and his idea of an ideal reality that underlies our sensations. The training data for our algorithms are shadows on the cave wall, yet, we hypothesize, models are recovering ever better representations of the actual world outside the cave.“ 

Aus meth. konstr. Sicht frage ich mich, inwieweit die PRH der KI im Unterschied zum expliziten Ideationsverfahren auf ein implizites Verfahren ideativer Prozesse hinaus liefe. Aus stochastischer Perspektive überschnitten sich damit Abstraktion und Ideation bzw. abstraktive und ideative Prozesse.