The Concept of Representation in ML: Beyond Plato and Aristotle

Representation is a central concept in modern machine learning, where it usually refers to internal encodings that support learning and generalization. As models scale and their capabilities become increasingly human-level this representational language sometimes shifts from an engineering context into the more philosophically loaded domain of mental representation. We argue that this is the case for recent claims about the convergence between representational properties of different AI models. In particular, we examine “The Platonic Hypothesis" and its claims that this convergence is driven by a unified structure of reality. We examine those claims by introducing arguments and ideas from the debates on Mental Representation in philosophy of mind. We argue that these philosophical resources can clarify what is at stake in such claims, explain why alignment evidence alone is insufficient for strong metaphysical conclusions, and suggest directions for future research.