# The Platonic Representation Hypothesis

> Platonic Representation Hypothesis를 소개한 논문.

[Platonic Representation Hypothesis](https://wiki.g15e.com/pages/Platonic%20Representation%20Hypothesis.txt)를 소개한 논문.

## Abstract

> We argue that representations in AI models, particularly [deep networks](https://wiki.g15e.com/pages/Deep%20neural%20network.txt), are converging. First, we survey many examples of convergence in the literature: over time and across multiple domains, the ways by which different neural networks represent data are becoming more aligned. Next, we demonstrate convergence across data modalities: as vision models and language models get larger, they measure distance between datapoints in a more and more alike way. We hypothesize that this convergence is driving toward a shared statistical model of reality, akin to <Plato>'s concept of an ideal reality. We term such a representation the platonic representation and discuss several possible selective pressures toward it. Finally, we discuss the implications of these trends, their limitations, and counterexamples to our analysis.

https://arxiv.org/abs/2405.07987