Different models cannot converge to the same representation if they have access to fundamentally different information; convergence is capped by mutual information between input signals

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• Bigger models are more likely to converge to a shared representation than smaller modelshypothesis0.853
  Selective pressure toward convergence via model capacity
• How do representations differ or converge between architectures, tasks, and modalities?question0.833
  Broader research question MAS is positioned to address, citing multiple recent works.
• Scaling model size, as well as data and task diversity, drives representational convergence toward the platonic representationhypothesis0.818
  Core mechanism hypothesis connecting PRH to the empirical trend of scaling in AI
• Interpretability features converge across different model architectures, revealing structural similarities.claim0.812
• Different neural network models trained on different objectives and modalities are converging to a shared statistical model of reality in their representation spaceshypothesis0.803
  The central hypothesis of the paper; the platonic representation hypothesis itself
• The model converges to a more stable truth direction in middle-to-late layers, as evidenced by increasing cosine similarity between layer-wise probes.claim0.800
  Supported by the geometric transition visible in cosine similarity heatmaps for F0-F3.
• Diverse computer vision models trained on visual recognition tasks converge to remarkably similar internal feature representations regardless of architecture, training procedure, or implementation details, closely matching the organization of animal visual cortexfinding0.795
  Empirical evidence for the universality hypothesis cited as supporting the possibility of convergent consciousness-like solutions
• Research gap: representational convergence in robotics has not been demonstrated at the same level as vision and languagequestion0.794
  Authors note robotics lacks a standardized representation approach and sufficient training data diversity to show PRH effects