Can Shallow Or Reciprocal Interaction Structures Compute Nonlinearly

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• Shallow interaction structures cannot compute non-linearly separable functions; depth (hidden layers) is necessary for ETI-relevant individualityclaim0.807
  Assertion that deep organization is mandatory, based on connectionist theory
• Under What Conditions Can Deep Interaction Structures Computingquestion0.794
• Under What Conditions Can Deep Interaction Structures Evolvequestion0.757
• How Do Nonlinearly Separable Interactions Between Components Enablequestion0.746
• When interactions constitute non-linearly separable functions, it creates a ‘we’; what we are doing becomes a relevant variable.claim0.744
  Explains how non-separability shifts identity from parts to collective.
• Hierarchical structure in interaction topology enables complex multiscale patterns that cannot exist in flat networks.claim0.739
  Explains why biological systems achieve organization across scales while language models struggle; grounds in free energy scaling
• Does the geometric structure of neural representations causally shape model behavior?question0.738
  The motivating research question of the paper
• This structural resonance does not mean mathematics proves Buddhism; it shows that human intelligence approaching the same structural truth from different directions can produce overlapping contours.claim0.738
  Closing epistemic disclaimer distinguishing structural resonance from proof.