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Gradland: On Phenomenal Experience, Differentiated Across Many Dimensions
Not provided
neural networksphenomenal experienceJacobian structure
2609.09306
Builder Relevance
4h ago60%
Abstract
The paper explores how the structure of physical interactions can characterize phenomenal experience in a neural network-based idealized world.
Reality Card
Core Claim
The paper demonstrates that the first-order structure of physical interactions, represented by gradients or Jacobians, can effectively account for various aspects of phenomenal experience.
Method / Result
Introduces two measures of Jacobian structure: effective rank and cohesion, based on Kirchhoff complexity.
Limitations
The idealized nature of the model may limit its applicability to real-world scenarios.
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