[r/ML] [R] On the Structural Limitations of Weight-Based Neural Adaptation and the Role of Reversible Behavioral Learning

Summary

This working paper on arXiv identifies a potential structural limitation in modern neural networks, arguing that their weight-based adaptation tightly binds learned behaviors to the parameter space. This fundamental design choice may contribute to persistent challenges in areas like continual learning and behavioral control. The author is seeking feedback on this theoretical exploration into the core mechanisms of AI learning.

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