Cracking the code: How neural networks might actually “think”

The blog post discusses a new approach to understanding neural networks through a combinatorial perspective, which offers insights into how these networks learn and compute logical operations. By examining the relationships encoded in the networks' parameters, the authors propose a 'feature channel coding hypothesis' that aims to decode neural logic and enhance interpretability, potentially improving AI reliability and safety.