Why are neural networks and cryptographic ciphers so similar? (2025)
Summary
This article highlights structural similarities between neural networks and cryptographic ciphers, focusing on sequence processing, repeated layers, and mixing strategies, and argues that convergent evolution in design arises from similar performance and hardware constraints. It also notes three core properties that shape both fields and hints at cross-disciplinary insights.