Microsoft researcher Adrian de Wynter, an AI scientist at Microsoft and researcher at the University of York, built a working neural network in the game Age of Empires II using goats to demonstrate that assumptions of human-like attributes in large language models (LLMs) are fundamentally flawed. In a study titled "If LLMs Have Human-Like Attributes, Then So Does Age of Empires II," de Wynter used the game's scenario editor to replicate basic neural network functions, where grass tiles represent "0," bridges represent "1," and goats act as bits carrying digital signals. The study argues that anthropomorphic features of LLMs are "empirically non-unique" because they can be replicated with digital goats in a strategy game from the 90s. De Wynter stated that many studies interpret chatbot behavior as evidence of uniquely human traits when they should assume other neural network systems can display the same characteristics. He told 404 Media that people should stop assuming LLMs exhibit human-like behavior simply because their models are trained on natural-language data, and argued that people should not become emotionally attached to prompt-based expert systems any more than they would to a toaster.