I built a neural network using DOOM games (github.com)

A developer has created a unique neural network implementation within the classic video game DOOM, employing its game mechanics to simulate complex computations. Using "voodoo dolls" to represent network neurons and game entities that interact dynamically, the network performs tasks such as recognizing handwritten digits and generating new DOOM level names. This innovative approach involves a series of matrix calculations, activation functions, and comparisons that yield precise results verified against mathematical references, showcasing an engaging interface that allows users to visualize neural network operations in a playful setting. This project, named "doomformer," is significant for the AI/ML community as it effectively combines gaming mechanics with machine learning concepts, making neural networks more accessible and interactive. By running multiple instances of DOOM as a computational platform, the developer demonstrates the potential of gaming environments as experimental spaces for AI research. The use of detailed scripts to control game functions and validate outcomes introduces fresh possibilities for real-time learning and decision-making in complex environments, paving the way for new educational tools and research methodologies in AI and neural network training.