Ever wondered what a GPU goes through during a massive language model inference run? While you type a query and wait for tokens, the silicon under the hood is holding together a fragile house of cards: balancing context window limits, scheduling activations, managing weights, and evading malicious adversarial attacks.
To teach you how LLMs behave (and fall apart) under load, I built an interactive game:
Play in Fullscreen Mode (if the embed sizing is tight)
Before initiating your run, choose your difficulty configuration (each represented by a unique retro pixel chip sprite and custom parameters):
This isn't just a homage to Vampire Survivors—every upgrade, weapon, and enemy represents a real-world concept in modern machine learning. Here is how the in-game mechanics map directly to how Large Language Models operate, fail, and optimize in production:
