Why this Data is Valuable

Number AI collects granular player input and movement data from video games to fuel the training of smarter NPCs, adaptive AI systems, and improved gameplay mechanics. This includes position, orientation, speed, and jump patterns, which help train NPC pathfinding, navigation, and movement realism. Control inputs like key presses, mouse movement, and gamepad actions inform models on how players interact with the environment, aiding in the development of responsive AI behaviors and predictive input models. Aiming behavior and input timing are used to train enemy AI to better mimic or counter human reflexes and targeting precision. By analyzing pathing, combat tactics, and interaction logs, AI can learn to anticipate player strategies and dynamically respond to them. Resource management decisions (like when players heal or reload) help model situational awareness and prioritization logic for NPCs. Contextual data—such as map, game mode, and session outcomes—trains AI systems to adjust behavior based on scenario difficulty or player skill level. Finally, performance data, anomalies, and user feedback are used to identify edge cases, improve NPC difficulty scaling, and ensure AI behavior remains human-like and enjoyable.