游戏AI来了，英伟达新模型看直播学会所有游戏，GPT-5.2秒杀塞尔达

Core Insights - Nvidia has developed a new AI model called NitroGen that learns general gaming operations by observing 40,000 hours of gameplay on platforms like YouTube and Twitch, marking a significant advancement in AI learning methods [1][3][39] - NitroGen is designed to be a versatile AI capable of playing over 1,000 different games, demonstrating a form of "game intuition" that allows it to adapt quickly to new gaming environments [11][14] - The model's ability to learn from visual inputs and corresponding controller actions signifies a shift in AI training, moving from traditional data reading to a more observational learning approach [10][37] Group 1 - NitroGen learns by watching gameplay videos that include controller overlays, allowing it to associate visual actions with specific inputs [7][10] - The model's performance in unfamiliar games is significantly better than that of models trained from scratch, showing a 52% improvement [14] - Nvidia's ambition extends beyond gaming; the technology aims to create a universal AI capable of navigating real-world scenarios by leveraging insights gained from virtual environments [22][25] Group 2 - The development of NitroGen represents a pivotal moment in robotics, as it utilizes gaming as a training ground for physical intelligence, potentially overcoming the "Moravec's Paradox" [26][40] - The AI's learning process is likened to a "matrix" where it can experience thousands of trials in a virtual setting, accelerating its evolution beyond physical time constraints [41] - Future AI agents will likely be structured in a layered architecture, combining reasoning capabilities with motion control strategies derived from extensive video data [44]