In a recent video, creator Nichonauta showcased how Google's Gema 4 language model can be used to play video games in real time. The experiment explores the impact of system prompts, persistent memory, and chain-of-thought reasoning on the AI's decision-making while controlling a game.
The video starts with an analysis of macro and micro management through the AI's reasoning chain, followed by stress tests on keyboard input and version control. A major focus is the implementation of persistent memory, allowing the AI to retain context across gaming sessions. The discussion also covers computer vision integration with Gema models, game design for AI players (including using Pokémon as a testbed), and environment navigation tests.
Nichonauta compares Gema 4 against competitors like Qwen and GPT, emphasizing the critical role of system prompts and contextual framing. The conclusion highlights that while Gema 4 shows promise for interactive AI, its performance heavily depends on careful prompt engineering and memory management.