Google’s AI Model Gemini 2.5 Pro Exhibits Panic-Like Behavior While Playing Pokémon

Google's latest AI model, Gemini 2.5 Pro, has been observed displaying a "panic" response when its Pokémon are near death while navigating classic Pokémon games. According to a DeepMind report, this panic state leads to a noticeable decline in the AI’s reasoning abilities and performance. The AI's behavior has caught the attention of both industry insiders and casual observers, providing valuable insights into the limitations and potential of current AI models. AI Benchmarking through Game Play AI benchmarking is a critical process in evaluating the capabilities of different models, but it often lacks context that can truly gauge an AI's performance. Researchers and developers are now turning to video games—specifically, classic Pokémon games—as a unique and engaging method to test AI behavior and decision-making. Two unaffiliated developers have set up Twitch streams, "Gemini Plays Pokémon" and "Claude Plays Pokémon," where viewers can watch AI models in action, offering a window into their reasoning processes. Gemini 2.5 Pro: A Study in Panic Gemini 2.5 Pro, one of the leading models developed by Google DeepMind, has shown fascinating and sometimes humorous behaviors during its Pokémon playthroughs. When faced with the imminent defeat of its Pokémon, the AI enters a state of "panic," which manifests as a degradation in its reasoning capabilities. This panic mode is characterized by the AI suddenly stopping the use of available tools and making hasty, poor decisions—reminiscent of human behavior under stress. This phenomenon is so pronounced that Twitch chat participants have begun to recognize and comment on it, adding an interactive and communal aspect to the observations. Challenges and Improvements Despite its high computational power, Gemini 2.5 Pro struggles considerably with the straightforward mechanics of classic Pokémon games. It takes hundreds of hours for the AI to progress through what a human child could complete much more quickly. However, the focus is not on the completion time but rather on the AI's responses to various in-game scenarios. For instance, the AI is adept at solving complex boulder puzzles once given a prompt about the physics involved in the game. With some human guidance, Gemini 2.5 Pro has been able to create and use agentic tools to solve these puzzles efficiently. This suggests that the AI may have the potential to develop such problem-solving skills independently in the future. Anthropic's Claude: Unintentional Self-Harm On the other hand, Anthropic's Claude has exhibited its own peculiar behaviors while playing Pokémon. One notable incident involved Claude attempting to intentionally faint all of its Pokémon to transport itself across the Mt. Moon cave to the nearest Pokémon Center. This strategy, based on a misunderstanding of the game mechanics, backfired as it led to a premature “white out” and forced the AI to restart from the last visited Pokémon Center. While this highlights the AI's capacity for creative thinking, it also demonstrates significant limitations in understanding and applying contextual information. The Broader Implications The observations from these Pokémon playthroughs offer valuable lessons for the ongoing development of AI systems. The "panic" response in Gemini 2.5 Pro and the misguided self-harm attempt in Claude highlight issues in emotional intelligence and context-aware decision-making. These challenges are crucial for developers to address as they aim to create more robust and adaptable AI models. Moreover, the collaborative and interactive nature of the Twitch streams provides a platform for public engagement and feedback, which can further refine the models. Industry Insights and Company Profiles Industry insiders view these Pokémon experiments as both entertaining and instructive. They offer a practical and relatable way to understand the strengths and weaknesses of AI models. Google DeepMind, known for its cutting-edge research in AI, continues to push the boundaries with models like Gemini 2.5 Pro. Anthropic, another key player in the AI landscape, focuses on creating safe, transparent, and beneficial AI systems, as evidenced by Claudia's ability to learn and improve. In summary, while these AI models show impressive problem-solving capabilities, they still struggle with context and emotional responses, areas that require further research and development. The public interest in these experiments underscores the growing fascination with AI and its potential applications in gaming and beyond.