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In a world where artificial intelligence is often presented as the solution to all our problems, the recent experience with Google Gemini reminds us that even the most advanced models can encounter serious limitations. During a playful test where Gemini was forced to confront the Pokémon universe, the results revealed some surprising behavior. Instead of demonstrating a clear and thoughtful strategy, the AI succumbed to panic attacks that led it to make impulsive and ineffective decisions. This experience perfectly illustrates that behind the veneer of high technology, AIs still have a lot to learn. In a world where artificial intelligence (AI) is often presented as the solution to all our problems, the recent test of the Google Gemini 2.5 Pro AI in the Pokémon universe reveals some surprising flaws. This powerful model, put to the test in a playful environment, proved to be less efficient than a child. This article explores the limitations of this AI by highlighting its erratic behavior and flawed game strategy. An Unexpected Test: Gemini Plays Pokémon AI enthusiasts are constantly putting these systems to the test, seeking to understand how far they can go. Recently, DeepMind, Google’s AI subsidiary, chose to integrate Gemini 2.5 Pro into a live interactive test on Twitch, entitled « Gemini Plays Pokémon. » The idea behind this challenge was to evaluate the AI’s reasoning abilities when faced with a complex task, often perceived as accessible even for a young child. Strange Behavior in the Face of Game Challenges During this game, Gemini not only completed the game; she also exhibited behavior so unexpected that it attracted the attention of viewers. The AI experienced phases of panic. which clearly disrupted its ability to make rational decisions. According to the Google report, during critical moments, particularly when its Pokémon were at risk of being knocked out, the model succumbed to stress, leading to a deterioration in its thinking. Impulsive and Ineffective DecisionsRather than relying on well-thought-out strategies, Gemini 2.5 Pro tends to react impulsively, often making ill-advised decisions. The report notes that these behaviors occurred frequently enough that Twitch chat observers noted these anomalies. When battling opponents, the AI abandoned all forms of planning, calling into question its supposed superiority. A Disproportionate Learning Time It’s also worth noting that, to make progress in the game, Gemini required several hundred hours of experience, a disproportionate amount of time compared to the dozens of hours it would take a child to master the rules of Pokémon. These results raise questions about the effectiveness of AI models in environments where flexibility and adaptability are paramount. Comparison with Other AIs Like Gemini, other artificial intelligences such as Anthropic’s Claude have also shown their flaws while playing Pokémon. During one sequence of the game, Claude developed an unpredictable strategy: deliberately losing all his Pokémon to escape a hopeless situation. This type of reasoning, while creative, also reveals notable limitations and an incomplete contextual understanding of the game’s mechanics. Conclusion: A nuanced reality regarding AI capabilities
These tests on Gemini 2.5 Pro and other AI systems clearly demonstrate that, despite their technological advances, these systems have significant limitations.
While they may excel in certain areas, the failures encountered in the Pokémon universe are a reminder that AI, even the most powerful, remains prone to flaws in its reasoning and adaptability.
To deepen your understanding of the capabilities and limitations of modern AI, consult articles such as « Meta AI in Europe » or « The Limits of Language Models in the Face of Modern Technologies. »
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