AI遭遇灵魂拷问!这道题所有模型集体翻车,网友:我也不会啊
量子位·2025-05-19 07:48

Core Insights - The article discusses the challenges faced by AI models in solving complex reasoning problems, particularly in image reasoning tasks [1][2] - A specific problem involving the completion of a cube structure has garnered attention, revealing discrepancies in the answers provided by different AI models [5][12] Group 1: Problem Definition and AI Responses - The problem involves determining how many small cubes are needed to complete a larger cube structure [3] - Various AI models provided differing answers: o3 suggested 45 cubes, while Gemini 2.5 Pro suggested only 10 cubes [6][9] - The correct answer, based on calculations, indicates that 14 cubes are needed to complete a 3x3x3 cube, given the existing structure [10] Group 2: Understanding Discrepancies in AI Answers - The discrepancies in answers stem from the AI models' varying interpretations of the final cube's specifications [13][24] - o3 misinterpreted the final cube size as 5x5x5, leading to an incorrect answer, while Gemini 2.5 Pro viewed it as 4x4x4 [18][20] - DeepSeek and Qwen models assumed a 3x3x3 structure, which also contributed to their differing results [20][24] Group 3: Learning and Adaptation of AI Models - Some AI models can improve their accuracy through iterative attempts and learning from previous mistakes [25][30] - User interactions with models like o3 showed that providing hints could lead to correct answers in subsequent attempts [26][29] - The article suggests that the learning process of AI can be enhanced by clearer problem definitions and structured training [38][40]