GPT-5.2考赢人类，OpenAI警告：大模型能力已过剩，AGI天花板不是AI

Core Insights - OpenAI's co-founder Greg Brockman announced that GPT-5.2 surpassed human baseline levels in the ARC-AGI-2 benchmark test, highlighting a performance paradox where models excel in tests but struggle in real-world applications [1][2] - The ARC-AGI-2 benchmark, designed to assess AI's abstract reasoning and inductive capabilities, aims to differentiate genuine reasoning from mere pattern matching [1][2] Benchmark and Performance - The ARC-AGI-2, developed by François Chollet and his team, tests AI's ability to handle unseen tasks without relying on large training datasets, thus eliminating the possibility of achieving high scores through data memorization [1][2] - Poetiq, an AI company focusing on meta-system architecture, achieved a 75% accuracy rate on the ARC-AGI-2 dataset with its GPT-5.2X-High model, surpassing the previous state-of-the-art (SOTA) by 15 percentage points [5][6] - Prior to Poetiq's introduction, GPT-5.2 was already close to human average performance, which is approximately 60% on the ARC-AGI-2 benchmark [5] Capability Overhang - OpenAI's recent communication emphasized the concept of "Capability Overhang," indicating a significant gap between what current models can do and how they are utilized in practice [10] - The future progress of AGI will depend not only on model advancements but also on effective usage and integration into real-world applications [10][11] Human-Machine Collaboration - Achieving AGI requires collaboration between models and humans, emphasizing the need to teach users how to effectively utilize AI [11] - The challenge lies in integrating AI into workflows, as many organizations purchase AI solutions without altering existing processes [12] Future Directions - The emergence of Poetiq and OpenAI's insights suggest a shift in AI competition from merely model parameters to system design, processes, and human-machine collaboration [18][19]