挑战主流观点：AI能力增长并非指数级，拐点或已出现
Are AI Capabilities Increasing Exponentially? A Competing Hypothesis
- 用更复杂模型分解基础与推理能力，发现各自改进速率不同
- 实证分析显示：当前数据下拐点已过，非未来将至
- 提醒警惕指数增长预测的脆弱性，适合关注AI趋势的人
快速提升的AI能力带来深远影响，从安全风险到劳动力市场变化。METR报告声称自2019年起AI能力呈指数增长。本文指出，现有数据并不支持这一结论，甚至在短期范围内也不成立。尽管METR使用逻辑斯蒂曲线拟合并推断拐点远在将来，我们对同一数据拟合逻辑斯蒂曲线后发现，拐点早已过去。此外，我们提出一个更复杂的模型，将AI能力拆分为基础能力和推理能力，二者分别具有独立的改进速率。理论证明该模型支持我们的假设：近期内将出现能力增长的拐点。本文目标并非建立自身严谨预测，而是揭示当前指数增长预测的脆弱性。
原文摘要 · Abstract (English)
Rapidly increasing AI capabilities have substantial real-world consequences, ranging from AI safety concerns to labor market consequences. The Model Evaluation & Threat Research (METR) report argues that AI capabilities have exhibited exponential growth since 2019. In this note, we argue that the data does not support exponential growth, even in shorter-term horizons. Whereas the METR study claims that fitting sigmoid/logistic curves results in inflection points far in the future, we fit a sigmoid curve to their current data and find that the inflection point has already passed. In addition, we propose a more complex model that decomposes AI capabilities into base and reasoning capabilities, exhibiting individual rates of improvement. We prove that this model supports our hypothesis that AI capabilities will exhibit an inflection point in the near future. Our goal is not to establish a rigorous forecast of our own, but to highlight the fragility of existing forecasts of exponential growth.
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