LLM Reasoning 相关度: 8/10

Are AI Capabilities Increasing Exponentially? A Competing Hypothesis

Haosen Ge, Hamsa Bastani, Osbert Bastani
arXiv: 2602.04836v1 发布: 2026-02-04 更新: 2026-02-04

AI 摘要

论文反驳了AI能力呈指数增长的观点,提出AI能力增长可能已过拐点,并构建复杂模型进行论证。

主要贡献

  • 反驳了AI能力指数增长的观点
  • 指出现有模型预测的脆弱性
  • 提出AI能力分解为基础能力和推理能力的复杂模型
  • 论证AI能力增长可能已过拐点

方法论

通过拟合sigmoid曲线和构建AI能力分解模型,分析现有数据,论证AI能力增长的拐点可能已经过去。

原文摘要

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.

标签

AI能力增长 指数增长 拐点 预测 模型

arXiv 分类

cs.AI