Are AI Capabilities Increasing Exponentially? A Competing Hypothesis

TL;DR

This paper challenges the claim that AI capabilities are growing exponentially by analyzing data and proposing a model that suggests an upcoming inflection point, emphasizing the fragility of exponential growth forecasts.

Contribution

It refutes prior exponential growth claims by fitting sigmoid curves to data and introduces a complex model decomposing AI capabilities into base and reasoning components.

Findings

The inflection point in AI growth has already passed according to current data.

A new model supports the hypothesis of an upcoming inflection point.

Existing exponential growth forecasts are fragile and potentially unreliable.

Abstract

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.