We present the first large-scale analysis of AI foundation model usage in science - not just citations or keywords. We find that adoption has grown rapidly, at nearly-exponential rates, with the highest uptake in Linguistics, Computer Science, and Engineering. Vision models are the most used foundation models in science, although language models' share is growing. Open-weight models dominate. As AI builders increase the parameter counts of their models, scientists have followed suit but at a much slower rate: in 2013, the median foundation model built was 7.7x larger than the median one adopted in science, by 2024 this had jumped to 26x. We also present suggestive evidence that scientists' use of these smaller models may be limiting them from getting the full benefits of AI-enabled science, as papers that use larger models appear in higher-impact journals and accrue more citations.

翻译：我们首次对人工智能基础模型在科学领域的使用情况进行了大规模分析——不仅限于引用或关键词统计。研究发现，其采用率增长迅速，接近指数级速度，其中语言学、计算机科学与工程学领域的应用最为广泛。视觉模型是科学领域最常用的基础模型，尽管语言模型所占份额正在增长。开源权重模型占据主导地位。随着AI开发者不断提升模型参数量，科学家虽随之跟进但增速远为缓慢：2013年，构建的基础模型中位数规模是科学应用模型中位数的7.7倍，到2024年这一差距已扩大至26倍。我们还发现初步证据表明，科学家使用较小规模模型可能限制其充分获取AI赋能科学的全部效益——因为采用较大模型的论文往往发表于更高影响力的期刊并获得更多引用。