科学界使用AI基础模型增速惊人，但多数研究者仍在用较小模型。
The Rapid Growth of AI Foundation Model Usage in Science
- 首次大规模分析科学领域基础模型真实使用情况
- 2024年科学家采用模型平均比自研小26倍，远落后于研发端
- 用更大模型的论文发表在高影响力期刊，引用更多
我们首次对科学领域中人工智能基础模型的实际使用情况进行大规模分析，不依赖引文或关键词。结果显示，使用率以近乎指数级速度增长，最高集中在语言学、计算机科学和工程领域。视觉类模型使用最广泛，但语言模型占比持续上升。开源权重模型占据主导地位。随着AI开发者不断增大模型参数规模，科学家采用的模型却增长缓慢：2013年，科研采用的模型平均比自研小7.7倍，到2024年这一差距扩大至26倍。我们还发现，科学家使用较小模型可能限制其从AI赋能科学中获益——使用更大模型的论文更可能发表于高影响期刊并获得更高引用。
原文摘要 · Abstract (English)
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.
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