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Stanford HAI Report: AI participation in scientific research is rapidly increasing, moving from a supporting tool to scientific discovery.

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ME News message, April 23 (UTC+8), according to the science chapter of the "2026 AI Index Report" released by Stanford HAI, AI's participation and influence in scientific research continued to rapidly improve in 2025. Data shows that AI-related publications in natural sciences have reached approximately 80,150, an increase of 26% compared to 2024, and the proportion of AI research output in overall scientific research has risen from less than 1% in 2010 to 5.8%–8.8%. The report points out that frontier models show potential to surpass the average human level on specific tasks (such as ChemBench), but still face significant challenges in complex scientific practices (such as ReplicationBench, UnivEarth, PaperArena, BixBench), lagging behind human experts. Multiple scientific fields are systematically building AI infrastructure. For example, astronomy has released the first foundation model AION-1, the first visual benchmark AstroVisBench, and a 100TB training dataset; in the meteorological field, Aardvark Weather has for the first time replaced traditional numerical weather prediction processes end-to-end with a single machine learning system, and FourCastNet 3 generates 60-day global forecasts in less than 4 minutes, 8 to 60 times faster than previous methods. The report also mentions that although the first fully AI-generated paper accepted by a peer-reviewed workshop (produced by Sakana's AI Scientist-v2) has appeared, the list of experimentally verified AI scientific discoveries remains very short. Unlike the general AI field, most scientific AI models originate from academic and government institutions, and many are international collaborations. (Source: InFoQ)
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