智能化科研（AI4R）是科研方法的重大变革。提出科技界不仅要关注科学智能（AIfor Science，AI4S），更要重视技术智能（AI for Technology，AI4T）；不仅要关注大语言模型（LLM），更要重视大科学模型（LSM）。同时提出，人工智能的突破主要不是靠大算力，而是计算模型的转变，中国应当争取在基础模型上做出颠覆性的创新；智能化科研适合做复杂问题的组合搜索，神经网络模型也许已接近能处理困难问题的复杂度阈值点；智能化科研的一种趋势是放弃绝对性，拥抱不确定性，一定时期内要适当容忍“黑盒模型”
AI for research (AI4R) is a significant change in research methods. The scientific and technological circles should not only pay attention to "AI for Science" (AI4S), but also attach great importance to "AI for Technology" (AI4T); Not only should we focus on the Large Language Model (LLM), but we should also pay more attention to the Large Science Model (LSM). The breakthrough of artificial intelligence mainly relies not on large computing power, but on the transformation of computational models. China should strive to make disruptive innovations on foundation models. AI4R is suitable for combinatorial search of complex problems, and neural network models may be close to the complexity threshold point that can handle difficult problems. One trend in AI4R is to abandon absoluteness, embrace uncertainty, and we should tolerate "black-box models" appropriately for a certain period of time.
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