
Advancements in Artificial Intelligence (AI), including generative systems like ChatGPT and DeepSeek, are motivating a revolution in academic research computing. Academic researchers are turning to AI to make fundamental strides in their research, creating and providing new models and algorithms, AI-ready datasets, AI-relevant cyberinfrastructure, and more. However, the academic sphere lags behind the private sector in AI resource availability and adoption. Science gateways have long facilitated academic research by simplifying the access and use of advanced computing resources, and promoting collaboration. Can science gateways help academic research communities by promoting access to advanced AI resources, new algorithms and models, and AI-ready datasets?The NSF Center of Excellence for Science Gateways (SGX3) founded an initiative called the AI Blueprint Factory to address this question. The Blueprint Factory will identify technical capabilities required to support evolving scientific and computing needs, and consider how science gateways can help.The purpose of the AI Blueprint Factory is to ascertain the AI needs of research communities that use national-scale computing infrastructure, and to make 5 to 10 year forecasts of needed features and resources. Its study team is interviewing researchers across disciplines and seniority levels to determine perceived needs, opportunities, and gaps in AI research support. The focus is not on supporting core AI research, but rather on fostering the utilization of AI techniques in domain science research.In this paper, we introduce and describe the study, and summarize the initial set of researcher interviews.
high performance computing, machine learning, cyberinfrastructure, science gateways, scientific software, artificial intelligence
high performance computing, machine learning, cyberinfrastructure, science gateways, scientific software, artificial intelligence
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
