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Exploring the role of large language models in the scientific method: from hypothesis to discovery
2025·24 Zitationen·npj Artificial IntelligenceOpen Access
Volltext beim Verlag öffnen24
Zitationen
13
Autoren
2025
Jahr
Abstract
Abstract We review how Large Language Models (LLMs) are redefining the scientific method and explore their potential applications across different stages of the scientific cycle, from hypothesis testing to discovery. We conclude that, for LLMs to serve as relevant and effective creative engines and productivity enhancers, their deep integration into all steps of the scientific process should be pursued in collaboration and alignment with human scientific goals, with clear evaluation metrics.
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Autoren
Institutionen
- Tufts University(US)
- King Abdullah University of Science and Technology(SA)
- Zuse Institute Berlin(DE)
- Network Rail(GB)
- Nvidia (United States)(US)
- University of Southampton(GB)
- Stanford University(US)
- University of Chicago(US)
- Santa Fe Institute(US)
- University of Edinburgh(GB)
- Jožef Stefan Institute(SI)
- Science for Life Laboratory(SE)
- Karolinska University Hospital(SE)
- Karolinska Institutet(SE)
- Centre for Sustainable Healthcare(GB)
- The Alan Turing Institute(GB)
- King's College London(GB)
- The Francis Crick Institute(GB)
Themen
Topic ModelingMachine Learning in Materials ScienceArtificial Intelligence in Healthcare and Education