A new research paper explores how artificial intelligence is being used by manufacturing and materials science researchers in the U.S. The study found that AI is primarily employed for modeling processes and exploring design spaces, leading to cost and time savings. However, the effectiveness of AI tools is limited to areas with abundant data, and they require integration with traditional research methods. The paper suggests that while AI can accelerate sustaining innovations, continued support for empirical, computational, and theoretical research is crucial for disruptive advancements. AI
IMPACT AI shows promise in accelerating sustaining innovations in manufacturing and materials science, but requires integration with traditional methods for disruptive advances.
RANK_REASON The cluster contains an academic paper detailing research findings on the use of AI in specific scientific fields. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- Artificial intelligence
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- John Nelson
- machine learning
- ScienceCast
- U.S.
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