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The missing data for intelligent scientific instruments
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AI
DOI：10.1038/s41592-025-02995-7.png)
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Abstract
En 中文
Most scientific instruments currently discard rich streams of commands, data and metadata from which AI systems could learn to conduct experiments with expert-level decision-making and troubleshooting skills. Recording and using this data at scale requires rethinking what data to store, incentivizing large-scale cooperation, and determining how to quantify the reliability of such autonomous systems.
Keywords:
AI systems
scientific instruments
data recording
autonomous decision-making
reliability quantification
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