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Neural network approach makes AI uncertainty checks far more efficient

This story is from 2026-08-20. It is preserved in the archive; the latest stories are on the live feed.

McGill University researchers have developed a more energy-efficient method of building AI systems that are better at measuring—and indicating—their own uncertainty. This will help users determine when human oversight is needed, when additional data should be collected and when a model is being ask…

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  1. 2026-08-20 19:20 · TechXplore AI & ML
    Neural network approach makes AI uncertainty checks far more efficient

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