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AI Applications Across the Infrastructure Life Cycle
From planning to decommissioning, every stage of the infrastructure asset life cycle has its own priorities and needs. Here are the ways that AI can...
AI GLOSSARY
Interpretability
Interpretability refers to the ability to understand and explain how an AI or machine learning model makes its decisions. By providing insights into the relationship between inputs and outputs, an interpretable model openly shows its internal workings and provides information that makes it easier for users to trust, verify, and act on the model’s predictions. Interpretability is especially important in high-stakes applications where transparency is required to ensure accountability and fairness.
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AI-enabled Acoustic Intelligence for Counter-UAS
by Syreeta Cummings
Unmanned Aircraft Systems (UAS) are now a staple of modern warfare, now responsible for 60% of targets destroyed in the Ukraine-Russia war....
5 min read
AI for Sensor Fusion: Sensing the Invisible
by Nick Sherman
In Defence and National Security, mission-critical data often emerges from a multitude of different sensor types. With AI, we can bring this...
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