AI GLOSSARY
Data Drift
Data drift occurs when the distribution between the inputs of a machine learning model change, which can cause a model to perform poorly. This shift happens when the characteristics of the data used for training the model differ from the data it encounters in production. Monitoring and addressing data drift is crucial to ensure that models continue to make accurate predictions in real-world applications.
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AI at the Edge: Transforming Defence Operations
Al Bowman:
At the edge, every second counts, and every decision matters. To gain and hold an advantage, Defence must design AI and Machine Learning for where...
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The Drone Blockade: Airports Grapple with A Growing Threat
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An uninvited buzz of drones in the air is forcing airports worldwide to rethink their approach to security. The implications are serious, impacting...
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