AI GLOSSARY
Explainable AI (XAI)
Explainable AI (XAI) refers to methods and techniques that make the decision-making processes of AI systems transparent and understandable to humans. Unlike black box models, explainable AI provides insights into how an AI model reaches its conclusions, allowing users to interpret, trust, and verify the outputs. This is particularly important in high-stakes applications like healthcare, finance, and autonomous systems, where understanding the rationale behind AI decisions is critical.
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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...
5 min read
Insuring Against AI Risk: An interview with Mike Osborne
by Nick Sherman
When used by malicious actors or without considerations for transparency and responsibility, AI poses significant risks. Mind Foundry is working with...
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News, announcements, and blogs about AI in high-stakes applications.