The ability to understand and explain why an AI model made a particular decision.
The ability to understand and explain why an AI model made a particular decision. Critical for high-stakes applications like healthcare, finance, and law where decisions need justification. Deep learning models are often 'black boxes,' making this challenging. Techniques include attention visualization, SHAP values, and LIME.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
The research field focused on making sure AI systems do what humans actually want them to do.
The broad field studying how to build AI systems that are safe, reliable, and beneficial.
The science of creating machines that can perform tasks requiring human-like intelligence — reasoning, learning, perception, language understanding, and decision-making.
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