The broad field studying how to build AI systems that are safe, reliable, and beneficial.
The broad field studying how to build AI systems that are safe, reliable, and beneficial. Covers everything from preventing harmful outputs to ensuring advanced systems remain under human control. Distinct from AI ethics, which focuses more on social and moral questions.
The research field focused on making sure AI systems do what humans actually want them to do.
Systematically testing an AI system by trying to make it produce harmful, biased, or incorrect outputs.
Safety measures built into AI systems to prevent harmful, inappropriate, or off-topic outputs.
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.
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