In AI, bias has two meanings. Technical bias: a learnable parameter in neural networks that shifts the activation function. Social bias: systematic errors in AI outputs that reflect prejudices in training data or design choices. The second meaning is a major concern for fairness and responsible AI deployment.
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.
Browse our complete glossary or subscribe to our newsletter for the latest AI news and insights.