A learning approach where an agent learns by interacting with an environment and receiving rewards or penalties.
A learning approach where an agent learns by interacting with an environment and receiving rewards or penalties. It discovers optimal strategies through trial and error. How AlphaGo mastered Go, how robots learn to walk, and a key ingredient in training language models through RLHF.
Reinforcement Learning from Human Feedback.
A model trained to predict how helpful, harmless, and honest a response is, based on human preferences.
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.
An autonomous AI system that can perceive its environment, make decisions, and take actions to achieve goals.
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