Artificially generated data used for training AI models. Can be created by other AI models, simulations, or procedural generation. Useful when real data is scarce, private, or biased. Increasingly used to train and evaluate models, but risks introducing its own biases and distribution issues.
Techniques for artificially expanding training datasets by creating modified versions of existing data.
AI systems that create new content — text, images, audio, video, or code — rather than just analyzing or classifying existing data.
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.
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