A neural network architecture where connections form loops, letting the network maintain a form of memory across sequences.
A neural network architecture where connections form loops, letting the network maintain a form of memory across sequences. LSTMs and GRUs are improved versions that solve the vanishing gradient problem. Once the go-to for sequence tasks, now largely replaced by transformers for most applications.
Long Short-Term Memory.
The neural network architecture behind virtually all modern AI language models.
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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